Abstract Due to the onset of climate change, humanity is moving towards using renewable energy technologies as our primary means of generating electricity. With the increased utilisation of renewable energy sources there is a growing need for large scale energy storage capabilities worldwide. When it comes to storing energy in the order of gigawatt-hours, Pumped Hydro Storage (PHS) has been proven to be more effective than any other energy storage method. Despite this, the implementation of new PHS projects is challenging due to the typically high capital cost, long lead times and specific nature of the sites where the technology is applicable. As an alternative to constructing new facilities, the research conducted focused on the viability of performing major upgrades to existing PHS plants as a cost-effective way of effectively increasing the storage capabilities of an electricity grid. This was done by conducting an exploratory case study into a proposed upgrade to an existing Pumped Hydro Storage facility in Queensland. In general, the study into the proposed upgrade yielded promising results both in terms of economic feasibility and environmental impact through the increased utilisation of renewable energy technologies. From this further research into developing and optimising the design proposal was recommended. Furthermore, from the positive results produced it was determined that performing major upgrades on existing PHS facilities can come with various benefits and thus is worth investigating as a cost-effective alternative to constructing new energy storage solutions.

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Dedicated to my loving grandad, Gazza.

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Table of Contents 1 Introduction ...... 1 1.1 Aim and Research Question ...... 1 1.2 Impact ...... 1 1.3 Thesis Scope ...... 1 1.4 Contents of Report ...... 1 2 Background ...... 3 2.1 Shift Towards Renewable Energy Technologies ...... 3 2.2 The Problem with Renewable Energy Sources ...... 3 2.3 Solar PV and the ‘Duck Curve’ ...... 3 2.4 Energy Storage as a Solution ...... 4 3 Pumped Hydro Storage ...... 5 3.1 Functional Overview ...... 5 3.1.1 Primary Purpose ...... 5 3.1.2 Operating Principle ...... 5 3.1.3 Phases of Operation ...... 5 3.1.4 Major Components and Configuration ...... 5 3.2 Hydraulic Machinery ...... 6 3.2.1 Turbines ...... 6 3.2.2 Pumps ...... 7 3.2.3 Dual Function Pump-Turbines ...... 7 3.3 Performance Characteristics ...... 7 3.4 Drawbacks ...... 8 3.5 Potential in Upgrading Existing Facilities ...... 8 4 Design Framework ...... 9 4.1 Flow Chart ...... 9 4.2 Steps Involved ...... 10 5 Case Study Method ...... 11 5.1 Overview ...... 11 5.2 Application ...... 11 6 Upgrade Proposal – Wivenhoe Power Station ...... 13 6.1 Selection of Existing Facility ...... 13 6.2 Step 1: Data Acquisition ...... 13 6.2.1 Facility Data ...... 13 6.2.2 QLD Electricity Grid ...... 13 6.3 Step 2: Viability of Capacity Increase ...... 14 6.4 Step 3: Design Development ...... 15 7 Evaluation ...... 16

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7.1 Overview ...... 16 7.2 Cost Analysis...... 16 7.2.1 Capital Cost ...... 16 7.2.2 Operational and Maintenance Costs ...... 18 7.3 Expected Return ...... 18 7.3.1 Operational Model ...... 19 7.3.2 Data ...... 19 7.3.3 Method ...... 19 7.3.4 Cost Correction for Effective Changes in Demand ...... 19 7.3.5 Implementation ...... 20 7.3.6 Results ...... 20 7.4 Environmental Impact ...... 20 7.4.1 Expected Emissions if Operational in 2017 ...... 21 7.4.2 Future Emissions Prediction and Offset Potential ...... 21 8 Sensitivity Analysis ...... 23 8.1 Overview ...... 23 8.2 CAPEX Sensitivity ...... 23 8.3 Annual Return Sensitivity ...... 25 9 Discussion of Results ...... 27 9.1 CAPEX Predication ...... 27 9.2 OPEX Prediction ...... 27 9.3 Expected Return ...... 27 9.4 Capital Recovery Time ...... 28 9.5 Emissions Offset Potential ...... 28 10 Conclusion and Recommendations ...... 29 10.1 Overview ...... 29 10.2 Design Improvements ...... 29 10.3 Methodology Improvements ...... 29 10.4 Wider Impact ...... 30 References ...... 31 Appendices ...... 33

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List of Tables Table 1: Major Components of a PHS Facility (Thapar, 2015) ...... 6 Table 2: Turbine Classification (Thapar, 2015) ...... 6 Table 3: Commonly Used Turbine Designs (Thapar, 2015) ...... 7 Table 4: Typical PHS Performance (Barbour, 2016) ...... 8 Table 5: Wivenhoe Power Station (CS Energy, 2017) ...... 13 Table 6: Evaluation Results Overview ...... 16 Table 7: CAPEX Prediction Breakdown ...... 18 Table 8: Installed Capacity and Lifetime Emissions Production by Source ...... 20 Table 9: CAPEX Sensitivity Analysis Parameters ...... 24 Table 10: Annual Return Sensitivity Analysis Parameters ...... 25

List of Figures Figure 1: The ‘Duck Curve’ of the California Electricity Grid (CAISO, 2016) ...... 3 Figure 2: Typical PHS facility layout (Kougias, 2017) ...... 5 Figure 3: Design Framework Flowchart ...... 9 Figure 4: Wivenhoe Power Station Layout (CS Energy, 2017) ...... 13 Figure 5: Average Demand 2017...... 14 Figure 6: Average Pool Price 2017 ...... 14 Figure 7: Cost Breakdown of typical 500MW hydro facility in the USA (IRENA, 2012) ...... 17 Figure 8: Potential for Offset of GHG Emissions ...... 21 Figure 9: Capital Cost Sensitivity ...... 23 Figure 10: Annual Return Sensitivity ...... 26

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Abbreviations: AEMO Australian Energy Market Operator CAISO California Independent Systems Operator CAPEX Capital Expenditure EDT Energy Discharge Time GHG Greenhous Gas IRENA International Renewable Energy Agency NEM National Energy Market OFAT One Factor at a Time OPEX Operational and Maintenance Expenditure PHS Pumped Hydroelectric Storage PPT Peak Period Time PV Photovoltaic QLD Queensland WPS Wivenhoe Power Station

Nomenclature: $ Australian Dollar c Australian Cent US$ U.S. Dollar (approximately AU$1.40 at the time of submission) t Metric ton

CO2e Carbon dioxide equivalent Greenfield Denoting previously undeveloped sites

Unless otherwise stated metric SI units were used throughout this report.

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1 Introduction 1.1 Aim and Research Question The aim of the research was to investigate the viability of upgrading Pumped Hydroelectric Storage (PHS) facilities with the goal of improving performance in a contemporary context. In particular, the research focused on optimising the performance of such facilities as a means of increasing the utilisation of renewable energy technologies and thus reducing net greenhouse gas emissions. The following research question was formulated to align with these goals: Can the performance of existing Pumped Hydroelectric Storage facilities be improved to have an overall positive effect on the environment and, if so, at what are the costs involved? The research conducted focused on applying and exploring this research question through the design and evaluation of a proposed upgrade to an existing PHS facility in Queensland, Australia. 1.2 Impact The research into the upgrade of an existing PHS facility yielded, in general, promising results both in terms of economic feasibility and environmental impact. The direct consequence of this is the recommendation that research be continued into the specific case investigated to further the design and improve the accuracy of the results. In a more general sense, showing that upgrading a PHS facility can produce positive results indicates that research into upgrading other facilities is warranted and worthwhile investigating. The general methodology used throughout this research could be adapted and applied to other PHS facilities both in Australia and worldwide. 1.3 Thesis Scope The research in this report was focused around increasing the generating capacity of PHS plants to improve overall performance as an energy storage facility. This was identified to be a particularly effective method of performance optimisation for PHS facilities connected to electrical grids with significant amounts of solar PV. Other means of upgrading PHS facilities, the construction of new PHS facilities and other energy storage options are outside the scope of this research. 1.4 Contents of Report The research conducted in this report was broken down into 10 main Sections. An overview of the contents of each of the following Sections is given below. Section 2: Background Provides relevant background information and shows the motivation behind the research investigating PHS as a means of increasing the adoption of renewable energy technologies. Section 3: Pumped Hydroelectric Storage Gives an overview of the functionality of PHS, its use cases, and what type of performance characteristics are typically achievable. In addition to this it provides insight into why the research focused on upgrading existing PHS facilities by increasing generating capacity. Section 4: Design Framework Provides the framework used to develop a preliminary design proposal for a generating capacity increase if it was determined that this would be beneficial for the selected PHS facility. FAA-MECH4500 Page 1 of 47

Section 5: Case Study Method Outlines the approach used to evaluate the design proposal produced using the framework provided in Section 4. Section 6: Upgrade Proposal – Wivenhoe Power Station It was identified that Wivenhoe Power Station would likely benefit from an increase in generating capacity and subsequently a preliminary upgrade design was produced using the framework outlined in Section 4. Section 7: Evaluation The proposed upgrade was analysed to gain an insight into the performance of the design. Predictions were made for the cost, return and environmental impact of the upgrade so the viability of the design could be evaluated. Section 8: Sensitivity Analysis Verifies the major outcomes from the evaluation in Section 7 and provides an insight into how changing various input parameters and assumptions affects the predicted performance of the design. Section 9: Discussion Discusses the results produced in the evaluation of the design and subsequent sensitivity analysis, identifying any significant or unexpected outcomes from the research. Section 10: Conclusion and Recommendations Gives an overview of the outcome case study and suggests ways in which the research be continued, giving recommendations for both methodology and design improvements. In addition to this, the wider impact of the research was discussed.

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2 Background 2.1 Shift Towards Renewable Energy Technologies Due to the onset of climate change, over the past decades the world has seen an increase in the use of renewable energy sources as a means of producing electricity. This is expected to continue, with most of the growth to come from the increased use of solar photovoltaic (solar PV) and wind energy technologies. It is expected by 2022, 82% of all renewable energy being generated will come from either of these sources. (International Energy Agency, 2017) 2.2 The Problem with Renewable Energy Sources An issue that comes with renewable energy sources such as solar and wind is the problem of intermittency. Unlike traditional energy sources from fossil fuels, the amount of energy that is produced from these sources at any given time is determined by natural factors that cannot be controlled. This creates a problem when it comes to the management of an electricity grid as the amount of power produced must be matched to the instantaneous demand for electricity in real time. For the widespread adoption of renewable energy technologies this problem must be overcome. 2.3 Solar PV and the ‘Duck Curve’ In Queensland, the government has committed to a renewable energy target of 50% clean energy generation by 2030. As Queensland has some of the most abundant solar resource in the world, most of the increase in the states renewable energy capacity is expected to come from solar PV. (QLD Government, 2018) A problem that comes with the increased use of solar PV in an electricity grid is the onset of a phenomenon commonly referred to as the ‘duck curve’. (see fig. 1) The name comes from the typical shape of the daily demand curve of an electricity grid using solar PV to generate a significant portion of its electricity.

Figure 1: The ‘Duck Curve’ of the California Electricity Grid (California Independent System Operator, 2016) Once installed, the energy produced during midday periods by both rooftop and large-scale solar PV installations will always be sold to the energy grid as the marginal cost of producing electricity is virtually zero. This causes an effective decrease in the net demand of the electricity FAA-MECH4500 Page 3 of 47 grid during the midday period when solar PV generates electricity. This effect can be clearly seen in fig. 1 which shows how the daily demand curve of the California electricity grid is changing. During the past number of years, the amount solar PV used in California has been growing to a point in 2017 where almost 40% of the electricity generation in the state came from solar PV. (Jones-Albertus, 2017) This phenomenon causes significant issues when it comes to grid management due to the large increase in demand which occurs over a relatively short period of time in the afternoon to meet the evening peak in demand. This effect typically causes higher electricity costs during the afternoon/evening and commonly results in a shorter and more abrupt peak-load period. It is expected that the demand curve of the Queensland electrical grid will follow the trend seen in California and the ‘duck curve’ will become an increasing problem. 2.4 Energy Storage as a Solution By having the capacity to store large amounts of electrical energy (in the order of GWh), the stated problems that come with intermittent renewable energy technologies can be overcome. By storing excess energy that is produced from renewable sources, this energy can be released when required to meet the grid demand. In addition to this, energy storage can also be used to counteract the negative effects of the ‘duck curve’. By storing energy during midday periods when solar PV installations are generating, the risk of over-generation is reduced as is the intensity of the ramp required to reach the peak demand in the afternoon/evening. There are a variety of different methods of storing the amount of energy required to overcome the problems inherent to renewable energy sources. This research will focus on Pumped Hydroelectric Storage as it is the only commercially proven method of storing the GWh of energy required to solve the outlined problems with renewable energy. (National Hydropower Association , 2012)

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3 Pumped Hydro Storage 3.1 Functional Overview 3.1.1 Primary Purpose Pumped Hydro Storage facilities are typically used as peak-load suppliers of energy to improve the overall performance of an electricity grid. This is achieved through the operation of PHS plants such that they generate electricity when the demand is highest and store energy when the demand is lowest (or there is an excess supply of energy). Due to ability of PHS facilities to respond to large changes in demand within seconds, these facilities also improve overall grid stability by providing critical ancillary services such as short-term load matching and network frequency control. (Energy Storage Association, 2018) 3.1.2 Operating Principle Pumped Hydro Storage functions by cycling water between 2 reservoirs that are at different levels of elevation. It works on the simple principle of gravitational potential energy. By holding a volume of water at an elevated height potential energy is stored and can be extracted when required. Because of this, the formula for calculating the amount of energy stored (E) in a PHS system is given by the simple equation: 퐸 = 휌𝑔ℎ푉 Here ρ is the density of water, V is the volume of water in the upper reservoir and h is the average height difference between the upper and lower reservoirs. 3.1.3 Phases of Operation A PHS facility operates in three main phases: Pumping Phase: During this phase the facility pumps water from the lower reservoir to the upper reservoir thereby storing energy. Generating Phase: During this phase water is allowed to flow from the upper to the lower reservoir with energy being extracted in the process. Storing Phase: During this phase water is held in the upper reservoir thus storing energy. This can be done indefinitely with the only minimal storage losses coming from evaporation and seepage. In practice additional phases such as start-up and shutdown of the pumps and turbines between the 3 main phases must been considered. However, for simplicity, these additional phases were neglected as they typically last a period of less than 90s and considering this are not significant to the research. (Clean Energy Council, 2014) 3.1.4 Major Components and Configuration Table 1 gives the major components of a typical PHS facility as well as a description of the role each plays in the storage and release of energy. The layout of these components in a typical configuration is illustrated in fig. 2. Upper Powerhouse Reservoir

Motor-Generator

Lower Reservoir Pump/Turbine

Tailrace Figure 2: Typical PHS facility layout (Kougias, 2017) FAA-MECH4500 Page 5 of 47

Table 1: Major Components of a PHS Facility (Thapar, 2015)

Component Description

Usually located at the lower reservoir and contains all the electromechanical Powerhouse equipment such as pumps, turbines, motor-generators and power electronics.

Converts the flow energy of water running from the upper reservoir into Turbine rotational kinetic energy to drive the generating unit. There are various types and configurations of turbine which will be discussed in Section 3.2. Applies work to water from the lower reservoir to achieve the pressure Pump necessary to pump the water to the upper reservoir. Commonly a single, dual function, unit that coverts rotational kinetic energy Motor-Generator to electrical energy during the generating phase and vice versa during the pumping phase. Responsible for integrating the energy being produced/consumed by the Power Electronics/ motor-generator unit with the electricity grid in terms of voltage, frequency Transformers and phase. The power electronics necessary for this is dependent on the type of motor-generator being used. Tunnel used for moving water between the upper reservoir and the Penstock powerhouse. Tunnel used for moving water between the lower reservoir and the Tailrace powerhouse.

3.2 Hydraulic Machinery 3.2.1 Turbines There are a variety of different turbine designs being used in hydroelectric facilities around the world. The different designs are classified both in terms of how the energy is extracted from the flow and the direction the flow travels relative to the spin axis of the turbines (see Table 2).

Table 2: Turbine Classification (Thapar, 2015)

Classification Description Energy Extraction Impulse Turbines work by directly converting the kinetic energy of the flow into Impulse rotational kinetic energy and thus operated under constant static pressures, usually atmospheric pressure. Reaction Turbines extract useful work from a flow by creating a pressure differential as the water flows over the blades. This pressure differential creates a lift force Reaction tangential to the rotor axis, causing rotation and is analogous to the operating principle of wind turbines. Flow Direction Tangential flow Turbines utilise water flowing tangential to the rotational axis of Tangential the runner. Axial Flow Turbines utilise water flowing in the direction parallel to the rotational Axial axis of the runner.

Mixed Flow Turbines have water entering the turbine tangentially to the rotational Mixed axis of the runner and leaving the turbine parallel to rotational axis of the runner.

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An overview of the function of the most commonly used turbine designs as well as the typical hydraulic head ranges for each is given in table 3.

Table 3: Commonly Used Turbine Designs (Thapar, 2015)

Turbine Head Range Description Design (m)

Pelton turbines are tangential flow, impulse turbines. Pressurised water is accelerated through a nozzle into a chamber at atmospheric pressure. This high velocity stream of water transfers kinetic energy to the rotor Pelton > 300 by striking specially designed buckets on the rotor. These buckets are designed to redirect the stream at almost 180 degrees to achieve maximum energy transfer.

Francis turbines are mixed flow turbines that extract energy from both the velocity of the flow and the pressure differential created over the rotor blades. This means Francis turbines simultaneously act as both Francis 15 – 750 impulse and reaction turbines. These turbines are characterised by a fixed blade rotor and a spiral inlet casing which gives water rotational velocity prior to passing over the rotor blades.

Kaplan turbines are reaction turbines that are produced in both mixed and axial flow configurations. These turbines are characterised by Kaplan < 40 having adjustability in the angle of both the inlet guide vanes and the rotor blades. This allows Kaplan turbines to achieve high levels of efficiency over a relatively wide range of flow rates.

3.2.2 Pumps The majority of PHS facilities use centrifugal pumps to provide the pressure necessary for the water to reach the upper reservoir. These pumps are limited by the onset of cavitation and thus, depending on the specific design, can only supply water to a maximum height of 150 – 200m. For PHS facilities with heads higher than this multiple pumping stages must be used. (Knapp, 2017) 3.2.3 Dual Function Pump-Turbines The design of a Francis turbine can be modified such that it can also act as a centrifugal pump when the direction of rotation is reversed. As this modified design must compromise between the individual requirements of being both a pump and a turbine the efficiencies that are achievable are typically lower than that of the single purpose hydraulic machines. Despite this, using dual function pump-turbines can often be a more economical solution compared to having separate, dedicated pump and turbine units as the total cost of the machinery is lower. (Voith, 2017) 3.3 Performance Characteristics Pumped hydro storage is a mature and proven technology that has been around for almost a century. It is estimated that 99% of the world’s electrical energy storage capacity is provided by PHS. (World Energy Council, 2016) This can be attributed to the performance characteristics and inherent properties of PHS that make it the most cost-effective method of storing GWh of electrical energy. A summary of the typical performance characteristics of grid-scale PHS systems is shown in table 4.

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Table 4: Typical PHS Performance (Barbour, 2016)

Storage Capacity 0.5 – 20 GWh Generating Capacity 50 – 3000 MW Full Cycle Efficiency 70 – 85 % Storage Capital Cost 14 – 430 US$/kWh Lifespan +50 y

3.4 Drawbacks One of the major downsides of PHS is the high capital cost (typically hundreds of millions of $) primarily due to the large amounts of civil works required in constructing a greenfield facility. In addition to this the process of gaining regulatory approval to build a PHS plant typically takes several years. When including actual construction time, the full development and implementation of a PHS project typically takes 6 to 10 years. Due to these high costs and long lead times, financing PHS projects can be challenging and this limit and slows the development of new facilities. (National Hydropower Association , 2012) In addition to this, due to the specific geographical requirements, the number of sites where PHS is viable is limited. This is especially true in countries like Australia that are relatively flat topographically. 3.5 Potential in Upgrading Existing Facilities Because of the age of the technology, a significant portion of the PHS facilities in operation today were built decades ago and may not be optimised for the energy storage and grid requirements of today. From this it was identified that the performance of existing facilities could be improved as an alternative means of effectively increasing the energy storage capabilities of an electrical grid. The research conducted focused on the feasibility of upgrading existing PHS facilities in QLD. This was done because of the large costs and lead times involved with constructing new PHS plants. In addition to this the number of sites where PHS is viable is limited due to QLD’s relatively flat topography. In particular, it was identified that existing PHS facilities in QLD would likely benefit from an increase in generating capacity. This was determined due to the onset of the ‘duck curve’ (see Section 2.3) causing the duration of the peak-load period to become shorter and more abrupt than what was experienced by the QLD electricity grid in the past. By increasing the generating capacity, the operation of PHS plants can be improved under these contemporary grid conditions. How this is achieved is explained further in the following Sections.

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4 Design Framework 4.1 Flow Chart Figure 3 shows the framework used to determine if the PHS facility being investigated would benefit from an increase in generating capacity and if so, produce a preliminary design proposal that would achieve the necessary increase. The shaded element seen in fig. 3 represents the possibility of identifying and developing other method of upgrading the selected facility (outside the scope of this research).

Select existing PHS facility

Step 1: Data Collection Electricity PHS Facility Grid Data Data

Step 2: Viability of Capacity Increase Estimate Peak Period Calculate Energy Time (PPT) Discharge Time (EDT)

Compare Values

Review Data and Consider Is PPT ≤ EDT? Yes Alternative Upgrade Options

No

Step 3: Design Development

Determine Capacity Consider Additional Increase Improvements

Select Hydraulic Develop and Refine Machinery Design

Outline Specifics of Preliminary Design Proposal

Figure 3: Design Framework Flowchart

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4.2 Steps Involved

Step 1: Data Collection After the PHS plant had been selected, all available data on the facility had to be obtained to give the best possible understanding of the facility’s capabilities and operational characteristics. In addition to this, data from the electricity grid to which the facility is connected was gathered to understand the operational requirements the plant would be subject to. Step 2: Viability of Capacity Increase Once all available data had been gathered, it had to be determined whether the facility could benefit from an increase in generating capacity. To do this, two parameters had to be determined and compared. From the generating and storage capacity of the existing facility the time taken for the facility to discharge its full amount of stored energy (EDT) could be calculated. By observing the price and demand curves of the electrical grid over a typical daily cycle, the duration of the peak period (PPT) could be estimated. If the PPT was greater than the EDT the facility would be unable to release its full amount of stored energy in during the peak period and thus would likely benefit from an increase in generating capacity. Step 3: Design Development After determining the need for an increase in generating capacity to the selected facility a preliminary design for achieving this had to be developed. To do this, it first needed to be determined how much additional generating capacity the upgrade would add. The aim was to increase the generating capacity to lower the EDT of the facility with the goal of making it as close as possible to the PPT whilst considering other factors such as cost effectiveness and optimal machinery selection. Once the specific hydraulic machinery had been selected the specifics of the upgrade proposal were clearly outlined so the performance of the design could be evaluated.

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5 Case Study Method 5.1 Overview The method used when conducting the research is that of an exploratory case study. The purpose of this research method is to provide a preliminary insight into the case being investigated with the aim of determining whether a more in-depth investigation is justified. 5.2 Application In this research, the subject of the study (the case) was a preliminary design proposal for increasing the generating capacity of an existing PHS facility. This design was produced using the framework outlined in Section 4. Once the design of the upgrade for had been developed, a cost benefit analysis was conducted to predict how the proposed upgrade would perform. This evaluation was broken down into 3 major components: Cost Analysis The specific cost (in $/kW) of the selected PHS facility when it was originally built was used as the basis of the calculation for the expected capital expenditure (CAPEX). A cost breakdown was applied to estimate the specific cost of each of the major components of the original facility (reservoirs, machinery etc.) individually. By correcting each of these individual costs to account for what was necessary in implementing the upgrade the total specific cost of the upgrade could be predicted. By applying this to the generating capacity of the proposed upgrade the estimated CAPEX could be found. The expected annual operational and maintenance cost (OPEX) was then calculated as a percentage of the predicted capital cost. Expected Return The expected return was found by analysing how the upgraded facility would have performed if it had operated in the previous calendar year. This was done by developing a model of how the facility would operate during the daily cycle of the electricity grid and applying this model to historical grid data obtained for that year. By finding the profit that would have been made for each day during the year the expected annual return was found. Environmental Impact The environmental impact the proposed design would have was predicted by examining how the upgraded facility would affect the net greenhouse gas (GHG) emissions of the electricity grid in a single daily cycle. To do this it was first determined what energy sources were currently being used to generate electricity during the peak-load periods of the grid. From this, the amount of CO2e being offset through the reduced use of these energy sources could be found. In a similar way, the energy sources that would supply the PHS facility with energy for pumping during periods of low demand were identified so the amount of CO2e produced during pumping could be estimated. By subtracting this from the emissions offset during generating the net effect on CO2e production could be found. By comparing each of these outcomes the overall performance and viability of the preliminary design could be evaluated. From this, it could be determined whether the specific case being investigated warrants further, more in-depth and extensive research. The result would also give an indication into whether the design framework could be applied to other existing PHS facilities to evaluate the feasibility of an increase in generating capacity.

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Because of variations in available data, grid conditions and the fact that no two PHS facilities are the same, the exact method used in determining the viability of an upgrade design must be developed on a case by case basis. For the case examined in this research the exact method and assumptions made are outlined in the following Sections.

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6 Upgrade Proposal – Wivenhoe Power Station 6.1 Selection of Existing Facility Wivenhoe Power Station (WPS) was selected as the facility that would be investigated. This facility was chosen as it is the largest PHS plant currently operating in Queensland and was commissioned more than 30 years ago. Using the framework outlined in Section 4 a preliminary design proposal was produced. 6.2 Step 1: Data Acquisition 6.2.1 Facility Data The Wivenhoe power station is a PHS facility located approximately 80 km north west of Brisbane. Commissioned in 1984, the facility is owned and operated by CS Energy Ltd. and has an expected design lifetime of 100 years. The facility uses two 285 MW reversible pump- turbines to cycle water between Wivenhoe Dam (lower reservoir) and Splityard Creek Dam (upper reservoir) as is illustrated in fig. 4. The key operational parameters of WPS are given in table 5. (CS Energy, 2017)

Table 5: Wivenhoe Power Station (CS Energy, 2017)

Generation Capacity 570 MW Storage Capacity 5700 MWh Upper Reservoir Capacity 23,300 ML Average hydraulic head 91 m Tunnel length 420 m

Figure 4: Wivenhoe Power Station Layout (CS Energy, 2017) 6.2.2 QLD Electricity Grid Wivenhoe Power Station is connected to the Queensland Electricity Grid which is part of National Energy Market (NEM). The NEM is regulated by the Australian Energy Market Operator (AEMO) which provided the QLD electricity grid data for the 2017 calendar year. The data used gave the wholesale price of electricity and instantaneous demand at 30-minute intervals. For a sample of the raw data used refer to appendix A. FAA-MECH4500 Page 13 of 47

6.3 Step 2: Viability of Capacity Increase From the storage and generating capacity of WPS shown in table 5, the energy discharge time (EDT) was calculated to be 10 h. This means the facility can generate electricity at full capacity for a total of 10 h before the usable water in Splityard Creek Dam has been exhausted and the facility must begin pumping. From the data supplied by the AEMO figures 5 and 6 were produced. Figure 5 shows the average daily demand curve of the QLD electricity grid in 2017 while fig. 6 illustrates the average wholesale price curve. For the averaged 2017 data used to produce these figures refer to appendix B.

7500

7000

6500

6000 Estimated Peak Period

5500 Demand (MW) Demand

5000

4500

Time of Day

Figure 5: Average Demand 2017

350

300

250

200

150

Price ($/MWh) Price 100 Estimated Peak 50 Period

0

Time of Day

Figure 6: Average Pool Price 2017 Using these average demand and price curves the duration of the peak-load period was estimated. From fig. 5 and the data given in appendix B it can be seen that the average demand peaks above 6500 MW between 15:00 and 22:00. Similarly, the average price peaks above $100/MWh roughly between 15:00 and 21:00. It was therefore estimated that the peak period of the QLD electricity grid is typically between 6 and 7 h long. Comparing this to the 10 h it takes for WPS to release the entirety of its stored energy, it was identified that the facility would likely benefit from an increase in generating capacity. FAA-MECH4500 Page 14 of 47

6.4 Step 3: Design Development Once the need for an increase in generating capacity had been confirmed, a design to achieve said increase was developed. It was calculated that a capacity increase of 244 - 380 MW would be required to reduce the EDT of WPS to 6 - 7 h. Using this and considering other factors such as cost effectiveness and optimal machinery selection the following design proposal was developed. It is proposed that an additional pump-turbine unit be installed to work alongside the 2 existing units. This 3rd reversible Francis turbine would be of the same size and type as the currently installed units with a generating capacity of 285 MW. This design decision was made based on several contributing factors:  The existing units are optimised for the hydraulic head and other conditions specific to WPS.  The reversible Pump-Turbine configuration has previously been determined to be the most economically viable option for this location.  The staff currently working at WPS are familiar with the operation and maintenance on these machines meaning little to no additional training would be required for day- to-day operation.  Using the existing design already developed specifically for WPS would reduce the cost as opposed to having a new unit be designed. With the inclusion of the third reversible pump-turbine, the total generating capacity of WPS would be increased 855 MW. From this, it can be determined that the upgraded WPS would be able to utilise its full amount of stored energy (5700 MWh) over a period of approximately 6.7 h. This new EDT is better suited to the PPT estimated in Section 6.3 and thus would allow WPS to operate more effectively as a peak-load supplier of energy.

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7 Evaluation 7.1 Overview In order to determine the feasibility of the proposed upgrade to WPS an evaluation was conducted, making predictions on the costs and performance of the design. When conducting the evaluation, the additional proposed 285 MW pump-turbine unit would be analysed as a stand-alone PHS facility. This was done as opposed to analysing the upgraded facility as whole so that any benefits that come from the proposed upgrade can be directly evaluated against the costs involved. In addition to this, aspects of the following evaluation used historical data from the QLD electricity grid which was influenced by the operation of WPS in its current configuration. For simplicity, in the following Sections the proposed 285 MW upgrade to WPS was referred to as ‘Unit 3’.

A summary of the main outcomes of the evaluation is shown in table 6. How these results were obtained as well as any assumptions made and data that was used is described in detail in the following Sections.

Table 6: Evaluation Results Overview

CAPEX $ 225.4 million OPEX $ 5.6 million Annual Revenue $ 22.6 million Capital Recovery Time 13.3 y

Max. Carbon Offset Potential 219 kt⸱CO2e/y

7.2 Cost Analysis 7.2.1 Capital Cost When estimating the capital expenditure required to construct a hydroelectric power facility the cost is commonly examined as a specific cost per kW of generating capacity. The CAPEX required to build a large hydro-electric facility (above 100 MW) commonly ranges between US$1000 and US$3500 per kW. (IRENA, 2012) When Wivenhoe Power Station was first built (commissioned in 1984) it cost a total of $245 million and had an output capacity of 500 MW. (Queensland Government, 1984) Adjusted for inflation this is a CAPEX of approximately $742 million giving the facility a specific capital cost of $1484/kW. This value was used as the basis for the cost analysis due to the cost of hydroelectric facilities being highly specific to the area where they are constructed. The International Renewable Energy Agency (IRENA) gives a breakdown of the costs involved in building an indicative 500 MW hydroelectric generating facility in the United States of America, shown in fig. 7.

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Figure 7: Cost Breakdown of typical 500MW hydro facility built in the USA (IRENA, 2012) By applying this percentage breakdown to the total specific cost to build WPS ($1484/kW), the specific cost for each component of WPS when it was built could be estimated. (see table 7) Considering that some of the components required for Unit 3 to function are already built (e.g. reservoirs), it is expected that the specific cost of the proposed upgrade be significantly less than the cost of building a greenfield facility. To account for this, the estimated specific costs of each component of WPS were individually adjusted to obtain a prediction for the total specific cost of Unit 3. For a full breakdown of the costs of each component and adjustments made, refer to table 7.

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Table 7: CAPEX Prediction Breakdown

% of total Specific Cost Predicted Cost Adjustment Component Cost from for WPS for Upgrade Justification Factor IRENA ($/kW) ($/kW) Both upper and lower reservoirs already exist. 10% of initial cost Reservoir 26% 386 0.1 38.6 included to account for any minor modifications that may have to be made to existing reservoirs. New tunnels must be built between upper and lower reservoirs to Tunnels 14% 208 1.0 208.0 accommodate the increase in flow rate required. The powerhouse would need to be increased in size to accommodate Powerhouse 14% 208 1.0 208.0 UNIT 3 along with the requirement of and Shafts additional shafts for coupling electromechanical equipment. Additional 20% included to accommodate for the fact that for UNIT 3 the main mechanical Powerhouse 16% 237 1.2 284.4 component is a reversible pump- Equipment turbine as opposed to the single purpose turbine units in the indicative 500 MW facility. Only 50% of total cost included due Engineering to the reduced requirement for and 7% 104 0.5 52.0 Engineering, Procurement and Management Management because of the reduced civil/construction works. Land rights assumed to be already Ownership 23% 341 0.0 0.0 under the ownership of the entity Costs constructing the upgrade. Total Specific Cost of Unit 3 791.0

From this high-level cost estimation, the predicted specific cost was found to be $791/kW. This result is further justified by IRENA who state that the cost of hydroelectric installations at sites with existing reservoirs can be as little as US$500/kW. (IRENA, 2012) By applying the 285 MW generating capacity of the upgrade to the predicted specific cost the estimated CAPEX was found to be $225.4 million. 7.2.2 Operational and Maintenance Costs IRENA states that the OPEX of a hydroelectric facility is usually predicted as a percentage of the initial capital expenditure per year. It states the average values of 2.0% to 2.5% per year to be the norm for large scale hydroelectric installations (above 100MW). This OPEX estimate includes large scale equipment refurbishment such as generator rewinding and turbine overhaul as well as general maintenance and continued optimisation of the communication/control systems. Not included in this estimate is the replacement of electromechanical equipment or large-scale civil works as these operations are usually only required every 30 – 50 years. (IRENA, 2012) Taking the larger value of 2.5% to account for the added complexity of Unit 3 being a PHS facility we calculate the annual OPEX to be approximately $5.6 million. 7.3 Expected Return In order to predict the annual revenue generated by the proposed upgrade to WPS it was examined how Unit 3 would have performed if it were operational during the 2017 calendar year. To do this, a model outlining the typical daily operation of Unit 3 first had to be realised. Once this was done, the model could be applied to historical data from 2017 to predict how Unit 3 would have performed if it were operational during that period. FAA-MECH4500 Page 18 of 47

7.3.1 Operational Model It was first decided that as part of the operational model, Unit 3 would generate electricity at full capacity for a total of 6 h each day. This was done because although the upgraded WPS could generate at full capacity for 6.7 h without needing to ‘recharge’, this would be un- achievable for every day of the year. Similarly, Unit 3 would also spend 6 hours every day pumping water to the upper reservoir, consuming approximately 407 MW. This was determined under the assumptions that the volumetric flow rate through Unit 3 would be the same in both pumping and generating phases and that the round-trip efficiency of the facility was 70%. Considering that reversible pump- turbines are typically less efficient than PHS systems with designated pumps, this efficiency was selected as it is the lower bound of the typical round-trip efficiency range given in Section 3.3. 7.3.2 Data The data used for the analysis was sourced from the AEMO. This data gives the wholesale price of electricity (in $/MWh) for the QLD grid for every half-hour period in 2017. The data was organised by day, with each row containing the wholesale price of electricity for the 48 half- hour periods of the given day. Refer to appendix C for a sample of the raw data used in the analysis. 7.3.3 Method To maximise profitability, it was assumed Unit 3 would generate at full capacity during the 12 highest priced half-hour periods over a given day. The amount of energy produced in each of these half-hour periods is known (142.5 MWh) along with the price of electricity for each period from the NEM data. Using this the total amount of revenue generated through the sale of electricity on a given day could be found. Similarly, it was assumed Unit 3 would operate in the pumping phase for the 12 lowest priced half-hour periods of each day. The amount of energy that is consumed in each of these half- hour periods is known (203.6 MWh) and thus the total amount spent purchasing the energy required to ‘recharge’ Unit 3 on a given day could be found. By subtracting this from the revenue generated in that day the daily profit could be determined. By repeating this and summing the daily profit for every day in 2017 the annual revenue generated through the operation of Unit 3 was predicted. 7.3.4 Cost Correction for Effective Changes in Demand When in the generating phase of operation Unit 3 would produce 285 MW of electricity. Similarly, when pumping it would consume 407 MW (assuming 70% efficiency). Comparing these values to the demand of the QLD electricity grid which typically varies between 5000 and 8000 MW, it was determined that the effective changes in demand caused by the operation of Unit 3 would be significant. Considering the dynamic nature of the NEM, it was therefore determined that the operation of Unit 3 would have a significant effect on the wholesale price of electricity and could not be neglected. To account for this a relationship between demand and price was found. This was achieved by plotting the wholesale electricity price against the corresponding demand for every half-hour period in 2017 and finding the linear line of best fit. (see appendix D) From this linear relationship it was determined that for every MW increase in demand the price of electricity would increase by approximately 7.69 c. Therefore, with an effective 285 MW decrease in demand experienced when Unit 3 would be generating we expect a decrease in price of FAA-MECH4500 Page 19 of 47 approximately $21.9/MWh. Similarly, with the effective 407 MW increase in demand experienced when Unit 3 would be pumping we expect the electricity price to increase by $31.9/MWh. 7.3.5 Implementation Because of the large amount of data (17000+ data points), a python script (see appendix E) was used to implement the method described in Section 7.3.3. The script would iterate through the rows of data each representing a full day of electricity prices. For each of these days, the prices were arranged from lowest to highest. The prices for each of the 12 highest priced half-hour periods were then corrected (as discussed in 7.3.4) and multiplied by the energy generated to find the revenue made on a given day. In the same way, the prices for each of the 12 lowest priced half-hour periods were corrected and multiplied by the energy consumed to find total amount spent consuming energy. This value was then subtracted from the revenue generated to find the daily profit. The script would then add the calculated profit for the given day to a cumulative total. By repeating this for every day in 2017 the expected annual return was found. 7.3.6 Results When executed, the script predicted the annual return to be approximately $22.6 million. (see appendix E) Using this value and the expected CAPEX and OPEX calculated in Section 7.2 the capital recovery time was calculated to be approximately 13.3 years. 7.4 Environmental Impact The amount of carbon dioxide (or equivalent) able to be offset through the operation of Unit 3 is entirely dependent on the primary energy source of WPS (i.e. where the energy used for pumping comes from). As WPS consumes energy from the grid this energy could come from a variety of different sources. Table 8 gives a summary of QLD’s current generating capacity by 1 source as well as the average amount of CO2e produced when generating 1 MWh of electricity for each of the given sources. For the full lists of QLD’s generating capacity and the amount of CO2e produced by source see appendices F and G respectively.

Table 8: Installed Capacity and Lifetime Emissions Production by Source

Energy Installed % of Total Emissions [2] [1] Source Capacity Capacity kg·CO2e/MWh Coal 8127.9 59.9 888 Natural Gas 4432.2 32.6 499 Hydro 168.4 1.2 26 Solar 112.0 0.8 85 Other 739.2 5.5 - Total 13579.7 100.0 - [1] (Queensland Government, 2018) [2] (World Nuclear Association, 2011) In the following predictions, the emissions generated during the manufacture and the construction of Unit 3 have been accounted for through the inclusion of the average lifetime emissions of hydroelectric power stations seen in table 8.

1 When discussing greenhouse gas (GHG) emissions it is commonplace to use the unit of carbon dioxide equivalent (denoted CO2e). This is done because although CO2 is the most abundant GHG with the largest impact on our planet, there are many other atmospheric gases that also contribute to the greenhouse effect. FAA-MECH4500 Page 20 of 47

7.4.1 Expected Emissions if Operational in 2017 Table 8 shows that more than 90% of Queensland generating capacity comes from coal and natural gas, both of which are highly polluting fossil fuels. As natursl gas is commonly only used to provide energy during peak demand periods it can be assumed that virtually no energy from gas would be used to ‘recharge’ WPS. Coal on the other hand is a high inertia, base-load power supplier and thus would supply almost all the grids power during times of low demand. (de Rooij, 2015) From this it was assumed that if in operation today 100% of the energy consumed during the pumping phase would come from coal-fired power stations. Under this assumption and considering efficiency losses it was determined Unit 3 would be a net producer of GHG emissions. Using the operational model outlined in Section 7.3.1 it was calculated that Unit 3 would consume 2442 MWh/d from coal-fired power stations while producing 1710 MWh/d. Using the lifetime values for CO2e production from table 8 and assuming Unit 3 would be replacing gas-fired power stations as a peak-load provider it was calculated that Unit 3 would be responsible for the production of approximately 1361 t⸱CO2e/d. From this, the predicted annual emissions of Unit 3 was found to be approximately 497 kt⸱CO2e. For full calculations see appendix H. 7.4.2 Future Emissions Prediction and Offset Potential As the use of renewable energy technologies grows, the amount of energy from these sources (particularly solar PV) being used in pumping would increase. As this happens, the amount of CO2e produced during the pumping phase of WPS would decrease. This will continue until a point where the operation of Unit 3 would offset more CO2e from the burning of natural gas than it would produce during pumping. Thus, Unit 3 would become “carbon negative” offsetting more CO2e than it is responsible for producing. To visualise this effect fig. 8 was produced showing how the amount of emissions offset by Unit 3 would increase as less energy from coal-fired stations is used.

% of Energy from Coal 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 750

500

250

0

-250

-500

-750

-1000 GHG Emmisions (T·CO2e/d) Offset Emmisions GHG -1250

-1500 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % of Energy from Solar

Figure 8: Potential for Offset of GHG Emissions FAA-MECH4500 Page 21 of 47

As solar PV is expected to continue to grow to become the largest supplier of renewable energy in QLD, fig. 8 shows how the amount of CO2e being offset by Unit 3 would increase if coal was replaced by solar PV as the primary energy source of WPS. Using this model, if approximately 70% of the energy consumed by WPS came from solar PV the facility would be carbon neutral. With 100% solar energy being supplied to Unit 3 the amount of emissions being offset was determined to be approximately 601 t·CO2e/d. (see appendix H for calculation)

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8 Sensitivity Analysis 8.1 Overview In order to validate the results produced in Section 7, a sensitivity analysis was conducted. This was done on the CAPEX and expected return predictions. (Sections 7.2.1 and 7.3) These results were selected as they were identified to be the most influential factors in determining the viability of the upgrade proposal. In addition to this, the methods used for these calculations were more refined and intensive when compared to the other evaluation results. The method used to conduct the following analysis is known as the one-factor-at-a-time (OFAT) method. This was done by varying a single input parameter while leaving all others at a defined baseline value and examining the subsequent change in the output. By observing how the output changes as each input is varied individually the robustness of the results could be determined. 8.2 CAPEX Sensitivity The CAPEX estimate from Section 7.2 was one of the most significant outcomes from the evaluation conducted as it is a highly influential factor when determining economic viability. It was therefore determined that testing this outcome to variations in the input parameters was critical. Table 9 outlines the baseline values used for the input and output parameters as well as the amount the inputs were varied by in the sensitivity study. By applying the outlined variations in input parameters and recording the subsequent change in CAPEX fig. 9 was produced. For tabulated data used in production of fig. 9 see Appendix I.

1050

WPS Total Specific Cost 1000 Cost of Reservoir Cost of Tunnels 950 Cost of Powerhouse/Shafts Cost of Powerhouse Equipment 900 Cost of Engineering/Management

850 Specific Cost ($/kW) Cost Specific

800

750

700 -30% -20% -10% 0% 10% 20% 30% 40% % Change From Baseline

Figure 9: Capital Cost Sensitivity

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Table 9: CAPEX Sensitivity Analysis Parameters

Assumption Baseline Value % Variation Parameter Justification of Selected Range Challenged (AU$/kW) from Baseline Output Specific Capital Cost – 791.0 – – Inputs Calculated Positively skewed range as certain specific cost of -10% changes in contributing factors (cost Total Specific Cost of WPS when built 1484.0 of labour, construction costs etc.) WPS is still valid in +30% since 1984 would most likely cause 2017. costs to be higher in 2017. Large range due to uncertainty in the Validity of % -10% extent of work to existing reservoir Specific Cost of cost breakdown 38.6 required to for the upgrade and Reservoir and correction generally high cost of factor applied. +50% civil/construction works.

-30% Estimated uncertainty in accuracy of Specific Cost of Validity of % 208.0 the assumed % breakdown of total Tunnels cost breakdown. +30% costs. As above. Positively skewed range -20% due to possible complications arising Specific Cost of Validity of % 208.0 from interfacing extension of Powerhouse/Shafts cost breakdown. +30% powerhouse with existing infrastructure. Positively skewed due to added Validity of % Specific Cost of -10% complexity surrounding the cost breakdown Powerhouse 284.4 reversible pump-turbine and correction Equipment configuration above what correction factor applied. +20% factor accounted for. Validity of % Estimated uncertainty due to -20% cost breakdown accuracy of the applied cost Specific Cost of EPM 52.0 and correction breakdown and assumption of +20% factor applied. reduced EPM costs.

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8.3 Annual Return Sensitivity Table 10 outlines the baseline values for the output and input parameters used in the sensitivity analysis of the expected return. In addition to this it shows how each input parameter was varied from the baseline and gives a justification for the selected range for each. The script described in Section 7.3.5 was modified so that the input parameters could be individually varied as required. (see appendix K for modified script) The changes in output when the script was executed for each case was recorded. From this fig. 10 was produced showing how varying each of the input parameters affected the annual return prediction. For the data used in the production of fig. 10 refer to appendix J.

Table 10: Annual Return Sensitivity Analysis Parameters

Range of Assumption Baseline % Variation Justification of Selected Parameter Inputs Challenged Value from Baseline Range Tested Output Expected $22.54 Annual – – – – million Return Inputs

-5% 66.5% Positively skewed range due to Full cycle assumed value for efficiency Efficiency efficiency of 70% being at the lower end of the upgrade. +15% 80.5% typical efficiency range of PHS plants found through research.

Validity of the -15% 6.54 c/kW Cost linear model used 7.69 Estimated uncertainty in the Correction to calculate cost model used. Factor c/kW correction factor. +15% 8.84 c/kW

-16.67% 5 h Positively skewed range as That the upgraded with the given storage capacity Total Time in WPS has enough of WPS at current the upgraded Each stored energy to facility could operate for a Operational 6 h operate for 6 maximum of approximately 6.7 Cycle per Day +8.33% 6.5 h hours each day. hours before needing to begin pumping.

That the time 0% 6 h Positively skewed as it is required in the unlikely for the pump-turbine Time spent pumping phase is unit to be capable of pumping Pumping each equal to the time 6 h at a higher flow rates than what day spent generating 25% 7.5 h is experienced when in (per day) operation as a turbine.

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40

Hours Required For Pumping Operational Hours Per Day 35 Cost Correction Factor Efficiency

30

25

20 EXPECTED ANNUAL ANNUAL RETURN MILLION) ($ EXPECTED

15 -20% -15% -10% -5% 0% 5% 10% 15% 20% 25% 30% % CHANGE FROM BASELINE

Figure 10: Annual Return Sensitivity

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9 Discussion of Results 9.1 CAPEX Predication From the method described in Section 7.2.1 the total CAPEX of the proposed upgrade was predicted to be $225.4 million. This method used the specific cost of WPS when it was built as the basis of the CAPEX calculation due to the highly site-specific nature of the cost of hydroelectric facilities. This cost was disassembled using a cost breakdown of a typical hydroelectric generating facility provided by IRENA. This cost breakdown was used as it came from a reputable source and because of the similarities between the characteristics of the indicative facility provided and WPS when it was built. These similarities include both having the same output capacity (500 MW) and being located in developed countries with comparable labour costs. Despite this, there were a number of differences between the typical facility given by IRENA and WPS. These differences were identified and considered when the cost correction factors were applied. Several assumptions were made throughout the process of predicting the CAPEX. These assumptions were challenged in the sensitivity analysis (Section 8.2) to observe how this would affect the predicted CAPEX. From fig. 9 it was determined that CAPEX is most sensitive to the original cost of WPS as this input was the basis of the entire cost prediction. When applying the maximum expected uncertainty in this parameter (+30%) we find that the predicted specific cost of the upgrade grows to $1028 /kW; a specific cost which remains significantly lower than the cost of WPS when it was built. 9.2 OPEX Prediction The annual OPEX was estimated as a percentage of the total capital cost per year. The typical range of 2.0 - 2.5% provided by IRENA was used, with the higher value of 2.5% being selected to give a more conservative estimate. Using this the annual OPEX was estimated to be $5.6 million. A sensitivity analysis was not conducted on the predicted OPEX as it is less significant than the other outcomes and largely dependent on the predicted CAPEX, which itself was subject to a sensitivity analysis. In addition to this, as the calculation only required 2 inputs the outcome of a sensitivity analysis done on the OPEX would be trivial and relatively inconsequential to the research. 9.3 Expected Return The annual profit that would be made if the proposed Unit 3 was in operation (according to the model described in Section 7.3.1) for every day in 2017 was found to be approximately $22.6 million. When the predicted profits of each day in 2017 were examined individually, it was observed that a significant number of these daily profits were negative. Hence, on these particular days operating Unit 3 according to the given model would result in net decrease in revenue. The script implemented in Section 7.3 was modified to exclude these daily losses as if Unit 3 would not operate on those particular days. When this was done, the annual return prediction increased to approximately $48.2 million. This indicates that the model being implemented was far from optimal and shows that the facility has the potential to generate more than twice the stated value for predicted revenue. A significant number of assumptions were made in predicting the annual return and subsequently a sensitivity analysis was conducted. The produced sensitivity chart (fig. 10) shows that the annual return is most sensitive to the efficiency of the facility as this directly

FAA-MECH4500 Page 27 of 47 impacts how much energy is needed during pumping. The less energy needed to ‘recharge’ WPS, the less money is spent pumping and thus profits increase. Perhaps the most significant outcome from the sensitivity study, however, was how the annual return changed as the amount of time spent pumping/generating per day was varied. Figure 10 shows clearly that if the operational model was changed so that Unit 3 spent less time pumping/generating each day (i.e. operating in a narrower time window and exchanging less energy) the profit generated will increase. From the raw data (see appendix J) it can be seen that if Unit 3 only spent 5 hours generating and 5 hours pumping each day the annual profits would increase by approximately 25% despite exchanging 16.7% less energy with the grid. This confirms the initial observation that was the basis of the design proposal; that WPS cannot be run optimally while utilising its full amount of stored energy in a daily cycle. In fact, this result indicates that the design proposal could be altered so the total capacity of WPS is increased above the proposed 855 MW and that this would increase the profitability of the facility. 9.4 Capital Recovery Time From the baseline values calculated for CAPEX, OPEX and Annual Return the expected capital recovery time was calculated to be roughly 13 years. Considering that PHS storage facilities commonly have a life time of more than 50 years this is a promising result. In addition to this, as discussed in Section 9.3, the annual profit generated through the operation of Unit 3 has the potential to be significantly larger than the estimated value of $22.6 million. It was therefore assumed that under an optimal, profit maximising operational model the capital recovery time would be significantly lower than the 13 years calculated. 9.5 Emissions Offset Potential If in operation today, Unit 3 would get most its energy from coal-fired power stations. Because of this, Unit 3 would be a net producer of GHG emissions and have an overall negative effect on the environment. However, as shown is Section 7.4.2, if the amount of energy from renewable sources consumed during pumping were to increase so too would the facility’s ability to offset GHG emissions. It was shown that if powered 100% by solar energy Unit 3 would offset approximately 601 t·CO2e/d. Note that as mentioned in Section 7.4, this emissions estimate takes into account CO2e production related to the manufacture and construction of Unit 3.

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10 Conclusion and Recommendations 10.1 Overview The outcomes of the evaluation of the preliminary design proposal yielded promising results indicating the proposed upgrade is both financially viable and has the potential to be a valuable means of decreasing the net GHG emissions of the QLD electricity grid. Because of the positive results stemming from the preliminary design and evaluation, it was determined that further research into upgrading WPS is warranted. Despite this, the outcomes of the evaluation show that there is room for improvement in both the design specifications and the method in the evaluation. 10.2 Design Improvements It was shown that if in operation today, Unit 3 would be a net producer of CO2e and thus would have a negative effect on the environment. Because of this, it is recommended that further research explores the possibility of constructing a dedicated solar PV farm to supply WPS with the energy required for pumping. This combined PHS and solar PV facility has the potential to be a purely generating facility able to supply the QLD electricity grid with 100% renewable energy on demand when it is needed the most. This would maximise the positive effect on the environment through the reduced use of fossil fuel energy sources during peak-load times. In addition to this, the amount of revenue generated by the facility would be increased as WPS would not need to purchase electricity from the grid to fill the upper reservoir. As the revenue generated by WPS was shown to be highly sensitive to the storage efficiency of the facility, it is recommended that further research investigates ways of maximising the efficiency of the upgrade proposal. This could be achieved through the use of advanced power electronics coupled with asynchronous generator technology or through the implementation of a system with separate, dedicated pump and turbine units to increase the hydraulic efficiency. Although these possible changes would likely increase the CAPEX significantly, the increase in revenue generated could make for a more economical design in the long term. The sensitivity analysis conducted on the expected return (Section 8.3) also indicated that upgraded facility would be more profitable if it were to operate for less hours each day despite exchanging less energy with the grid. From this, it is recommended that further research investigates increasing the generating capacity of WPS beyond the 855 MW proposed in this research. By comparing how CAPEX and profitability change when increasing the generating capacity a more optimal design could be achieved. 10.3 Methodology Improvements To provide a more accurate cost estimation than produced with method used in Section 7.2.1, a more intensive, bottom-up approach must be implemented. This would involve an in-depth examination into what exactly is required for each aspect of the design (civil works, machinery, engineering, labour etc.). By predicting the cost of each of these aspects at an individual level and summing the values a more accurate and refined prediction for the total cost of the upgrade could be found. In addition to this, it was identified that the model used when predicting the annual return of the upgrade was sub-optimal and would differ significantly from the cycles the facility would operate at in practice. It is therefore recommended that a more dynamic model, capable of determining optimum operating conditions on a day by day basis, be developed. Such a model would more accurately predict the profit maximising operation of Unit 3 as the operation of

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WPS would realistically differ from day to day depending on the demands of the electricity grid. 10.4 Wider Impact The case study conducted shows that there are undoubtably potential benefits, both financial and environmental, that can come from upgrading PHS facilities to better suit the grid requirements of today. From this it was determined that upgrading other existing PHS facilities is worth investigating as allowing existing storage facilities to reach their full potential in a contemporary context has been shown to be a cost-effective method of effectively increasing the energy storage capabilities of an electricity grid. Although the exact method used in developing and evaluating an upgrade design must be developed on a case-by-case basis, the research conducted in this report can be interpreted and used as a guide for upgrading other PHS facilities.

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References Barbour, E. (2016). Pumped Hydroelectric Storage (PHS). Retrieved from Energy Storage Sense: http://energystoragesense.com/pumped-hydroelectric-storage-phs/ California Independent System Operator. (2016). What the duck curve tells us about managing a green grid. Retrieved from CAISO: https://www.caiso.com/Documents/FlexibleResourcesHelpRenewables_FastFacts.pdf Clean Energy Council. (2014). Hydroelectricity. Retrieved from Clean Energy Council: https://www.cleanenergycouncil.org.au/technologies/hydroelectricity.html Clean Energy Council. (2017). Queensland leadership to spark new electricity supply and lower prices. Retrieved from Clean Energy Council: https://www.cleanenergycouncil.org.au/news/2017/June/queensland-renewable-reverse- auction-support.html CS Energy. (2017). Electricity generation at Wivenhoe Power Station. Retrieved from CS Energy : https://www.csenergy.com.au/ArticleDocuments/191/Electricity%20generation%20at%20Wiv enhoe%20Power%20Station%20-%2030%20Oct%202016.pdf.aspx CS Energy. (2017). WIVENHOE POWER STATION. Retrieved from CS Energy: https://www.csenergy.com.au/what-we-do/generating-energy/wivenhoe-power-station de Rooij, D. (2015). Base Load and Peak Load: understanding both concepts. Retrieved from SINO Voltaics : http://sinovoltaics.com/learning-center/basics/base-load-peak-load/ Electropaedia. (2005). Hydroelectric Power . Retrieved from Electropaedia: https://www.mpoweruk.com/hydro_power.htm Energy Storage Association. (2018). Pumped Hydroelectric Storage . Retrieved from energystorage.org: http://energystorage.org/energy-storage/technologies/pumped- hydroelectric-storage Hydro-Québec. (2018). Turbines. Retrieved from Hydro-Québec: http://www.hydroquebec.com/learning/hydroelectricite/types-turbines.html International Energy Agency. (2017). Renewables 2017. Retrieved from IEA: https://www.iea.org/publications/renewables2017/ IRENA. (2012). Hydropower. Retrieved from IRENA.org: https://www.irena.org/documentdownloads/publications/re_technologies_cost_analysis- hydropower.pdf Jones-Albertus, B. (2017). Confronting the Duck Curve: How to Address Over-Generation of Solar Energy. Retrieved from U.S. Department of Energy: OFFICE of ENERGY EFFICIENCY & RENEWABLE ENERGY: https://www.energy.gov/eere/articles/confronting-duck-curve-how- address-over-generation-solar-energy Knapp, D. W. (2017). Renewable Energy Technologies Part 4: HydroPower. Munich, Bavaria , Germany. Retrieved from Renewable Energy Technologies. Kougias, I. (2017). Pumped hydroelectric storage utilization assessment: Forerunner of renewable energy integration or Trojan horse? Ispra, Italy: ScienceDirect. Mechanical Booster. (2018). Francis Turbine Working Principle, Main Parts, Diagram and Application. Retrieved from Mechanical Booster: http://www.mechanicalbooster.com/2018/01/francis-turbine.html

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National Hydropower Association . (2012). Challenges and Opportunities For New Pumped Storage Development. Retrieved from hydro.org: https://www.hydro.org/wp- content/uploads/2017/08/NHA_PumpedStorage_071212b1.pdf QLD Government. (2018). Energy. Retrieved from Department of Environment and Science: https://www.des.qld.gov.au/science/research/sectors/energy/ QLD Government. (2018). Powering Queensland Plan: an integrated energy strategy for the state. Retrieved from Department of Natural Resources, Mines and Energy: https://www.dnrme.qld.gov.au/energy/initiatives/powering-queensland Queensland Government. (1984). Wivenhoe Power Station. Retrieved from Queensland Floods Commission of Inquiry: http://www.floodcommission.qld.gov.au/__data/assets/file/0007/7792/Tarong_Energy_Appen dix_11.PDF Queensland Government. (2018). Electricity Generation Map of Queensland. Retrieved from Business Queensland: https://maps.dnrm.qld.gov.au/electricity-generation-map/ Queensland Government. (2018). Powering Queensland Plan: an integrated energy strategy for the state. Retrieved from https://www.dnrme.qld.gov.au/energy/initiatives/powering-queensland Renewables First . (2015). Kaplan Turbines. Retrieved from Renewables First : http://www.renewablesfirst.co.uk/hydropower/hydropower-learning-centre/kaplan-turbines/ Renewables First. (2015). Pelton and Turgo Turbines. Retrieved from Renewables First: http://www.renewablesfirst.co.uk/hydropower/hydropower-learning-centre/pelton-and-turgo- turbines/ SEQ Water. (2010). Wivenhoe Power Station . Retrieved from SEQ Water: http://www.seqwater.com.au/public/source-store-treat-supply/hydro-electric-power Thapar, O. D. (2015). Chapter 3: HYDRAULIC TURBINE CLASSIFICATION AND SELECTION. Retrieved from MODERN HYDROELECTRIC ENGINEERING PRACTICE IN INDIA: https://www.iitr.ac.in/departments/AH/uploads/File/Modern_Hydroelectric_Engineering_Prac tice_Prof_OD_Thapar/Volume_I/Chapter- 3_Hydraulic_Turbine_Classification_and_Selection.pdf Voith. (2017). Reversible pump turbines, Ternary sets and Motor-generators. Retrieved from Pumped storage machines: http://voith.com/ca-en/7_06_Broschuere-Pumped-storage.pdf World Energy Council . (2016). World Energy Resources: Hydropower. Retrieved from World Energy Council : https://www.worldenergy.org/wp- content/uploads/2017/03/WEResources_Hydropower_2016.pdf World Nuclear Association. (2011). Comparison of Lifecycle Greenhouse Gas Emissions of Various Electricity Generation Sources . Retrieved from world-nuclear.org: http://www.world- nuclear.org/uploadedFiles/org/WNA/Publications/Working_Group_Reports/comparison_of_li fecycle.pdf

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Appendices Appendix A – QLD Electricity Grid Raw Data

The table below gives a sample of the raw data supplied by the AEMO for the QLD electrical grid in 2017.

Date Time Demand (MW) Price ($/MWh) 1/01/2017 0:30:00 6462 186.25 1/01/2017 1:00:00 6353 83.75 1/01/2017 1:30:00 6261 64.91 1/01/2017 2:00:00 6170 53.33 1/01/2017 2:30:00 6150 64.03 1/01/2017 3:00:00 6039 57.5 1/01/2017 3:30:00 5960 52.02 1/01/2017 4:00:00 5894 54.35 1/01/2017 4:30:00 5875 59.63 1/01/2017 5:00:00 5835 57.64 1/01/2017 5:30:00 5830 55.91 1/01/2017 6:00:00 5773 47.76 1/01/2017 6:30:00 5848 47.99 1/01/2017 7:00:00 5929 47.15 1/01/2017 7:30:00 6054 46.08 1/01/2017 8:00:00 6134 46.83 1/01/2017 8:30:00 6265 48.91 1/01/2017 9:00:00 6486 54.32 1/01/2017 9:30:00 6610 60.06 1/01/2017 10:00:00 6770 57.55 1/01/2017 10:30:00 6917 79.89 1/01/2017 11:00:00 6993 292.05 1/01/2017 11:30:00 7047 99.72 1/01/2017 12:00:00 7180 214.18 1/01/2017 12:30:00 7281 298.82 1/01/2017 13:00:00 7329 98.5 1/01/2017 13:30:00 7440 82.33 1/01/2017 14:00:00 7530 104.05 1/01/2017 14:30:00 7620 108.77 1/01/2017 15:00:00 7681 119.94 1/01/2017 15:30:00 7801 101.09 1/01/2017 16:00:00 7898 185.32 1/01/2017 16:30:00 7841 303.85 1/01/2017 17:00:00 7997 112.73 1/01/2017 17:30:00 8042 114.06 1/01/2017 18:00:00 7934 291.35 1/01/2017 18:30:00 7904 91.54 1/01/2017 19:00:00 7975 111.76 1/01/2017 19:30:00 8031 76.03 1/01/2017 20:00:00 7981 86.72 1/01/2017 20:30:00 7883 97.03 1/01/2017 21:00:00 7687 61.69 1/01/2017 21:30:00 7568 76.11 1/01/2017 22:00:00 7344 56.34 1/01/2017 22:30:00 7154 66.53 1/01/2017 23:00:00 7066 69.23 1/01/2017 23:30:00 6764 62.71 2/01/2017 0:00:00 6446 61.04 2/01/2017 0:30:00 6288 61.07 2/01/2017 1:00:00 6202 52.95 2/01/2017 1:30:00 6066 46.82 2/01/2017 2:00:00 6004 43.85 2/01/2017 2:30:00 5965 52.49 2/01/2017 3:00:00 5898 48.38 … … … … Raw Data sourced from AEMO FAA-MECH4500 Page 33 of 47

Appendix B – QLD Electricity Grid Average Data 2017

Time of Day Average Price ($/MWh) Average of Demand (MW) 0:00:00 73.27 5747 0:30:00 69.64 5576 1:00:00 72.91 5450 1:30:00 64.47 5334 2:00:00 64.44 5262 2:30:00 61.84 5230 3:00:00 60.75 5210 3:30:00 59.13 5198 4:00:00 57.72 5198 4:30:00 62.60 5250 5:00:00 62.79 5310 5:30:00 67.20 5460 6:00:00 69.92 5611 6:30:00 82.08 5867 7:00:00 127.30 6096 7:30:00 87.16 6344 8:00:00 88.24 6368 8:30:00 87.32 6353 9:00:00 88.33 6315 9:30:00 86.87 6288 10:00:00 82.09 6237 10:30:00 83.28 6209 11:00:00 98.41 6189 11:30:00 82.81 6176 12:00:00 90.11 6198 12:30:00 91.74 6217 13:00:00 90.73 6255 13:30:00 100.01 6305 14:00:00 95.59 6368 14:30:00 96.33 6445 15:00:00 109.58 6516 15:30:00 123.67 6613 16:00:00 150.23 6748 16:30:00 237.21 6893 17:00:00 315.54 7053 17:30:00 234.33 7171 18:00:00 146.93 7245 18:30:00 155.75 7285 19:00:00 175.00 7342 19:30:00 127.27 7245 20:00:00 104.07 7153 20:30:00 103.33 7052 21:00:00 84.82 6849 21:30:00 81.41 6692 22:00:00 73.28 6488 22:30:00 89.40 6336 23:00:00 109.40 6242 23:30:00 86.09 6043 Raw Data sourced from AEMO

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Appendix C: QLD Wholesale Price Day by Day

The table below shows a sample of the data used in predicting the annual return of Unit 3.

Date 00:00 00:30 01:00 01:30 02:00 02:30 03:00 03:30 04:00 … 1/01/2017 80.31 186.25 83.75 64.91 53.33 64.03 57.5 52.02 54.35 2/01/2017 61.04 61.07 52.95 46.82 43.85 52.49 48.38 50.22 45.19 3/01/2017 65.59 45.78 47.91 45.04 46.92 44.6 46.72 43.27 43.22 4/01/2017 58.86 48 43.16 41.04 42.97 46.02 52.4 60.78 59.49 5/01/2017 58.14 51.63 43.9 44.41 43.83 44.58 42.43 41.33 42.6 6/01/2017 40.8 42.58 38.76 44.37 44.41 43.88 40.51 41.85 45.49 7/01/2017 54.6 47.5 39.87 42.54 41.85 53.14 45.38 47.64 44.55 8/01/2017 46.15 43.42 40.48 39.82 41.59 40.48 38.57 33.64 34.29 9/01/2017 42.65 42.23 36.54 38.88 36.7 33.11 28.48 41.52 35.81 10/01/2017 51.22 50.5 47.85 47.34 47.51 47.99 47.02 47.56 46.39 11/01/2017 46.81 50.85 44.33 37.2 35.98 32.05 25.73 38.28 35.38 12/01/2017 49.78 53.22 51.84 41.93 40.48 38.65 37.21 37.68 37.88 13/01/2017 44.68 50.97 51.75 48.61 45.94 45.68 43.41 48.79 47.05 … 14/01/2017 47.65 132.73 84.01 75.51 52.43 56.38 53.72 46.25 50.43 15/01/2017 101.13 77.24 86.92 57.65 59.37 61.06 60.63 61.38 62.36 16/01/2017 47.62 47.39 46.44 47.23 46.29 47.73 52.27 46.25 48.51 17/01/2017 53.59 63.1 64.39 59.82 58.35 69.12 77.48 83.53 85.46 18/01/2017 64.76 64.76 61.05 61.03 67.05 65.01 59.91 59.35 59.93 19/01/2017 49.83 52.23 60.97 60.62 55.57 48.73 48.81 48.37 48.1 20/01/2017 44.97 48.98 51.98 56.04 47.87 46.05 45.02 44.53 44.56 21/01/2017 53.5 269.16 56.77 53.3 45.7 44.28 43.23 41.19 40.31 22/01/2017 47.33 40.02 47.59 42.44 37.26 40.46 37.45 36.98 34.97 23/01/2017 71.68 65.25 62.62 61.71 59.69 56.04 47.77 54.48 55.52 24/01/2017 44.85 44.1 45.1 49.15 43.85 41.45 41.92 40.49 41.18 25/01/2017 45.02 48.39 45.75 46.24 46.28 45.29 43.87 43.95 43.86 26/01/2017 50.83 49.6 47.92 46.17 47.76 45.79 45.62 44.49 45.63 … … … Raw Data sourced from AEMO

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Appendix D: Approximate Relationship Between Price and Demand (QLD, 2017)

1000

900

800

700

600

500

400 Price ($/MWh) Price 300 y = 0.0769x - 376.88 200

100

0 4000 5000 6000 7000 8000 9000 10000 Demand (MW)

Raw data sourced from AEMO

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Appendix E: Expected Return Python Code Script:

Output:

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Appendix F: Queensland Generating Capacity by Energy Source

Source Installed Capacity (MW) % of total Coal 8127.9 59.9 Gas 4432.2 32.6 Bagasse 394.4 2.9 Hydro 168.4 1.2 Solar 112.0 0.8 Waste Coal Mine Gas 108.9 0.8 Gas/diesel 80.2 0.6 Diesel 45.6 0.3 Wood waste 44.8 0.3 Landfill Gas 22.0 0.2 Coffee grounds & sawdust 16.0 0.1 Wind 12.5 0.1 Sewage 12.1 0.1 Agricultural Waste 1.5 0.0 organic wet-waste 1.3 0.0 Geothermal 0.1 0.0 Grand Total 13579.7 100.0 (Queensland Government, 2018)

Appendix G: Queensland Generating Capacity

(World Nuclear Association, 2011)

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Appendix H: Expected Emissions Example Calculation

Generating at full capacity for 6 hours each day gives a total energy output of 1710 MWh /day.

Producing from through hydroelectric generation a total of:

44460 kg⸱CO2e/d

While offsetting:

853290 kg⸱CO2e/d

From the production of electricity through the burning of natural gas.

Assuming 70% efficiency, during pumping the facility consumes a total of 2443 MWh/d.

When 100% of Energy for Pumping comes from Coal:

From coal fired power stations pumping will produce a total of:

2169384 kg⸱CO2e/d

Summing to get net daily CO2e output:

44460 – 853290 + 2169384 = 1360554 kg⸱CO2e/d

When 100% of Energy for Pumping comes from Solar PV:

From solar PV pumping will produce a total of:

207655 kg⸱CO2e/d

Summing to get net daily CO2e output:

44460 – 853290 + 207655 = -601175 kg⸱CO2e/d

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Appendix I: CAPEX Sensitivity Data

Variation from Baseline Input -20% -10% 0% 10% 20% 30% 40% WPS Total Specific Cost - 711 791 870 949 1028 - Cost of Reservoir - 787 791 795 799 803 806 Cost of Tunnels 749 770 791 812 833 - - Cost of Powerhouse/Shafts 749 770 791 812 833 853 - Cost of Powerhouse - 763 791 819 848 - - Equipment Cost of 781 786 791 796 801 - - Engineering/Management

Appendix J: Annual Return Sensitivity Data

Variation from Baseline Input -16.67% -15% -10% -8.33% -5% 0% 5% 8.33% 10% 15% 16.67% 20% 25% Hours Required for - - - - - 22.55 - 21.94 - - 21.33 - 20.72 Pumping Operational 28.21 - - 25.49 - 22.55 - 19.41 - - - - - Hours Per Day Cost Correction - 28.79 26.71 - 24.63 22.55 20.47 - 18.39 16.31 - - - Factor Efficiency - - - - 16.78 22.55 27.63 - 32.15 36.18 - - -

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Appendix K: Modified Script for Sensitivity Analysis

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