Environmental Impact and Levelised Cost of Energy Analysis of Solar Photovoltaic Systems in Selected Asia Pacific Region: a Cradle-To-Grave Approach

sustainability

Article Environmental Impact and Levelised Cost of Energy Analysis of Solar Photovoltaic Systems in Selected Asia Paciﬁc Region: A Cradle-to-Grave Approach

Norasikin Ahmad Ludin 1,*, Nurfarhana Alyssa Ahmad Affandi 1, Kathleen Purvis-Roberts 2, Azah Ahmad 3, Mohd Adib Ibrahim 1 , Kamaruzzaman Sopian 1 and Suﬁan Jusoh 4

1 Solar Energy Research Institute (SERI), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia; [email protected] (N.A.A.A.); [email protected] (M.A.I.); [email protected] (K.S.) 2 W.M. Keck Science Department, Claremont McKenna, Pitzer, and Scripps Colleges, Claremont, CA 91711, USA; [email protected] 3 Sustainable Energy Development Authority (SEDA), Putrajaya 62100, Malaysia; [email protected] 4 Institute of Malaysian and International Studies (IKMAS), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia; suﬁ[email protected] * Correspondence: [email protected]

Abstract: Sustainability has been greatly impacted by the reality of budgets and available resources as a targeted range of carbon emission reduction greatly increases due to climate change. This study analyses the technical and economic feasibility for three types of solar photovoltaic (PV) renewable energy (RE) systems; (i) solar stand-alone, a non-grid-connected building rooftop-mounted structure, (ii) solar rooftop, a grid-connected building rooftop-mounted structure, (iii) solar farm, a grid- connected land-mounted structure in three tropical climate regions. Technical scientific and economic tools, including life cycle assessment (LCA) and life cycle cost assessment (LCCA) with an integrated framework from a Malaysian case study were applied to similar climatic regions, Thailand, and Citation: Ahmad Ludin, N.; Ahmad Indonesia. The short-term, future scaled-up scenario was defined using a proxy technology and Affandi, N.A.; Purvis-Roberts, K.; Ahmad, A.; Ibrahim, M.A.; Sopian, K.; estimated data. Environmental locations for this scenario were identified, the environmental impacts Jusoh, S. Environmental Impact and were compared, and the techno-economic output were analysed. The scope of this study is cradle-to- Levelised Cost of Energy Analysis of grave. Levelised cost of energy (LCOE) was greatly affected due to PV performance degradation Solar Photovoltaic Systems in rate, especially the critical shading issues for large-scale installations. Despite the land use impact,

Selected Asia Pacific Region: A increased CO2 emissions accumulate over time with regard to energy mix of the country, which Cradle-to-Grave Approach. requires the need for long-term procurement of both carbon and investment return. With regards Sustainability 2021, 13, 396. to profitably, grid-connected roof-mounted systems achieve the lowest LCOE as compared to other https://doi.org/10.3390/su13010396 types of installation, ranging from 0.0491 USD/kWh to 0.0605 USD/kWh under a 6% discounted rate. A simple payback (SPB) time between 7–10 years on average depends on annual power generated by Received: 16 November 2020 the system with estimated energy payback of 0.40–0.55 years for common polycrystalline photovoltaic Accepted: 29 December 2020 technology. Thus, maintaining the whole system by ensuring a low degradation rate of 0.2% over a Published: 4 January 2021 long period of time is essential to generate benefits for both investors and the environment. Emerging

Publisher’s Note: MDPI stays neu- technologies are progressing at an exponential rate in order to ﬁll the gap of establishing renewable tral with regard to jurisdictional clai- energy as an attractive business plan. Life cycle assessment is considered an excellent tool to assess ms in published maps and institutio- the environmental impact of renewable energy. nal afﬁliations. Keywords: solar photovoltaic; greenhouse gas emission; levelised cost of energy; energy payback time; return of investment

Copyright: © 2021 by the authors. Li- censee MDPI, Basel, Switzerland. This article is an open access article 1. Introduction distributed under the terms and conditions of the Creative Commons At- Sustainability and policies promoting economic, ﬁnancial, and social inclusion will tribution (CC BY) license (https:// have limited impact if they cannot be sustained. A regional economic forum for different creativecommons.org/licenses/by/ economies or countries can be used to promote a balanced, inclusive, sustainable, inno- 4.0/). vative, and secured growth by accelerating regional economic integration. The policy

Sustainability 2021, 13, 396. https://doi.org/10.3390/su13010396 https://www.mdpi.com/journal/sustainability Sustainability 2021, 13, 396 2 of 21

commitments and agreements are a good start for such a goal. However, the pursuit of an inclusive and sustainable community should not only end with official statements, but also requires implementation [1]. The Asia and Pacific region has been leading in this field, as reflected in its steady growth from a 60% share of global growth in renewable energy power generation (excluding hydro) in 2016 [2]. All Asia-Pacific Economic Cooperation (APEC) economies have individual energy or emissions intensity targets and have collectively set a target equivalent to reducing energy intensity by 45% between 2005 and 2035 [3]. However, the realities of funding and resources should be considered in the planning and implementation of projects. Likewise, policies that promote economic growth and stability are essential in ensuring a steady stream of financial resources that can be used to promote inclusive growth while convincing consumers of the value of such cost [4]. The current global average cost of electricity from utility-scale solar photovoltaic (PV) is USD 0.053/kWh [5]. This amount represents a 73% decrease since 2010 because of the fast pace of innovation, which has infused competitive pressure into the energy market. The overall reduction depends on drivers, such as balance-of-system (BOS), operation and maintenance, and capital costs. Given the effort of setting suitable policies in place, the cost of PV and renewables can decrease further in the near future [6]. Many countries in Asia have set individual energy and emission targets and adopted national renewable energy policies to achieve sustainability in every development sector [7]. The main drivers to strengthen solar PV cumulative capacity includes policies, regulations, programmes, and government support. These drivers will simultaneously increase the system flexibility, penetrating ambitious power market reform, installing new transmission lines, and the expansion of distributed generation. These new policies are expected to speed up deployment of solar energy [8]. Market and policy frameworks need to evolve in order to manage simultaneously these multiple objectives. Although the deployment timing and implementation transition uncertainty are high, if existing grid integration and infrastructure challenges are addressed, this uncertainty can be reduced with proposed federal tax reforms, international trade, and energy policies, which can have implications for the financial impact of renewables and alter their expansion over our forecast period [9]. Since 2014, China and Japan have long maintained a steady growth of renewable energy capacity compared with other countries in the region (Table1). This commitment to renewable energy was encouraged by the United Nations’ Sustainable Development Goals in fighting climate change and environmental deterioration [10]. China is working actively to meet its 40% energy intensity reduction target by 2025 (from its 2005 base) by expanding public transportation systems and strengthening fuel economy standards [11]. China expects the use of non-fossil primary energy to reach 20% by 2030 with a CO2 reduction of 60–65% [12]. Malaysia is increasing the implementation of renewable energy, based on the example of countries leading in renewable energy capacity, especially those in northeast Asia [12]. Countries such as Japan, Republic of Korea, and Taiwan are committed to energy efficiency goals well beyond the 45% target. Japan has strengthened its energy efficiency measures by liberalizing its electricity and gas markets and setting a CO2 reduction goal of 25% by 2030 from base emissions in 2013 [13]. Moving towards a greener future, countries set up goals and plans based on regional progress and targets. However, setting goals requires comprehensive analysis on the renewable technology and its implementation, in this case, solar photovoltaic (PV) systems. An operating PV system has a significantly lower environmental and techno-economic impact compared to any electrical generation power plant, but the cost is higher. Thus, a thorough analytical foundation is needed to demonstrate the benefit of a PV system and provide reliable data for evaluation purposes for future development guidelines. This study aims to assess 6 PV systems characteristics from 3 different countries, namely, Thailand, Indonesia, and Malaysia. The three different types of systems include standalone, rooftop, and solar farm systems. The different PV systems will be analysed using life cycle assessment (LCA) and life cycle cost assessment (LCCA). Results are to be compared under functional unit of CO2 equivalent emission per power generation (CO2 eq/kWh) of a PV Sustainability 2021, 13, 396 3 of 21

2 system, emission per square meter (CO2 eq/m ), and capital cost of system per power generation (USD/kWh) of the PV system.

Table 1. Total Solar Energy Capacity in Asia (2014–2018) [13].

Total Solar Energy Capacity (MW) Asia Countries 2014 2015 2016 2017 2018 Brunei 1 1 1 1 1 Darussalam Cambodia 9 12 18 28 28 China 28,402 43,552 77,802 130,816 175,032 Chinese Taipei 620 842 1245 1768 2618 India 3518 5396 9647 17,873 27,098 Indonesia 42 51 58 59 60 Japan 23,339 34,150 42,040 49,040 55,500 Kazakhstan 5 57 57 59 209 Korea DPR 5 8 10 11 11 Korea Rep 2481 3613 4502 5835 7862 Malaysia 166 229 279 317 438 Philippines 23 165 759 886 886 Singapore 26 46 97 116 150 Thailand 1304 1425 2451 2702 2725 Viet Nam 5 5 5 8 106 Total 59,946 89,552 138,971 209,519 272,724

2. Methodology Three types of PV systems were analysed for this comparison, solar farm, solar rooftop, and solar standalone system. An LCA and LCCA study is carried out in four distinct phases [14]. Phase 1: Goal and scope of study. The life cycle study is a process-based method that covers the entire system from cradle to grave. Within this scope, two different methods, experimental study and simulation tool approach, strengthen the data evaluation. The Sustainability 2021, 13, x FOR PEER REVIEW 4 of 22 scope of the study assumed a 25-year lifetime for all PV systems and case studies were based on a two-year matured system (Figure1).

Figure 1. Photovoltaic (PV) systems life cycle timeline. Figure 1. Photovoltaic (PV) systems life cycle timeline.

The system boundaries covered the eco-sphere and techno-economic effects, but not techno-sphere and social effects. This approach accounted for impacts only related to normal operations of processes and products, based on the assumption that no spill, accident, and/or natural disaster occurs throughout the entire process. The study estimated the effects based on the average maintenance and replacement of the three case studies [15]. Phase 2: Life cycle inventory (LCI). LCI is based on the identification and quantification assessment of the field in accordance with the environmental assessment methods [16]. The inventory data primarily include all materials and energy flows between life- cycle phases based on the designed framework [17]. Primary and secondary data were utilised to complete the inventory using the Ecoinvent database on SimaPro software. Data collection and calculations were associated with the functional system [18], emission per square meter (CO2 eq/m2), CO2 equivalent emission per power generation (CO2 eq/kWh) of a photovoltaic system, and capital cost of the system per power generation (USD/kWh). Three types of PV balance-of-system (BOS) for the case study were identified. (i) Solar stand-alone, a non-grid-connected building rooftop-mounted structure (Figure 2), (ii) solar rooftop, a grid-connected building rooftop-mounted structure (Figure 3), (iii) solar farm, land-mounted structure (Figure 4).

Figure 2. Solar standalone system balance-of-system (BOS).

The whole standalone system is connected to a string that holds 20 PV modules due to its low peak power. The generated DC current passes through the charge controller, which prevents the battery from being overcharged and dissipates excess power from load resistance. The fuse and isolation switch protect the PV from accidental shorting of wires and automate switching to off when PV is not generating electricity. The fuse and Sustainability 2021, 13, x FOR PEER REVIEW 4 of 22

Figure 1. Photovoltaic (PV) systems life cycle timeline. Sustainability 2021, 13, 396 4 of 21 The system boundaries covered the eco-sphere and techno-economic effects, but not techno-sphere and social effects. This approach accounted for impacts only related to normal operationsThe system of proc boundariesesses and covered products, the based eco-sphere on the and assumption techno-economic that no spill, effects, accident, but and/ornot techno-sphere natural disaster and occurs social effects.throughout This th approache entire accountedprocess. The for study impacts estimated only related the ef- fectsto normal based on operations the average of processes maintenance and products,and replacement based on of the the assumption three case studies that no [15]. spill, accident,Phase and/or2: Life naturalcycle inventory disaster occurs (LCI). throughout LCI is based the on entire the process.identification The study and estimated quantifica- tionthe assessment effects based of on the the field average in accordance maintenance with and replacementthe environmental of the three assessment case studies methods [15]. [16]. ThePhase inventory 2: Life cycle data inventory primarily (LCI). include LCI is all based materials on the identificationand energy andflows quantification between life- cycleassessment phases ofbased the fieldon the in accordancedesigned framewor with thek environmental [17]. Primary assessment and secondary methods data [ 16were]. utilisedThe inventory to complete data primarilythe inventory include using all materialsthe Ecoinvent and energy database flows on between SimaPro life-cycle software. Dataphases collection based on and the calculations designed framework were associated [17]. Primary with andthe functional secondary datasystem were [18], utilised emission to complete the inventory using the Ecoinvent database on SimaPro software. Data collection per square meter (CO2 eq/m2), CO2 equivalent emission per power generation (CO2 and calculations were associated with the functional system [18], emission per square eq/kWh) of a photovoltaic system, and capital cost of the system per power generation meter (CO eq/m2), CO equivalent emission per power generation (CO eq/kWh) of a (USD/kWh).2 2 2 photovoltaic system, and capital cost of the system per power generation (USD/kWh). Three types of PV balance-of-system (BOS) for the case study were identified. (i) Solar Three types of PV balance-of-system (BOS) for the case study were identified. (i) Solar stand-alone, a non-grid-connected building rooftop-mounted structure (Figure 2), (ii) so- Sustainability 2021, 13, x FOR PEER REVIEWstand-alone, a non-grid-connected building rooftop-mounted structure (Figure2), (ii) solar5 of 22 larrooftop, rooftop, a grid-connecteda grid-connected building building rooftop-mounted rooftop-mounted structure structure (Figure (Figure3), (iii) solar3), (iii) farm, solar farm,land-mounted land-mounted structure structure (Figure (Figure4). 4).

isolation switch are optional to the complete system, but its implementation can save energy and improve battery life. A battery bank is typical for a stand-alone system because it stores excess energy generated and allows flexible usage time at night. The stored electricity is directed to the DC load demand before being transferred to the inverter and converted into AC current for the AC load. The BOS for a rooftop PV system can include one or more strings, in accordance with market demand. The generated DC current is converted into AC through the inverter, which can uphold about 6 to 7 strings. If the system production is sufficient, a distribution board is needed for load power distribution that can be fed by 10 inverters. If the power production fails to reach up to 10 inverters, a distribution board is unnecessary and is connected via a stand-alone system. A substation is set to a 11 kV switchgear to manage the system voltage before electricity export to the grid. If necessary, a transformer can be includedFigureFigure 2.in 2. Solar theSolar loop standalone standalone before system systemexporting balance-of-system the electricity. (BOS). (BOS).

FigureFigure 3. Solar rooftop systemsystem BOS. BOS.

Figure 4. Solar farm system BOS.

The BOS for the solar farm uses an entirely different system due to the large volume of electricity management. The system utilizes a distribution board and a Burnell Cabin bundle, which includes a step-up transformer, a metering system, and a communication or remote monitoring system. These bundles handle large voltage efficiently. A substation is required as a switchgear to manage the system voltage before exportation to the grid. A metering cabinet is needed to record the imported and exported power. Finally, the power reaches the point of connection to the main national grid. Sustainability 2021, 13, x FOR PEER REVIEW 5 of 22

Sustainability 2021, 13, 396 5 of 21 Figure 3. Solar rooftop system BOS.

Figure 4. Solar farm system BOS. Figure 4. Solar farm system BOS. The whole standalone system is connected to a string that holds 20 PV modules due to itsThe low BOS peak for power.the solar The farm generated uses an DCentirely current different passes system through due the to charge the large controller, volume of whichelectricity prevents management. the battery The from system being overcharged utilizes a distribution and dissipates board excess and power a Burnell from loadCabin bundle,resistance. which The includes fuse and a isolationstep-up transformer, switch protect a themetering PV from system, accidental and shorting a communication of wires or andremote automate monitoring switching system. to off These when bundles PV is not handle generating large electricity. voltage efficiently. The fuse and A substation isolation is switchrequired are as optional a switchgear to the completeto manage system, the system but its voltage implementation before exportation can save energy to the and grid. A improvemetering battery cabinet life. is Aneeded battery to bank record is typical the imported for a stand-alone and exported system power. because Finally, it stores the powerexcess reaches energy the generated point of and connection allows flexible to the usagemain national time at night. grid. The stored electricity is directed to the DC load demand before being transferred to the inverter and converted into AC current for the AC load. The BOS for a rooftop PV system can include one or more strings, in accordance with market demand. The generated DC current is converted into AC through the inverter, which can uphold about 6 to 7 strings. If the system production is sufficient, a distribution board is needed for load power distribution that can be fed by 10 inverters. If the power production fails to reach up to 10 inverters, a distribution board is unnecessary and is connected via a stand-alone system. A substation is set to a 11 kV switchgear to manage the system voltage before electricity export to the grid. If necessary, a transformer can be included in the loop before exporting the electricity. The BOS for the solar farm uses an entirely different system due to the large volume of electricity management. The system utilizes a distribution board and a Burnell Cabin bundle, which includes a step-up transformer, a metering system, and a communication or remote monitoring system. These bundles handle large voltage efficiently. A substation is required as a switchgear to manage the system voltage before exportation to the grid. A metering cabinet is needed to record the imported and exported power. Finally, the power reaches the point of connection to the main national grid. Phase 3: Life cycle impact assessment (LCIA). LCIA was separated into two parts; energy and emission impact analysis and economic fluctuation impact analysis. The results were combined and further refined for discussion. The various system parameters were normalized under the specified functional unit in Phase 2. (a) Energy and emission impact analysis Cumulative Energy Demand (CED) is the aggregate energy used during systems life cycle production. Energy payback is the energy produced by RE technology for the 25-year lifetime of the system, divided by the energy consumed to initially manufacture the system itself. The energy payback time (EPBT) is calculated based on the following Equation (1) [19]: EPBT = CED (MJ)/LEP (MJ), (1) Sustainability 2021, 13, 396 6 of 21

CED (MJ) = EM + ET + EI + ED, (2) Localized energy production (LEP) is the cumulative energy produced by the PV system for 25 years. Cumulative energy demand (CED) in Equation (2) is the energy consumed during; manufacturing phase (EM), transportation phase (ET), installation phase (EI), and disposal phase (ED). The energy consumed to manufacture PV system is based on country grid electricity mix. Greenhouse gas (GHG) emission rate from the grid electricity mix can be calculated as Equation (3) below [20]: gCO2 Total GHG emission during life cycle (gCO2) GHG emission rate = . (3) kWh kWh Annual power generation year × Lifetime (year)

The avoided GHG emission (CO2 equivalent emission/kWh) of the PV system that produce clean energy to the grid for 25 years can be calculated with Equation (4):

W G = . (4) I × η × PR × LT × A

Where I is irradiation (kWh/m2/year), η is conversion efﬁciency, PR is the performance ratio, LT is PV lifetime (year), and A is the area of module (m2). Emission reduction (ER) refers to the difference between baseline and project emissions when the same amount of power is generated.

ER (emission reduction) = BE (baseline emission) − PE (project emission), (5)

BE = EG × EFgrid, (6) BE is the amount of emissions generated by the country grid electricity mix when generating the same amount of power as the PV power plants; PE is the quantity of emissions generated by PV power plants, which is zero; EG is the annual electricity generation of the PV system project, (MWh/year); and EFgrid is the combined emission factor for the grid, (tCO2/MWh) [21]. (b) Economic ﬂuctuation impact analysis Economic analysis is a time-dependent formula with a variety of variables, including the discount factor, time-variant failure probability at time, single present value factor, and annuity present value factors. The levelised cost of energy (LCOE) as shown in Equation (7) only considers the cost of the life cycle and the amount of energy generated; it can eliminate favouritism or bias between technologies [22].

LCC LCOE = . (7) LEP LEP is the amount of energy generated by the PV power plant for 25 years. A low value of LCOE is preferred because it shows that a small amount of money is needed to produce one unit of energy. The overall cost of the project (LCC) is calculated with Equation (8) [23]. This cost is inﬂuenced by several parameters, such as investment (CI), operating, maintenance and repair (COMR), replacement (Crep) and other costs (CO), and residual value (Cres). LCC analysis is an analysis based on a baseline case study and uses an assumption value to forecast future value. In this study, electricity price changes are not considered since LCC uses a discounted rate to be able to compare the results over three different regions. LCC = C1 + COMR + Crep + CO − Cres (8) The payback period is the number of years required to recover the initial investment or early outﬂow. A short PB period is highly coveted, because capital gains will be available Sustainability 2021, 13, x FOR PEER REVIEW 7 of 22

produce one unit of energy. The overall cost of the project (LCC) is calculated with Equa- tion (8) [23]. This cost is influenced by several parameters, such as investment (CI), operating, maintenance and repair (COMR), replacement (Crep) and other costs (CO), and residual value (Cres). LCC analysis is an analysis based on a baseline case study and uses an assumption value to forecast future value. In this study, electricity price changes are not considered since LCC uses a discounted rate to be able to compare the results over three different regions.

LCC = C +C +C +C − C (8) Sustainability 2021, 13, 396 7 of 21 The payback period is the number of years required to recover the initial investment or early outflow. A short PB period is highly coveted, because capital gains will be available early and will reduce the risk of the investment. The equation below was used to obtain the refundearly period. and will PB reducewas calculated the risk ofby the using investment. the following The equationEquation below(9) [24]: was used to obtain the refund period. PB was calculated by using the following Equation (9) [24]: (C − Cumulative cash flow before n) PB = (n−1) + (9) Current (C − cashCumulative flow n cash flow before n) PB = (n − 1) + 1 (9) For this calculation, n is the recovery year when annualCurrent cash cash flow flow exceeds n the initial investment. Two typesForthis of PB calculation, periods were n is included the recovery in the year economic when annual analysis: cash a simple flow exceeds PB the initial period (SPB) andinvestment. the discounted Two types PB period of PB periods (DPB). The were SPB included period in ignores the economic the time analysis: value a simple PB of money, whereasperiod the (SPB) DPB and period the discountedof the discount PB period considers (DPB). the Thetime SPB value period of money. ignores the time value Phase 4: Interpretationof money, whereas. Data the validation DPB period and ofverification the discount were considers conducted the thoroughly time value of money. with the reference Phaseflow, 4:as Interpretation.stated in the system Data validation boundaries, and ISO verification standards were for conductedenviron- thoroughly mental and policywith theguidelines, reference Ecoinvent flow, as stated data inbase the for system material boundaries, value and ISO environmental standards for environmental impact assessmentand policy [25]. guidelines, Ecoinvent database for material value and environmental impact Economicassessment differences [25 between]. regions were compared in terms of regional policy standards, regionalEconomic tariff extraction differences and financial between rate regions levelling were (Figure compared 5). The in values terms were of regional policy assessed and calculatedstandards, based regional on the tariff benefits extraction received and for financial the power rate generated levelling (Figurebased on5). The values market economieswere [26]. assessed Impact and assessment calculated re basedsults were on the interpreted benefits receivedbased on forGHG the emis- power generated sions and financialbased outcomes on market without economies consider [26].ing Impact geographical assessment impact results due to were noncompa- interpreted based on rable bases. GHG emissions and financial outcomes without considering geographical impact due to noncomparable bases.

Figure 5. Study framework. Figure 5. Study framework.

Selected Case Studies Economic ﬂuctuation analysis was normalized with a basis of comparison for purposes between country economies, which have variety of market value. In the assessment of variation of the systems and product market value during the selected timeline, the case study systems were expected to fulﬁl all the listed criteria below: i. A two-year matured system; ii. Location in Asian countries with a tropical climate; iii. Commercial system owned by an individual or single company; iv. The use of a crystalline-based (monocrystalline/polycrystalline) or amorphous PV system only. Sustainability 2021, 13, x FOR PEER REVIEW 8 of 22

Sustainability 2021, 13, x FOR PEER REVIEW 8 of 22

Selected Case Studies SelectedEconomic Case Studies fluctuation analysis was normalized with a basis of comparison for pur- posesEconomic between fluctuation country economies, analysis was which normalized have variety with of a market basis of value. comparison In the assessment for pur- posesof variation between of country the systems economies, and product which market have variety value during of market the value.selected In timeline, the assessment the case study systems were expected to fulfil all the listed criteria below: Sustainability 2021, 13, 396 of variation of the systems and product market value during the selected timeline, the8 case of 21 studyi. systemsA two-year were matured expected system; to fulfil all the listed criteria below: i. ii. ALocation two-year in matured Asian countries system; with a tropical climate; ii.iii. LocationCommercial in Asian system countries owned with by an a tropical individual climate; or single company; The criteria listed above are applied to typical systems implemented in numerous coun- iii.iv. CommercialThe use of systema crystalline-based owned by an (monocrystalline/polycrystalline) individual or single company; or amorphous PV tries due to their long-established results and trust by consumers. Two other economies, system only. iv. namely,The use Thailandof a crystalline-based and Indonesia, (monocrystalline/polycrystalline) were selected within the APEC region or amorphous for comparison PV withsystemThe Malaysia. criteria only. listed These above countries are wereapplied selected to typical not only systems because implemented of their tropical in numerous climate, countriesbutThe alsocriteria due because to listed their of abovelong-established their closely are applied related resu to energy ltstypical and resources, trustsystems by consumers. whichimplemented drive Two the in policiesother numerous econo- in a countriesmies,similar namely, due direction. to Thailand their Thelong-established and introduction Indonesia, of resu were PVlts in selected theseand trust neighbouring within by consumers. the APEC countries Tworegion is other also for growing compar-economies,isonat namely,with a constant Malaysia. Thailand rate andThese and comparable Indonesia,countries to werewere that selected of Malaysia. withinnot only Figures the because APEC6–8 show regionof their the for energy tropical compar- mix cli- isonmate, forwith but Malaysia, Malaysia. also because Indonesia, These of countriesthei andr Thailand.closely were related Theselected energy energy not mix resources,only of thebecause country which of istheir drive a key tropical the factor policies thatcli- mate,in aaffects similar but also the direction. typebecause of energy Theof thei introduction consumedr closely related during of PV in anenergy these entire resources,neighbouring system life which cycle. countries drive theis also policies grow- ining a similar at aThe constant direction. case studies rate The and chosen introduction comparable are as shown of toPV that in Tablethese of Malaysia.2 neighbouring. Case 1 isFigures located countries 6–8 in Malaysia show is also the with grow-energy an annual average radiation of 1571 kWh/m2/year. The standalone PV system was installed ingmix at fora constant Malaysia, rate Indonesia, and comparable and Thailand. to that The of Malaysia.energy mix Figures of the 6–8country show is thea key energy factor on the roof of a single-story house in 2015. The system consists of 12 polycrystalline panels mixthat for affects Malaysia, the type Indonesia, of energy and consumed Thailand. during The energy an entire mix system of the countrylife cycle. is a key factor which cover an effective area of 19.22 m2. The power capacity of Case 1 is 3.0 kWp and the that affects the type of energy consumed during an entire system life cycle. PV system was installed by the owner to support renewable energy development. Malaysia Primary Energy Mix Malaysia Primary Energy Mix 19.30% Natural Gas Natural Gas 19.30% Crude Oil, Petroleum Products and Others 32.40% 4.00% Crude Oil, Petroleum Products and Others Coal & Coke 32.40% 4.00%0.40% Coal & Coke Hydropower 0.40%0.20% 0.20% Hydropower 0.10% Biodiesel Biodiesel 0.10% Biomass 43.60% Biomass Solar 43.60% Solar FigureFigure 6. Malaysia 6. Malaysia primary primary energy energy mix. mix. Source: Source: [27,28]. [27,28]. Figure 6. Malaysia primary energy mix. Source: [27,28]. Indonesia Primary Energy Mix Indonesia Primary Energy Mix 37.00% 37.00% 6.40% 6.40% Coal Natural Gas Coal Natural Gas 4.70% Oil Hydropower 4.70% Oil Hydropower Geothermal 21.80% Geothermal 21.80% 33.00% 33.00%

Figure 7. Indonesia primary energy mix. Source: [27,28].

Figure 7. Indonesia primary energy mix. Source: [27,28]. Figure 7. Indonesia primary energy mix. Source: [27,28]. SustainabilitySustainability2021 2021, 13, 13, 396, x FOR PEER REVIEW 9 of 229 of 21

Sustainability 2021, 13, x FOR PEER REVIEW 10 of 23 Thailand Primary Energy Mix

Sustainability 2021, 13, x FOR PEER REVIEW 10 of 23

5%1%7% 5% Sustainability 2021, 13, x FOR 3%PEER REVIEWthe government and is maintained regularly all year round. These are the 6 case studies10 of 23 selected for analysis using LCANatural and LCCA. Gas Lignite Coal the government and is maintained regularly all year round. These are the 6 case studies Sustainability 2021, 13, x FOR PEER REVIEW 67% 10 of 23 29% selected for analysisTable 2. Selectedusing LCA caseHard andstudies Coal LCCA. in Asia. Others the government and is maintained regularly all year round. These are the 6 case studies Sustainability 2021, 13, x FOR PEER REVIEW Bagasse Agricultural Waste Ser-10 of 23 selectedAnnual for analysisTable Average 2. Selectedusing No.LCA case of and studies PV LCCA. Panels in Asia. and Panel Effec- Power Case Locationthe government and is maintained regularly all year round. These are the 6 case vicestudies Sustainability 2021, 13, x FOR PEER REVIEW Irradiation MunicipalModel Solid Waste Biogastive Area Capacity Ser-10 of 23 selectedAnnual for analysisTable Average 2. usingSelected LCANo. case of and studies PV LCCA. Panels in Asia. and Panel Effec- Power Year Case Locationthe government and is maintained regularly all year round. These are the 6 case studiesvice Irradiation SolarModel PV Windtive AreaPower Capacity Ser- selectedAnnual for analysisTable Average 2. using Selected LCANo. case andof studies PV LCCA. Panels in Asia. and Panel Effec- Power Year Case Location50% 13% vice Malaysiathe governmentIrradiation and is maintainedHydropower12 Modelregularly unit all year round.tive Area These areCapacity the 6 case studies 1% 9% YearSer- (2′43′ N, selected1571Annual for kWh/m analysisTable Average2 2./year Selectedusing LCANo. SHARPcase of andstudies PV Poly-Si-ND-LCCA. Panels in Asia. and Panel19.22 Effec- m2 3.0Power kWp 2015 Case MalaysiaLocation 12 unit vice 101′57′ E) FigureIrradiation 8. Thailand primary energy235QCJModel mix. Source: [27,28].tive Area Capacity Ser- (2′43′ N, Annual1571 kWh/mTable Average2 /year2. Selected No.SHARP case of studies PV Poly-Si-ND- Panels in Asia. and Panel19.22 Effec- m2 3.0Power kWp Year2015 Case Location Figure 8. Thailand primary energy mix. Source: [27,28]. vice 101Malaysia′57′ E) Irradiation Model235QCJ12 unit tive Area Capacity Case 1 Ser- Table 2. Selected case studies(2′43′ inN, Asia. 1571 kWh/m2/year SHARP Poly-Si-ND- 19.22 m2 3.0 kWp Year2015 TheAnnual case Averagestudies chosen No. are of as PV shown Panels in Tableand 2. CasePanel 1 Effec-is located inPower Malaysia with Case Location101Malaysia′57′ E) 235QCJ12 unit vice Case 1 an annualAnnualIrradiation average Average radiation No. of of1571 PVModel kWh/m Panels 2/year.Panel The Effectivetive standalone Area PVPowerCapacity system wasService in- Case Location(2′43′ N, 1571 kWh/m2/year SHARP Poly-Si-ND- 19.22 m2 3.0 kWp Year2015 Thailand stalled onIrradiation the roof of a single-storyand 2808house Model unit in 2015. The systemArea consists Capacityof 12 polycrystallineYear Case 1 Malaysia101′57′ E) 12235QCJ unit panels which cover2 an effective area of 19.22 m2. The power capacity2 of Case 1 is 3.0 kWp (2(18.7′43′ ′N, N 15711672 kWh/mkWh/m2/year/year SHARPSolartron Poly-Si-ND- 4548.9819.22 m m2 3.0702 kWp kWp 20152011 Thailand and the PV system was installed by2808 the owner unit to support renewable energy development. Case 1 101MalaysiaMalaysia98.9′57′ ′ E)E) Polycrystalline12235QCJ12 unit unit SP250 0 (18.70 ′ N0 0 1672Next, kWh/m Case1571 2 2is/year located in Thailand.Solartron It is a standalone4548.98 solar mfarm2 system702 kWp which only2011 (2 43 N, 101 57 2 SHARP 19.22 m2 2 3.0 kWp 2015 Thailand(2′43′ N, 1571kWh/m kWh/m2/year/year SHARP2808 Poly-Si-ND- unit 19.22 m 3.0 kWp 2015 98.9E)′ E) generates electricity for the Poly-Si-ND-235QCJcampusPolycrystalline area and SP250does not sell its excess electricity. The power CaseCase 12 101′57′ E) 2 235QCJ 2 2 (18.7′ N capacity1672 of kWh/m the system/year is 702 kWp Solartronwith 2808 polycrystalline4548.98 panels m over702 4548.98 kWp m . The2011 Case 1 2 Thailand98.9′ E) system started operating in 2011Polycrystalline with2808 an unitannual SP250 average irradiation of 1672 kWh/m /year. CaseCase 12 (18.7′ N The standalone1672 kWh/m solar2/year farm is consideredSolartron a high-risk investment4548.98 m without2 702 any kWp generated 2011 Malaysia Thailand98.9′ E) income. Its1685.39 payback relies onlyPolycrystalline on28082808 1320its unitelectrical unitunit SP250 consumption savings over time. Case 2 Thailand 1672 2 (5.22′ N 2 2138.42 m2 200 kWp 2016 (18.70 ′ N 0 1672Case kWh/m 3 is located2 /year in Malaysia.Solartron SolartronThe 200 kWp, polycrystalline4548.984548.98 m mPV system702702 kWp iskWp mounted 20112011 on (18.7MalaysiaN 98.9 E) kWh/mkWh/m /year/year Polycrystalline 100.24Thailand98.9′ E)′ E) the large rooftop1685.39 of a factory.PolycrystallinePolycrystalline The2808 13202138.4 unitunit SP250 m SP250 2 flat rooftop area is now covered with 1320 Case 2 2 (5.22′ N photovoltaic panels2 since 2016. Annual average irradiation2138.4 reaches m 2 1685.39200 kWh/m kWp 2 /year.2016 Case 2 Malaysia(18.7′ N 1672kWh/m kWh/m2/year/year PolycrystallineSolartron 4548.98 m 702 kWp 2011 Case 3 100.2498.9′ E)′ E) Although the1685.39 system is expectedPolycrystalline to1320 generate unit SP250 good income with a short payback period, Case 2 (5.22′ N 2138.4 m2 200 kWp 2016 the factory area2 appears to interfere with the effectiveness of PV production capability kWh/m /year Polycrystalline Case 3 100.24Malaysia′ E) due to heavy dust accumulation on top of the panels. This could greatly affect the power 0 0 1685.391685.39 13201320 unit unit 2 Case 2 (5.22(5.22N 100.24′ N 2 2138.42138.4 m m2 200200 kWp kWp 20162016 Thailand generationkWh/m and 2efficiency/year of thePolycrystalline Polycrystallinepanel if it is not regularly maintained. Case 3 Malaysia100.24E) ′ E) 32 unit (18.7′ N 1672The fourth1685.39kWh/m case 2/year study is located1320 in unit Thailand and was51.84 installed m2 in 2011.2.5 kWp It is a small2011 (5.22′ N 2138.4 m2 200 kWp 2016 Case 3 2.5 kWp grid-connected2 system,Amorphous mounted Siliconon the slanted-roof structure of an event hall. Thailand98.9′ E) kWh/m /year Polycrystalline Case 3 100.24Malaysia′ E) 32 unit 2 Case 4 (18.7′ N There1672 are kWh/m1685.39only 32 2/yearamorphous PV 1320panels unit with an effective51.84 area m of2 51.842.5 m kWp. The annual2011 (5.22′ N Amorphous2 Silicon 2138.4 m2 200 kWp 2016 Thailand98.9′ E) averagekWh/m irradiation2/year is 1672 kWh/mPolycrystalline/year, which is expected to be enough in supporting Thailand 1672 32 unit32 unit 2 Case 3 100.24(18.70 ′′ NE)0 the small,1672 kWh/mrarely used2/year event hall. The excess production51.84 of51.84 m electric m2 ity 2.5on2.5 kWpa non-event kWp 2011 day2011 Case 4 (18.7 N 98.9 E) kWh/m2/year Amorphous Silicon Thailand can be sold to the grid for income.Amorphous Silicon 98.9′ E) 32 unit CaseCase 34 (18.7′ N 1672Next, kWh/m Case 5 is2/year an 8.0 MWp solar farm system located51.84 in Malaysia m2 and2.5 kWpbuilt in 2014.2011 Case 4 Malaysia Amorphous29,092 unit Silicon Thailand98.9′ E) The system installation includes 29,092 highly efficient monocrystalline PV panels on va- 2 32 unit 2 (2.3 N, 102.3cant 1571land. kWh/m The 47,1292 /year m 2 piece Yingliof land PANDA was bought and 47,129managed m2 by a8.0 company, MWp which2014 Case 4 (18.7′ N 1672 kWh/m /year 51.84 m 2.5 kWp 2011 Malaysia Amorphous29,09229,092 unit unit Silicon 2 Thailand98.9MalaysiaE)′ E) adds to the investment1571 cost. TheMonocrystalline annual average irradiation is 1571 kWh/m /year and the (2.3 N, 102.3 1571 kWh/m2/year YingliYingli32 PANDA PANDAunit 47,12947,129 m2 m2 8.08.0 MWp MWp 20142014 (2.3 N, 102.3 E)installationkWh/m is expected2/year2 to produce high power generation yields. 2The PV system is main- Case 4 Malaysia(18.7′ N 1672 kWh/m /year Monocrystalline29,092 unit 51.84 m 2.5 kWp 2011 Case 5 E) tained and cleaned regularly AmorphoustoMonocrystalline preserve its Silicon efficiency throughout the years. (2.398.9 N,′ 102.3E) 1571 kWh/m2/year Yingli PANDA 47,129 m2 8.0 MWp 2014 Case 5 Finally, Case 6 is located in Indonesia. The 2.0 MWp PV system started operation in Case 4 Case 5 MalaysiaE) 2014. It has 8568 monocrystallineMonocrystalline panels29,092 installedunit on 13,880.16 m2 of land. The annual av- 2 2 (2.3 N, 102.3 1571 kWh/m /year Yingli2 PANDA 47,129 m 8.0 MWp 2014 Indonesiaerage irradiation is 1888 kWh/m8568/year8568 unit and unit it is expected to boost power output by using Case 5 MalaysiaIndonesiaE) a transformer18881888 to maximized electricityMonocrystallineAdyasolar29,092 generation.unit The PV system is owned partially by (1.3 N, 116.3 Adyasolar SP240-24M 13,880.1613,880.16 m2 m2 2.02.0 MWp MWp 2014 2014 (1.3(2.3 N,N, 116.3 102.3 E) 1571kWh/m2/year kWh/m2/year YingliSP240-24M PANDA 47,129 m2 8.0 MWp 2014 Indonesia kWh/m2/year 8568 unit MalaysiaE)E) 1888 MonocrystallineMonocrystallineMonocrystalline29,092 unit Case 5 2 Case 6 (1.3 N, 116.3 2 Adyasolar SP240-24M 13,880.16 m2 2.0 MWp 2014 (2.3Indonesia N, 102.3 1571kWh/m2/year kWh/m /year Yingli8568 PANDA unit 47,129 m 8.0 MWp 2014 Case 6 E) 1888 Monocrystalline Case 5 (1.3 N,E) 116.3 AdyasolarMonocrystalline SP240-24M 13,880.16 m2 2.0 MWp 2014 kWh/m2/year IndonesiaE) Monocrystalline8568 unit CaseCase 56 3. Results and1888 Discussion (1.3 N, 116.3 Adyasolar SP240-24M 13,880.16 m2 2.0 MWp 2014 Indonesia3.1. EnvironmentalkWh/m2/year Impact 8568 unit Case 6 E) 3. Results and1888 Discussion Monocrystalline (1.3 N, 116.3 Adyasolar SP240-24M 13,880.16 m2 2.0 MWp 2014 kWh/m2/year IndonesiaE) 3.1. Environmental Impact Monocrystalline8568 unit Case 6 3. Results and1888 Discussion (1.3 N, 116.3 Adyasolar SP240-24M 13,880.16 m2 2.0 MWp 2014 3.1. EnvironmentalkWh/m2/year Impact Case 6 E) 3. Results and Discussion Monocrystalline

3.1. Environmental Impact Case 6 3. Results and Discussion 3.1. Environmental Impact 3. Results and Discussion 3.1. Environmental Impact Sustainability 2021, 13, 396 10 of 21

Next, Case 2 is located in Thailand. It is a standalone solar farm system which only generates electricity for the campus area and does not sell its excess electricity. The power capacity of the system is 702 kWp with 2808 polycrystalline panels over 4548.98 m2. The system started operating in 2011 with an annual average irradiation of 1672 kWh/m2/year. The standalone solar farm is considered a high-risk investment without any generated income. Its payback relies only on its electrical consumption savings over time. Case 3 is located in Malaysia. The 200 kWp, polycrystalline PV system is mounted on the large rooftop of a factory. The 2138.4 m2 flat rooftop area is now covered with 1320 photovoltaic panels since 2016. Annual average irradiation reaches 1685.39 kWh/m2 /year. Although the system is expected to generate good income with a short payback period, the factory area appears to interfere with the effectiveness of PV production capability due to heavy dust accumulation on top of the panels. This could greatly affect the power generation and efficiency of the panel if it is not regularly maintained. The fourth case study is located in Thailand and was installed in 2011. It is a small 2.5 kWp grid-connected system, mounted on the slanted-roof structure of an event hall. There are only 32 amorphous PV panels with an effective area of 51.84 m2. The annual average irradiation is 1672 kWh/m2/year, which is expected to be enough in supporting the small, rarely used event hall. The excess production of electricity on a non-event day can be sold to the grid for income. Next, Case 5 is an 8.0 MWp solar farm system located in Malaysia and built in 2014. The system installation includes 29,092 highly efﬁcient monocrystalline PV panels on vacant land. The 47,129 m2 piece of land was bought and managed by a company, which adds to the investment cost. The annual average irradiation is 1571 kWh/m2/year and the installation is expected to produce high power generation yields. The PV system is maintained and cleaned regularly to preserve its efﬁciency throughout the years. Finally, Case 6 is located in Indonesia. The 2.0 MWp PV system started operation in 2014. It has 8568 monocrystalline panels installed on 13,880.16 m2 of land. The annual average irradiation is 1888 kWh/m2/year and it is expected to boost power output by using a transformer to maximized electricity generation. The PV system is owned partially by the government and is maintained regularly all year round. These are the 6 case studies selected for analysis using LCA and LCCA.

3. Results and Discussion 3.1. Environmental Impact All graphs showed a similar pattern in which PV manufacturing dominates the total cumulative energy demand (CED) of any type of system. Normalized CED is the energy consumption based on installed system capacity and percentage of the mix; the difference is projected in Figure9. The country energy mix is highly affected by energy consumption with respect to fossil fuels. Large-scale standalone solar farms typically require a massive BOS, but the case study included two systems that are not grid-connected only support a certain designated area, and whose energy is not for sale. Thus, the energy consumption is second to that of PV manufacturing in solar-farm case studies. This case is different from the small-scale standalone system in Case 1, where the decommissioning and disposal phase is greater than the BOS. The difference may be due to the need for disposal management that dominate in small systems. A typical solar system CED is mostly from the manufacturing PV phase (Cradle) (Figure9). According to the CED analytical results, PV manufacturing dominated the energy demand in all the case studies in the three countries surveyed. Energy input from country- grid electricity mix is an important factor that affects the CED of a PV system. All system CEDs derive mainly from PV manufacturing and emit high GHG emissions, especially for large-scale systems. However, the large-scale generation quickly covers the CED coupled with the use of amorphous technology PV, which accounts for the lowest manufacturing CED. According to Kourkoumpas et al., (2018) manufacturing of PV, speciﬁcally the ingot growing method, consumes the most energy, about 45% of the total primary energy [29]. Sustainability 2021, 13, 396 11 of 21

The embodied energy of materials is highly correlated with the production of technology Sustainability 2021, 13, x FOR PEER REVIEWand components. The embodied energy content in a multi-crystalline silicon PV11 panelof 22 ranges between 1095–4312 kWh/m2 and accounts for 85% of the PV module [30]. The value can be reduced depending on the clean energy mix of a country such as in Norway [31].

Normalized CED of Case Studies 160.00 3.00

140.00 )

2.50 2 120.00 Thousands 2.00 100.00

80.00 1.50

60.00 1.00 40.00

0.50 (MWh/m Normalized CED 20.00 Cumulative Energy Demand (MWh)Demand Energy Cumulative - - Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Total 35.39 10,751.88 2,865.98 29.97 133,419.2 32,802.95 CED Norm 1.84 2.36 1.34 0.58 2.83 2.36

FigureFigure 9. 9. NormalizedNormalized cumulative cumulative energy energy demand demand (CED) (CED) of of case case studies. studies.

AccordingThe embodied to the energy CED analytical and carbon results, coefficients PV manufacturing (Table3) determine dominated the embeddedthe energy demandenergy andin all embedded the case studies carbon in of the each three material countries in asurveyed. solar PV Energy BOS. Mason input etfrom al. observedcountry- grida 71% electricity reduction mix in is lifean important cycle energy factor BOS that requirements affects the CED by usingof a PV an system. advanced All system system CEDsdesign, derive which mainly implies from the PV potential manufacturing for near-zero and emit life high cycle GHG GHG emissions, emissions especially with future for large-scaledevelopment systems. [32]. However, Based on the industrial large-scal fuele generation mix, multi-crystalline quickly covers silicon the CED (m-Si) coupled panel withuses the 4750 use MJ/m of amorphous2 in the manufacturing technology PV, process, which accounts which is for slightly the lowest higher manufacturing than that of 2 CED.polycrystalline According siliconto Kourkoumpas (p-Si) panel et (4070al., (2018) MJ/m manufacturing). This situation of PV, leads specifically to a greater the ingot GHG 2 growingemission method, impact ofconsumes 0.242 tCO the2/m most. energy, about 45% of the total primary energy [29]. The embodied energy of materials is highly correlated with the production of technology Table 3. Material embedded energyand and components. carbon coefficient The embodied (Ice v2). energy content in a multi-crystalline silicon PV panel 2 rangesEmbedded between 1095–4312 Energy and kWh/m Carbon and Coefficient accounts for 85% of the PV module Comments [30]. The value can be reduced depending on the clean energy mix of a country such as in Norway [31]. Materials EE EC EE: Embedded Energy The embodied energyEC (kgCO and carbon2/kg) coefficients (Table 3) determine the embedded en- (MJ/kg) (kgCO2e/kg) EC: Embedded Carbon ergy and embedded carbon of each material in a solar PV BOS. Mason et al. observed a Aggregate 71% 0.083reduction in life cycle energy 0.0048 BOS requirements 0.0052 by using Industrial an advanced fuel consumptionssystem design, (general) Aluminium which implies the potential for near-zero life cycle GHG emissions with future develop- 155 8.24 9.16 Assumed ratio (general) ment [32]. Based on industrial fuel mix, multi-crystalline silicon (m-Si) panel uses 4750 MJ/m2 in the manufacturing process, which is slightly higherIncludes than that CO ofemission polycrystalline from Primary Glass 15.00 0.86 0.91 2 silicon (p-Si) panel (4070 MJ/m2). This situation leads to a greaterprimary GHG manufacturing emission impact Siliconof 0.242 2355 tCO2/m2. - - Lithium 853 5.30 - Water 0.01 0.001 - Plastic 80.50 2.73 3.31 Includes feedstock energy (EU) Wire 36.00 2.83 3.02 2 2 MJ/m kgCO2/m Monocrystalline PV 4750 242 Industrial fuel mix Polycrystalline PV 4070 208 Sustainability 2021, 13, x FOR PEER REVIEW 12 of 22

Table 3. Material embedded energy and carbon coefficient (Ice v2).

Embedded Energy and Carbon Coeffi- Comments cient Materials EE EC EE: Embedded Energy EC (kgCO2/kg) (MJ/kg) (kgCO2e/kg) EC: Embedded Carbon Aggregate 0.083 0.0048 0.0052 Industrial fuel consumptions (general) Aluminium 155 8.24 9.16 Assumed ratio (general) Includes CO2 emission from primary manufac- Primary Glass 15.00 0.86 0.91 turing Silicon 2355 - - Lithium 853 5.30 - Water 0.01 0.001 - Plastic 80.50 2.73 3.31 Includes feedstock energy (EU) Wire 36.00 2.83 3.02

MJ/m2 kgCO2/m2 Monocrystalline 4750 242 SustainabilityPV 2021, 13, 396 Industrial fuel mix 12 of 21 Polycrystalline PV 4070 208

EnergyEnergy consumption consumption from from PV PV manufacturin manufacturingg is approximately is approximately 60%–70% 60–70% of of the en- entire tirelife life cycle cycle in in all all types types of PVof PV systems. systems. This This energy energy consumption consumption factor factor could could lead to lead advance- to advancementsments in manufacturing in manufacturing methods methods and technologicaland technological development. development. Various Various types types of PV of PVpanels panels involve involve different different production production methods methods and and energy energy consumption consumption rates. rates. FigureFigure 10 10 shows that the CED of monocrystalline PVPV productionproduction isis thethe highest,highest, andand that that of of polycrys- poly- crystallinetalline PV PV and and amorphous amorphous silicon silicon is is the the lowest.lowest. ThisThis indicatesindicates thatthat the type of PV used in in thethe system contributescontributes greatlygreatly to to the the energy energy impact impact factor. factor. According According to Ludinto Ludin et al. et (2018), al. (2018),the CEDthe CED of thin-film of thin-film PV is PV lower is lower in terms in terms of energy of energy payback payback time PBT)time inPBT) comparison in compar- with isonthat with of monocrystallinethat of monocrystalline (m-Si) and(m-Si) polycrystalline and polycrystalline (p-Si), with(p-Si), its with consumption its consumption balanced balancedto its production to its production efficiency efficiency [33]. However,[33]. However, in terms in terms of PV of performance,PV performance, p-Si p-Si was was more moreefficient efficient in solarin solar conversion conversion independent independen of thet of location. the location. Annual Annual conversion conversion efficiency effi- for ciencym-Si for and m-Si p-Si and was p-Si around was around 12.8%, whereas12.8%, whereas that for that a-Si for reached a-Si reached 8% [34]. 8% [34].

PV Manufacturing CED and GHG emission 80.00 30,000.00 70.00 25,000.00 60.00

Thousands 20,000.00 50.00 40.00 15,000.00 30.00 10,000.00 20.00 5,000.00 10.00

Cumulative Energy Demand (MWh)Demand Energy Cumulative - - Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 CED 23.64 5,377.86 2,528.05 19.18 67,859.0 19,985.4

GHG emission 8.69 3,053.60 693.95 8.34 26,142.8 6,987.23 eq) (tCO2 Emission Gases Greenhouse

Figure 10. CED of different types of solar panel manufacturing and greenhouse gas (GHG) emission by case study. Figure 10. CED of different types of solar panel manufacturing and greenhouse gas (GHG) emission by case study. According to the CED of all case studies, the EPBT showed different patterns (Figure 11). Case 4 had the fastest EPBT of 0.7 years because the system consumed a small amount of energy, particularly from amorphous silicon manufacturing. Solar PV systems using thin-film panels are preferable due to their low EPBT periods, in addition to their low GHG emissions. GHG emissions (or GWP) is approximately 9.4–104 g CO2-eq/kWh for polycrystalline PV systems, 44–280 g CO2-eq/kWh for monocrystalline PV systems, and 15.6–50 g CO2-eq/kWh for amorphous PV systems [35]. Energy PB is greatly influenced by various components used and activities during the life cycle phases, which include a 25-year lifetime. High energy PB years by Ecoinvent included the production of the relevant components, but even just including PV panel production results in a high global warming potential [36]. EPBT calculations are heavily influenced by the amount of sunlight received by a PV system. The more sunlight received, the more kWh the PV system will produce, and the faster the PV system will offset the energy it consumed to manufacture it. A 2006 study reported the EPBT of one to two years based on an average of 4.7 peak sun-hours received in southern Europe. If you live in a sunny climate, then the EPBT will be low. The current overall worldwide average EPBT is one to three years (rather than one to two years for southern Europe) and accounts for cloudy locations across the globe [37]. Sustainability 2021, 13, x FOR PEER REVIEW 13 of 22

According to the CED of all case studies, the EPBT showed different patterns (Figure 11). Case 4 had the fastest EPBT of 0.7 years because the system consumed a small amount of energy, particularly from amorphous silicon manufacturing. Solar PV systems using thin-film panels are preferable due to their low EPBT periods, in addition to their low GHG emissions. GHG emissions (or GWP) is approximately 9.4–104 g CO2-eq/kWh for polycrystalline PV systems, 44–280 g CO2-eq/kWh for monocrystalline PV systems, and 15.6–50 g CO2-eq/kWh for amorphous PV systems [35]. Energy PB is greatly influenced by various components used and activities during the life cycle phases, which include a 25-year lifetime. High energy PB years by Ecoinvent included the production of the relevant components, but even just including PV panel production results in a high global warming potential [36]. EPBT calculations are heavily influenced by the amount of sunlight received by a PV system. The more sunlight received, the more kWh the PV system will produce, and the faster the PV system will offset the energy it consumed to manufacture it. A 2006 study reported the EPBT of one to two years based on an average of 4.7 peak sun-hours received in southern Europe. If you live in a sunny climate, then the EPBT Sustainability 2021, 13, 396 will be low. The current overall worldwide average EPBT is one to three years (rather13 than of 21 one to two years for southern Europe) and accounts for cloudy locations across the globe [37].

Figure 11. Energy paybackpayback timetime (EPBT) (EPBT) of of PV PV systems systems varies varies based based on on maintenance maintenance energy energy investment. investment. Case 1 had the highest EPBT of 3.6 years, due to the large CED allocation in the batteryCase energy 1 had storage the highest system EPBT which of entails3.6 years, a significant due to the cost large compared CED allocation to a grid-connected in the bat- terysystem energy [38]. storage Solar-farm system Cases which 5 and entails 6 had a sign the sameificant EPBT cost compared range, which to a isgrid-connected 2.6–2.7 years, systemdue to energy[38]. Solar-farm production. Cases Although 5 and 6 both had solarthe same farms EPBT achieved range, a highwhich CED, is 2.6–2.7 their energy years, dueproduction to energy was production. sufficient toAlthough compensate both the sola consumedr farms achieved energy. Casea high 2, CED, which their resulted energy in productionthe longest was EPBT sufficient of two years, to compensate showed that the aconsumed large-scale energy. standalone Case 2, solar which farm resulted required in thea large longest CED EPBT in construction of two years, and showed PV manufacturing. that a large-scale However, standalone its energy solar farm generation required was a largeinsufficient CED in to construction cover its CED and over PV amanufacturing. short time period. However, This valueits energy was alsogeneration affected was by insufficientits elevated to energy cover consumptionits CED over a for short operation time period. and maintenance. This value was The also system affected maturity by its elevatedalso played energy a role, consumption as indicated for by variousoperation improvement and maintenance. gap indicators, The system such maturity as efficiency also playedincrement a role, and as conversion indicated by [39 various]. Case improvement 3 exhibited a gap remarkable indicators, EPBT such of as 3.2 efficiency years for in- a crementcommonly and used conversion polycrystalline [39]. Case technology, 3 exhibited compared a remarkable with the EPBT CED of of3.2 12.61 years MJ/Wp for a com- and monlyan EPBT used of 2.2–6.1polycrystalline years for technology, multi-crystalline compared installation with the in China.CED of 12.61 MJ/Wp and an EPBTThe of 2.2–6.1 GHG emissionyears for bymulti-crystalline the PV system installation capacity (Figure in China. 12) showed that the ratio of GHGThe emitted GHG overemission the PV by systemthe PV capacitysystem capacity normalized (Figure the 12) comparison showed that because the ratio the PV of GHGsystems emitted because over they the varyPV system in size capacity and total normalized energy consumption. the comparison For abecause typical the silicon PV systemssolar PV because technology, they vary the GHG in size emission and total rate energy ranges consumption. between 29–671 For a typical g CO2 eq/kWhsilicon solar for PVm-Si. technology, Meanwhile, the the GHG p-Si rangeemission is around rate ranges 12.1–569.0 between g CO 29–6712eq/kWh g CO [332].eq/kWh The ratio for for m-Si. the Meanwhile,entire system the consistently p-Si range rangedis around within 12.1–569.0 2.8–4.2. g MagrassiCO2eq/kWh et al. [33]. (2020) The reported,ratio for the 100 entire kWp systemm-Si PV consistently plant emits ranged 43 g CO within2eq/kWh 2.8–4.2. compared Magrassi to Caseet al. 3,(2020) 200kWp reported, p-Si PV 100 plant kWp emits m-Si 569 g CO2eq/kWh. The large difference in value could be due to manufacturing of PV and installation phase of the system [40]. A larger ratio means that a greater amount of GHG is emitted for a certain system capacity. For Case 2, the ratio was extremely high despite the comparably lower GHG emission compared with that of other large-scale solar farms. This result means that the system produces a large amount of GHG emissions over a small-scale system, either due to local PV manufacturing process or power peak of the PV panel itself. Figure 13 shows the annual avoided GHG emissions by case study. The larger the system capacity installed, the greater the annual electricity generated, which replaces the regional electricity mix generated for the grid. This result supports the argument that a large-scale solar farm with high energy production is more viable than other small PV systems due to its carbon payback capability. A small-scale solar system is also viable over a long period, but its carbon emissions per 1 kWh production is extremely low [41]. Thus, carbon payback requires a long time. Moreover, GHG emissions over 1 MJ of energy consumption by each life-cycle phase shows that the manufacturing and disposal stages of the PV systems emit the highest amount of carbon emissions. The reasons are that both local manufacturing (particularly that of amorphous silicon) and the effect of the electricity grid mix has an increased value of GHG. The GHG emitted by monocrystalline PV manufacture is relatively high over 1 MJ of energy consumed, compared with that of polycrystalline PV [42]. Sustainability 2021, 13, x FOR PEER REVIEW 14 of 22

PV plant emits 43 g CO2eq/kWh compared to Case 3, 200kWp p-Si PV plant emits 569 g CO2eq/kWh. The large difference in value could be due to manufacturing of PV and installation phase of the system [40]. A larger ratio means that a greater amount of GHG is emitted for a certain system capacity. For Case 2, the ratio was extremely high despite the comparably lower GHG emission compared with that of other large-scale solar farms. This result means that the system produces a large amount of GHG emissions over a Sustainability 2021, 13, 396 14 of 21 small-scale system, either due to local PV manufacturing process or power peak of the PV panel itself.

GHG Emission over PV System Capacity 30,000.00 5.00 4.50 25,000.00 4.00 3.50 20,000.00 3.00 15,000.00 2.50 2.00 10,000.00 1.50 1.00 5,000.00 Total GHG Total Emission (tCO2 eq) 0.50 Ratio GHG/PV System Capacity - - Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Total GHG Emission 8.69 3,053.60 693.95 8.34 26,142.80 6,987.23 GHG by PV System Capacity 2.90 4.35 3.47 3.34 3.27 3.49 Sustainability 2021, 13, x FOR PEER REVIEW 15 of 22

Figure 12. GHG emission normalized by PV system capacity. Figure 12. GHG emission normalized by PV system capacity.

Figure Annual13 shows Avoided the annual GHG avoided Emission GHG emissions by case study. The larger the system capacity installed, the greater the annual electricity generated, which replaces the regional 6,000.00 electricity mix generated for the grid. This result supports 4,000.00 the argument that a large-scale solar farm with high energy production is more viable 3,500.00 than other small PV systems 5,000.00 due to its carbon payback capability. A small-scale solar system is also viable over 3,000.00 a long period, but its carbon emissions per 1 kWh production is extremely low [41]. Thus, 4,000.00 carbon payback requires a long time. Moreover, GHG emissions 2,500.00 over 1 MJ of energy consumption 3,000.00 by each life-cycle phase shows that the manufacturing 2,000.00 and disposal stages of the PV systems emit the highest amount of carbon emissions. The reasons are that both 1,500.00 local 2,000.00 manufacturing (particularly that of amorphous silicon) and the effect of the electricity grid mix has an increased value of GHG. The GHG emitted 1,000.00 by monocrystalline PV 1,000.00 manufacture is relatively high over 1 MJ of energy consumed, compared 500.00 with that of polycrystalline PV [42]. Annual Avoided Emission (tCO2 eq) Annual Electricity Generated (MWh) Generated Annual Electricity - - Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Annual Electricity Generated 3.35 702.00 478.59 2.58 4,846.00 2,970.72 Annual Avoided Emission 2.48 343.98 354.16 1.26 3,586.04 1,069.46

Figure 13. Case Studies annual avoided GHG emission. Figure 13. Case Studies annual avoided GHG emission.

3.2.3.2. Economic Economic Impact Impact EconomicEconomic impact impact studies studies have have been been conducte conductedd on onvarious various products products as a as platform a platform for evaluatingfor evaluating value-to-money value-to-money along along the entire the entire value value chain chain [43]. [ 43The]. TheLCC LCC and andLCOE LCOE for all for caseall case studies studies is calculated is calculated based based on different on different discount discount rates (2%, rates 4%, (2%, and 4%, 6%). and From 6%). Figure From 14,Figure the LCC 14, the value LCC decreased value decreased as the discount as the discountrate increased. rate increased. All the case All studies the case followed studies thisfollowed trend, thisexcept trend, for exceptCase 3 forwhose Case LCC 3 whose value LCCincreased value as increased the discount as the rate discount increased. rate Thisincreased. anomaly This is anomalydue to the is duetotal to cost the of total operational, cost of operational, maintenance, maintenance, and repair and cost repair (COMR cost), replacement(COMR), replacement cost (Crep cost) and (C represidual) and residual value (C valueres) at (C 2%res )( at−USD 2% ( −22,952.14),USD 22,952.14), which whichare sub- are stantiallysubstantially less than less thanthose those at 4% at and 4% 6%, and −USD 6%, − 4437.34USD 4437.34 and USD and 4673.74 USD 4673.74 respectively. respectively. Thus, atThus, a 2% atdiscount a 2% discount rate, the rate,inflow the of inﬂowcash (C ofres value) cash (C isres greatervalue) than is greater at 4% and than 6% at discount 4% and rates.6% discount rates.

(a) LCC and LCOE of Case 1 and (b) LCC and LCOE of Case 2, 3, 5 and 6 2 with Discounted Rate with Discounted Rate

30,000.00 0.12 25,000.00 0.35

0.3 25,000.00 0.1 20,000.00 Thousands 0.25 20,000.00 0.08 15,000.00 0.2 15,000.00 0.06

0.15 LCC ($) LCC ($) 10,000.00

10,000.00 0.04 ($/kWh) LCOE 0.1 ($/kWh) LCOE 5,000.00 0.05 5,000.00 0.02

0.00 0 0.00 0 Case 1 Case 4 Case 2 Case 3 Case 5 Case 6

LCC (2%) LCC (4%) LCC (6%) LCC (2%) LCC (4%) LCC (6%) LCOE (2%) LCOE (4%) LCOE (6%) LCOE (2%) LCOE (4%) LCOE (6%)

Figure 14. (a) Life cycle cost (LCC) and levelised cost of energy (LCOE) of case 1 and 4. (b) LCC and LCOE of case 2, 3, 5, and 6 based on different discount rates of 2%, 4%, and 6%. Sustainability 2021, 13, x FOR PEER REVIEW 15 of 22

Annual Avoided GHG Emission 6,000.00 4,000.00 3,500.00 5,000.00 3,000.00 4,000.00 2,500.00 3,000.00 2,000.00 1,500.00 2,000.00 1,000.00 1,000.00 500.00 Annual Avoided Emission (tCO2 eq) Annual Electricity Generated (MWh) Generated Annual Electricity - - Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Annual Electricity Generated 3.35 702.00 478.59 2.58 4,846.00 2,970.72 Annual Avoided Emission 2.48 343.98 354.16 1.26 3,586.04 1,069.46

Figure 13. Case Studies annual avoided GHG emission.

3.2. Economic Impact Economic impact studies have been conducted on various products as a platform for evaluating value-to-money along the entire value chain [43]. The LCC and LCOE for all case studies is calculated based on different discount rates (2%, 4%, and 6%). From Figure 14, the LCC value decreased as the discount rate increased. All the case studies followed this trend, except for Case 3 whose LCC value increased as the discount rate increased. This anomaly is due to the total cost of operational, maintenance, and repair cost (COMR), replacement cost (Crep) and residual value (Cres) at 2% (−USD 22,952.14), which are substantially less than those at 4% and 6%, −USD 4437.34 and USD 4673.74 respectively. Thus, Sustainability 2021, 13, 396 15 of 21 at a 2% discount rate, the inflow of cash (Cres value) is greater than at 4% and 6% discount rates.

(a) LCC and LCOE of Case 1 and (b) LCC and LCOE of Case 2, 3, 5 and 6 2 with Discounted Rate with Discounted Rate

30,000.00 0.12 25,000.00 0.35

0.3 25,000.00 0.1 20,000.00 Thousands 0.25 20,000.00 0.08 15,000.00 0.2 15,000.00 0.06

0.15 LCC ($) LCC ($) 10,000.00

10,000.00 0.04 ($/kWh) LCOE 0.1 ($/kWh) LCOE 5,000.00 0.05 5,000.00 0.02

0.00 0 0.00 0 Case 1 Case 4 Case 2 Case 3 Case 5 Case 6

LCC (2%) LCC (4%) LCC (6%) LCC (2%) LCC (4%) LCC (6%) LCOE (2%) LCOE (4%) LCOE (6%) LCOE (2%) LCOE (4%) LCOE (6%)

Figure 14.Figure(a) Life 14. cycle (a) Life cost cycle (LCC) cost and (LCC) levelised and levelised cost of energy cost of (LCOE) energy of(LCOE) case 1 of and case 4. (1b and) LCC 4. and(b) LCC LCOE of case 2, 3, 5, and 6 basedand on LCOE different of case discount 2, 3, 5, ratesand 6 of based 2%, 4%, on different and 6%. discount rates of 2%, 4%, and 6%.

The highest LCC values at 2%, 4%, and 6% is that of Case 5, followed by those of Cases 2, 3, and 6. Solar farms cost the most because they are primarily built-in large scale, thus requiring the purchase of land, cost for land clearing and management, building of facilities, road access, and other factors. For example, in Case 5, these costs consumed about 20% (USD 4,200,000.00) of the initial investment. As expected, large-scale PV systems need enormous quantities of PV modules, inverters, support structures, and electrical systems. These costs consumed USD 15,750,000.00, which is 75% of the initial investment cost. The same condition applies to Case 6 where PV modules and other BOS systems cost the most. On the other hand, the lowest LCC value was that of Case 4, followed by Case 1. This was due to the small amount of equipment for the Case 4 system compared with Case 3. The system for Case 4 consisted of 32 units of PV modules, an inverter and a charge controller. Meanwhile, the Case 3 system consisted of 1320 units of PV modules, eight inverters, and large BOS systems, which cost a considerable amount. Case 4 did not use batteries, although the quantity of PV modules (the most expensive component) was considerably greater than that of stand-alone case studies. Batteries contributed substantially to the LCC value because they need to be replaced every three-years given their lifetime. Discount rates play an important role in the calculation of LCC and a similar role in LCOE. The smallest discount rate will contribute lower results in LCC and LCOE together [44]. Thus, a low discount rate improves the reduction of the overall cost of the PV system, reducing the cost of producing one unit of energy [45]. The LCOE for all case studies in Table4 showed a comparatively higher value than the other categories of PV systems, that is, Case 1. The LCOE for Case 1 recorded values of 0.2881, 0.2475, and 0.2173 USD/kWh discount rate of 2%, 4%, and 6% respectively. A stand-alone system produces a high LCOE value because the cumulative energy generated (LEP) extremely low compared with their LCC value [46]. In this case, Case 1 produced 78,033.60 kWh throughout its lifetime, but the LCC value was extremely high (at 2%, 4% and 6%), thus resulting in a high LCOE value. However, the value is considered on the higher end among the other PV systems and comparable to the LCOE variety range of 0.06–0.12 USD/kWh of an implausible PV/T system, as summarized by Gu et al. (2018) [47]. The lowest LCOE value was observed for the rooftop PV system. Both cases showed good performance in LCOE values, especially Case 4. The rooftop PV system can achieve a low LCOE value because it can produce a large amount of LEP. For example, Case 4 can produce 243,552.50 kWh in its 25 years of operation compared with Cases 1, which produce 78,033.60 kWh, these values are notably low for their LCC. Meanwhile, Case 3 Sustainability 2021, 13, 396 16 of 21

can produce 11,640,331.37 kWh, similar to a solar farm mounted on the roof of a building. Another reason that a rooftop can achieve low LCOE is their low LCC value compared with their LEP value. Rooftops require no land, thus saving a considerable amount in property investment. This condition eventually lowered the LCC value. Unlike solar farms, purchasing land results in an extra cost which contributes to the high LCC value.

Table 4. Findings summary main analysis.

Life Cycle Cost, LCC Levelized Cost of Energy, LCOE (USD) (USD/kWh) Discount 2% 4% 6% 2% 4% 6% Rate Stand-alone PV Case 1 22,480.70 19,310.94 16,959.09 0.2881 0.2475 0.2173 Case2 725,147.86 723,662.66 721,783.24 0.0443 0.0442 0.0441 Rooftop PV Case 3 677,047.86 695,562.66 704,673.74 0.0582 0.0598 0.0605 Case 4 12,439.22 12,198.39 11,958.97 0.0511 0.0501 0.0491 Solar farm Case 5 26,184,865.32 25,509,958.23 24,889,130.50 0.111 0.1082 0.1055 Case 6 5,218,893.56 5,100,949.46 4,988,828.95 0.072 0.0703 0.0688

The fastest simple payback (SPB) was recorded in Case 6, which presented a PB of 6.26 years, followed by Case 4 with 7.96 years, Case 3 with 8.45 years, Case 5 with 9.75, and Case 2 with the slowest PB period of 13.28 years (Table5). For Case 1, PB was impossible to attain because the last year of operation, the 25th year of operation, the savings was USD 1624.55. USD 6650.00 is needed to attain SPB. As for discounted payback (DPB), according to Allouhi et al. 2020, the current market conditions in Morocco show that the economic analysis of the monocrystalline-Si/ polycrystalline-Si type system was the technology offering the longest discounted payback period with the 20-city average of 28.62 years [34]. In this study, the fastest DPB (6.76 years) was observed in Case 6 at a 2% discount rate, followed by Case 6 at 4% with DPB of 7.36 years, and Case 6 at 6% with DPB of 8.1 years. These values are comparable to the shortest DPB of 17.11 years for p-Si and 21.62 years for m-Si [34]. The slowest DPB was that of Case 2 at 6% (25.11 years). For others, their DPB averaged between 8–16 years. In standalone systems, the PB is long because their present value savings are remarkably low. Their savings reached roughly 24% of their initial investment on the 25th year of their operation. Thus, calculating DPB was impossible. The PV module cost must be lowered by 30% to make the LCOE and PB periods competitive to improve the PB of a PV system investment [22].

Table 5. Simple Payback (SPB) Period and Discounted Payback (DPB) Period.

Simple Payback, SPB Discounted Payback, DPB (Year) (Year) Discount rate - 2% 4% 6% Stand-alone PV - Case 1 ---- Case2 13.28 14.28 17.59 25.11 Rooftop PV - Case 3 8.45 9.36 10.55 12.20 Case 4 7.96 8.77 9.80 11.22 Solar farm - Case 5 9.75 10.98 12.69 15.32 Case 6 6.26 6.76 7.36 8.10 Sustainability 2021, 13, 396 17 of 21

4. Policy Intervention National policies and global collaborative actions play important roles in shaping industrial development and widening the energy security frontier based on abundant PV resources. Many studies considered newly raised economic and social issues related to the LCA of large-scale PV system installation. Cross-disciplinary interest in systematic innovations include building integrated renewable technology, smart city, and hybrid renewable technology systems [48–50]. Although renewables are progressively replacing high impact products from an environmental view point, the life cycle of PV systems shows that renewable energy still requires technological innovations to be more sustainable. Related strategies include the following: • Whole system integration for optimal spatial consumption and impact trade-off balance on a temporal basis; • Improvement of additional technology efficiency via low-energy consumption and low-toxic manufacturing; • Design an optimal evaluation method that includes environment, circular economy, and social issues for renewable energy technology. The LCA and LCCA of PV systems (standalone, solar rooftop, and solar farm PVs) have produced distinctive results from the environment and economic points of view. The three economies analysed are still heavily dependent on traditional energy. Through their comprehensive target line-ups, governments in Asian countries have adopted various policies to further develop their own renewable energy policy interventions. These actions include agreements and unregulated laws that highlight incentives and carbon taxes to manage the increase in energy demand. However, a comprehensive analysis is required to assemble fragmented policies and regulations to achieve necessary goals [51]. Stakeholders and governments in Asia are responding to the growing pressures of growing population and increased energy demand by reviewing their existing policies to further stabilize energy and secure economic growth [51]. According to the RE market development, the cost of panels should decrease with the improved technology in the quickly growing PV installation market [49]. In addition, Malaysia has increased PV installation capacity due to attractive incentives offered by the government, such as Feed-in-Tariffs (FiT) and subsidies. These policies work as a catalyst and are crucial for PV implementation growth. The cost of system management could be reduced by improving electricity governance system, increasing clean energy investment and upgrading the grid system [52]. Grid-storage systems, when the grid is used for energy storage, is not considered in this study since the type of grid connection used in the case studies region is different. Grid connected PV systems usually manage electricity through the term import (buying) and export (selling) of electricity, without considering it as storage. The grid electricity market value is specified by region/country itself with governments incentives through RE policy interventions [53]. Public awareness of RE has gradually increased, and consumers are now searching for green incentives and tax exemptions for clean resource technology investments, which have further increased RE capacity to 2080 MW by 2020 and a target of 4000 MW by 2030 by Malaysia [54]. Correspondingly, the Malaysian climate change targets are the 35% reduction of GHG intensity by 2030 from the 2005 level with the increase to 45% reduction with enhanced international support [55]. Similarly, GDP growth in Indonesia is limited due to wildfires and other natural disasters that affect the country, an estimated Rp221 trillion allotted for renovation and recovery [56]. Thus, Indonesia focuses on achieving an electrification ratio of 99.7% by 2025. With the implementation of a PV business model that encourages self-consumption, Indonesia uses net billing as a market-based compensation mechanism. This mechanism supports consumer compensation based on the actual market value of the kWh consumed or injected onto the grid [13]. The costs for small-scale solar systems are lower than for large-scale solar ones. This condition promotes an increased societal interest in the technology with low investment despite geographical conditions. Therefore, risks are low because small-scale systems do not need to compete against wholesale electricity prices, but Sustainability 2021, 13, 396 18 of 21

instead compete against the final cost of electricity facing consumers. Large-scale solar PV systems also face the challenge of grid connection, land acquisition, acquisition of relevant solar data and negotiation of long-term pricing agreements that are unsuitable for various backgrounds of consumers. Indonesia aims to reduce 26% and 29% of its GHG emission from business-as-usual (BAU) level by 2020. This target can be increased to 41% by 2020 with international support. Indonesia also plans to increase 23% and 31% of its renewable energy shares into the primary energy supply by 2025 and 2050, respectively [51]. Thailand renewables are significantly leading in bioenergy due to their abundant resources. Thailand is well-known for its abundant automobile and truck traffic, and its car ownership is expected to grow to an average of 32 cars per 1000 person [7]. Thus, Thailand needs to spur its RE consumption growth to 30% by 2036. This growth is assumed to include 20.11% renewable energy mix into the power generation share and 25.04% into transport fuel consumption [51]. Accordingly, Thailand aims to improve its green energy outlook for climate change by reducing energy intensity by 30% based on 2010 levels. The country also plans to reduce GHG emission by 20% from the 2030 BAU level and increase it to 25% with enhanced international support. Installation capacity relates to the number of PV panel produced. Based on the findings in this study, PV manufacturing contributed higher CO2 and GHG emissions in comparison to the other life cycle phases for all the PV systems. This phase also consumed the highest CED based on the country’s electricity mix. Planning of system capacity size is crucial, given that the standalone system does not generate any income from the energy produced. The savings depend on the amount of energy consumed. Therefore, before installing a standalone system, a plan must be developed to calculate a suitable capacity size of the load system (for example, a house). The load energy consumption needs to be the same as the energy produced to maximize savings. The rooftop system is more viable as there is not a need to purchase land, as with large scale solar farms. Compared with solar farms, the rooftop system has a lower cost and LCOE, which are better than that of solar farm systems. If rooftops were as large as solar farms, increased amounts of energy can be produced to yield a low LCOE. Thus, more profits are gained, and the PB period of the system is shortened.

5. Conclusions All case studies for each PV system in Malaysia, Thailand, and Indonesia were suc- cessfully conducted. According to the findings of this study, Case 4 had the fastest energy PB time of 0.14 years due to its low manufacturing energy consumption of amorphous silicon technology. The normalized CEDs for all cases were within the average range of 45 MJ/m2 to 60 MJ/m2. Comparison of different types of PV systems proves that manufacturing of products eventually dominates the CED of each system and influences the EPBT longevity overtime, in addition to those of efficiency and degradation factors on PV panel itself. Moreover, the GHG emission of PV system ratio to its total system capacity stays consistently within 2.8–4.2. The GHG emission/CO2 eq. per 1 kWh of energy produced by the PV system shows whether the system produced enough green energy to cover its non-renewable mix electricity used to produce the system. Most of the case studies, except Cases 5 and 6, emitted more CO2 compared with their production. However, whether the PV system requires considerable time to recuperate remains unclear. Meanwhile, in the LCC and LCOE analyses, the best system was the rooftop PV system. Both cases of rooftop PV systems recorded the lowest value of LCC and LCOE. The LCOE value of Case 4 was the highest with 0.0491 USD/kWh, followed by Case 3 with 0.0582 USD/kWh. Case 6 (2%) showed the best performance in supplementary financial measures. Case 6 was the best in regards to the SPB and DPB analyses. Thus, the solar farm system is more feasible in this case compared with the rooftop PV system. For the rooftop PV system to be financially viable and to take advantage of its low LCC and LCOE value, it needs to be operated at a large scale (similar to solar farms) with increased capacity to achieve high energy production. However, for solar farms to be more cost-effective and achieve low LCOE value, the use of PV modules with degradation rates below 0.20% is Sustainability 2021, 13, 396 19 of 21

highly recommended. National and regional policy interventions play important roles in supporting renewable energy growth and development in their implementation in Asia. The need to identify priorities, maintain stability and develop pathways for the renewable energy market is crucial to achieve the targets set up by various countries. • Economies should widen their renewable energy roadmap by considering other adapt- able policies and measures in the energy portfolio. • Attractive programs and incentives are an excellent catalyst to improve public awareness and attract investments. • Initializing the many energy scenarios in a decision-making platform achieves the highest potential for concerns of spatial installation and temporal market-driven trade-offs.

Author Contributions: Data curation, A.A.; investigation, N.A.A.A.; supervision, K.S.; validation, M.A.I. and S.J.; writing—original draft, N.A.L.; writing—review and editing, K.P.-R. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not Applicable. Informed Consent Statement: Not Applicable. Data Availability Statement: Data is contained within the article. Acknowledgments: The authors would like to acknowledge the support of publication works and expertise from the Economic Research Institute for ASEAN and East Asia (ERIA). Conﬂicts of Interest: The authors declare no conﬂict of interest.

Abbreviations AC Alternating Current BAU Business-as-Usual CO2 Carbon Dioxide DC Direct Current EPBT Energy Payback Time GHG Greenhouse Gas LCA Life Cycle Assessment LCI Life Cycle Inventory LCC Life Cycle Cost LEP Local Energy Production PB Payback RE Renewable Energy SPB Simple Payback m-Si Monocrystalline APEC Asia Paciﬁc Cooperation BOS Balance of System CED Cumulative Energy Demand DPB Discounted Payback FiT Feed-in-Tariff GDP Gross Domestic Product LCCA Life Cycle Cost Assessment LCOE Levelised Cost of Energy LCIA Life Cycle Impact Assessment O&M Operation and Maintenance PV Photovoltaic SDG Sustainable Development Goals a-Si Amorphous Silicon p-Si Polycrystalline Sustainability 2021, 13, 396 20 of 21

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