energies

Article Wind Energy Potential of Gaza Using Small Wind Turbines: A Feasibility Study

Mohamed Elnaggar 1, Ezzaldeen Edwan 1 and Matthias Ritter 2,* ID 1 Department of Engineering, Palestine Technical College, College street, 920, Deir El-Balah, Gaza Strip, Palestine; [email protected] (M.E.); [email protected] (E.E.) 2 Department of Agricultural Economics, Humboldt-Universität zu Berlin, Philippstr. 13, 10115 Berlin, Germany * Correspondence: [email protected]; Tel.: +49-30-2093-46851

Academic Editor: Frede Blaabjerg Received: 20 July 2017; Accepted: 14 August 2017; Published: 18 August 2017

Abstract: In this paper, we conduct a feasibility study of the wind energy potential in Gaza, which suffers from a severe shortage of energy supplies. Our calculated energy harvested from the wind is based on data for a typical meteorological year, which are fed into a small of 5 kW power rating installable on the roof of residential buildings. The expected annual energy output at a height of 10 m amounts to 2695 kWh, but it can be increased by 35–125% at higher altitudes between 20 m and 70 m. The results also depict the great potential of wind energy to complement other renewable resources such as solar energy: the harvested energy of a wind system constitutes to up to 84% of the annual output of an equivalent power rating photovoltaic system and even outperforms the solar energy in the winter months. We also show that one wind turbine and one comparable photovoltaic system together could provide enough energy for 3.7 households. Hence, a combination of wind and solar energy could stabilize the decentralized energy production in Gaza. This is very important in a region where people seek to reach energy self-sufficient buildings due to the severe electricity shortage in the local grid.

Keywords: ; wind energy; small wind turbine; Gaza; Palestine

1. Introduction During the last decade, renewable energies have witnessed a great deal of importance worldwide: renewable power capacity doubled from 1010 GW in 2007 to 2017 GW in 2016 with installed wind energy capacity increasing from 95 GW to 487 GW and installed solar capacity increasing from 7.8 GW to 303 GW in this period [1,2]. Currently, Gaza is also witnessing a spread in the use of photovoltaic power systems due to the sunny weather conditions, but the use of systems is currently rare in the Gaza Strip [3,4]. The Gaza Strip has an increasing demand for electrical power with an increasing shortage of power supplies. The Gaza Strip is a coastal strip and it is part of the state of Palestine located on the eastern coast of the Mediterranean Sea. Gaza constitutes the Southern Palestinian governorates, which also includes the West Bank as northern governorates. The Gaza Strip is 41 km long, and from six to twelve kilometers wide, with a total area of 365 square kilometers and more than 1.85 million inhabitants, Gaza is among the regions with the highest population density in the world. In 2009, Gaza’s total demand for power, according to estimates by the Gaza Electricity Distribution Co. (Gaza, Palestine), is 244 MW [5]. However, even when the only power plant is running, Gaza obtains, at most, only 198 MW from all power supplies. The working power plant contributes about 60 MW [5]. Another 121 MW are brought in from Israel (but only if all 10 feeding lines are in good order), and Egypt powers the Southern Gaza city of Rafah with another 17 MW. Therefore, the deficit

Energies 2017, 10, 1229; doi:10.3390/en10081229 www.mdpi.com/journal/energies Energies 2017, 10, 1229 2 of 13 under the best circumstances is 18%. According to a UN report from July 2017, Gaza’s energy crisis has worsened: the electricity demand in 2017 amounts to 450 MW, whereas only 120–142 MW are supplied due to a halt of the power plant, leading to a deficit of more than 68%. Under different growth and energy supply scenarios, energy deficit projections for 2020 range between 29% and 75% [6]. Adding to the complexity, the “grid” is not actually integrated, meaning that power from Egypt, Israel, and the power plant cannot be diverted within Gaza to make up for losses in another part. That means, for example, if the power plant stops working, electricity from Egypt cannot be rerouted to Gaza City [5]. The grid has an average blackout schedule of at least 12 h daily. With the current grid infrastructure, it is impossible to feed it directly with renewable electricity generated by individuals using solar or other renewable sources. Therefore, the typical solution would be to develop self-sufficient energy supply systems. This solution can be realized through a hybrid power system composed of solar panels and/or wind turbines, battery banks, and inverters. Wind energy is one of the most promising clean energy sources that developing and developed countries are seeking to harvest to reduce dependence on non-renewable sources of energy [7,8]. Despite its current low use, wind energy has a promising future in Gaza for the following reasons:

• Solar energy is not enough alone to supply the needed energy, especially during the night and in the short gray days of winter. Moreover, according to local weather statistics, wind speed increases in winter, so that solar energy and wind energy can complement each other.

• Photovoltaic modules are not cheap, roughly 1.2 USD $/Wp, and their manufacturing technology is complicated (Wp denotes peak power and it is used in photovoltaic systems to describe the power rating of installed solar panels. The subscript p is to differentiate it from measured power). Small wind turbines, in contrast, have a rather simple manufacturing technology and can be completely manufactured in Gaza. Therefore, wind turbines could have lower costs than solar panels in terms of $/W if manufactured locally. Moreover, manufacturing itself contributes to the local economy. • Due to the high population density, Gaza city is full of high-rise residential buildings. The majority of the buildings are restricted to five floors as regulated by the local municipality. Therefore, the majority of the city areas will access unobstructed wind at nearly the same height since the land is flat. The height of the buildings of around 50 m and the installation of the turbine on a metal pole allow for wind turbines installed at higher altitudes. All of the roofs in Gaza are flat and, therefore, the installation is possible and technically stable due to the concrete building structure. Although the wind speed is not that high at low altitudes, we expect it will be more efficient at higher altitudes. This issue will be investigated deeply in our research. • Wind turbines require less land area, which is restricted to the metal pole and, therefore, they fit the small land area of the Gaza Strip.

In this paper, the possibility of using small wind turbines in Gaza to harvest wind energy is investigated theoretically and by simulation using TRNSYS software through finding wind speed, maximum power produced by the wind turbine, and the actual turbine power. We base our analysis on the specifications of the proposed WTT 5000S (small) wind turbine. The goal is to explore the use of wind energy in dense urban areas and to evaluate the performance of a small wind turbine at different altitudes on top of residential buildings based on its output power and the total generated energy. Moreover, the potential to complement solar energy and to meet the household energy demand is assessed.

2. Climatic Data Gaza is located on the western edge of the Asian continent and the eastern extremity of the Mediterranean Sea at 31.5◦ N latitude and 34.47◦ E longitude [9]. Due to its location as a narrow strip adjacent to sea, it is exposed to stable wind patterns during the whole year, as far as small wind-energy Energies 2017, 10, 1229 3 of 13 Energies 2017, 10, 1229 3 of 13

energy systems are concerned [10]. Moreover, this location, as a residential area, makes it a good systemscandidateEnergies are for2017 concerned exploiting, 10, 1229 [10 wind]. Moreover, energy thisfor home location, usage as ato residential solve energy area, shortages. makes it a good candidate3 of 13 for exploitingThe climate wind energy database for home is constructed usage to solve based energy on shortages. Meteonorm software (Meteotest, Bern, Switzerland,Theenergy climate systems meteonorm) database are concerned isfor constructed the [10]. period Moreover, based from on1991 this Meteonorm lotocation, 2010. asMeteonorm software a residential (Meteotest, provides area, makes Bern,hourly it Switzerland,a gooddata for a meteonorm)‘typicalcandidate meteorological for for theexploiting period year’ windfrom based energy 1991 on for nearby to home 2010. usageweather Meteonorm to solve stations energy provides and shortages. stochastic hourly weather data for generators a ‘typical The climate database is constructed based on Meteonorm software (Meteotest, Bern, meteorological(details can be found year’ based in [11]). on Since nearby there weather is no stationstypical meteorological and stochastic weatheryear data generators for Gaza, specifically, (details can Switzerland, meteonorm) for the period from 1991 to 2010. Meteonorm provides hourly data for a bewe found will rely in [ 11on]). Ashdod Since there climatic is no data typical due meteorological to the similarity year between data for these Gaza, two specifically, cities. Ashdod we will is only rely ‘typical meteorological year’ based on nearby weather stations and stochastic weather generators 30 km away from Gaza, located also in the coastal plain of the Mediterranean Sea at the same on Ashdod(details climaticcan be found data in due [11]). to Since thesimilarity there is no betweentypical meteorological these two cities. year data Ashdod for Gaza, is only specifically, 30 km away fromelevation,we Gaza, will so locatedrely they on have Ashdod also comparable in climatic the coastal data climatic plaindue to conditions. of the the similarity Mediterranean This between makes Seathese it a atreasonable two the cities. same Ashdod candidate elevation, is only for so Gaza they havewind30 comparable data km inaway other climaticfrom studies, Gaza, conditions. as located well (e.g., also This [9]).in makes the coastal it a reasonable plain of the candidate Mediterranean for Gaza Sea wind at the data same in other studies,elevation,Figure as well 1 sodepicts (e.g., they have [ 9the]). comparablehistogram climaticof wind conditions. speed data This at makes 10 m itheight a reasonable for a typicalcandidate meteorological for Gaza year.Figurewind It can data1 be depicts innoticed other the studies, that histogram the as windwell of(e.g., speed wind [9]). can speed reach data above at 10 13 m m/s height for fora few a typical hours meteorologicalin certain days. year.In Figure It canFigure 2, bethe noticed 1wind depicts situation that the thehistogram windis summarized speedof wind can speed th reachrough data above ata wind10 13m height m/srose. forMost for a afew typicalof the hours times,meteorological in certainwind comes days. Infrom Figureyear. the2 Itsea,, thecan this windbe noticed means situation that from the is between summarizedwind speed south-so can through reachuthwest above a wind and13 m/s rose. north-northwest. for Most a few of hours the times,in Most certain windof days.the comes wind In Figure 2, the wind situation is summarized through a wind rose. Most of the times, wind comes fromspeeds the lie sea, between this means 2 and from 6 m/s. between Figure south-southwest 3 shows the monthly and north-northwest. means of wind Most speed. of theIt becomes wind speeds clear from the sea, this means from between south-southwest and north-northwest. Most of the wind that the average monthly speed mostly exceeds 4 m/s, except for October and November. The highest lie betweenspeeds lie 2 and between 6 m/s. 2 and Figure 6 m/s.3 shows Figure the3 shows monthly the monthly means ofmeans wind of speed.wind sp Iteed. becomes It becomes clear clear that the average wind speeds are achieved in February and September. averagethat monthly the average speed monthly mostly speed exceeds mostly 4 exceeds m/s, except 4 m/s, forexcept October for October and November. and November. The The highest highest average windaverage speeds wind are achieved speeds are in achieved February in andFebruary September. and September.

Figure 1. Histogram of wind speeds and the fitted Weibull distribution function (red) for the typical FigureFigure 1.1. HistogramHistogram ofof windwind speedsspeeds andand thethe fittedfitted WeibullWeibull distributiondistribution functionfunction (red)(red) forfor thethe typicaltypical meteorological year. meteorologicalmeteorological year.year.

Figure 2. Wind rose for the typical meteorological year.

Figure 2. Wind rose forfor thethe typicaltypical meteorologicalmeteorological year.year.

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4.6 4.4 4.2 4 3.8

Wind speed (m/s) Wind speed 3.6 3.4

FigureFigure 3. 3. MonthlyMonthly average average wind wind speed speed in in a atypical typical meteorological meteorological year. year.

3.3. Methodology Methodology

3.1.3.1. Wind Wind Harvesting Harvesting System System Basics Basics TheThe wind wind turbine turbine used used for for harves harvestingting wind wind energy energy needs needs to to be be mounted mounted at at a a relatively relatively large large heightheight above above the the ground ground to to avoid avoid local local obstacles. obstacles. To To overcome overcome the the intermittency intermittency of of wind wind energy, energy, harvestedharvested energy energy is is stored stored in in battery battery banks banks and and a a DC/AC DC/AC inverter inverter is is used used to to convert convert it it to to AC AC electrical electrical power.power. Home Home wind wind turbines turbines consist consist of of a arotor, rotor, a a generator generator mounted mounted on on a aframe, frame, and and (usually) (usually) a atail. tail. ThroughThrough the the spinning spinning of of turbine turbine blades, blades, the the rotor rotor capt capturesures the the kinetic kinetic energy energy of of the the wind wind and and converts converts itit into into rotary rotary motion motion to to drive drive the the generator. generator. The The rotor rotor can can have have two, two, three, three, or or more more blades, blades, but but the the mostmost common common rotors rotors have three blades. TheThe inputinput powerpower thatthat is is fed fed to to the the turbine turbine is is proportional proportional to to its itsswept swept area, area, which which is proportional is proportional to the to blade the blad diameter.e diameter. Details Details about theabout structure the structure of wind of turbines wind turbinescan be found can be in found [12]. in [12]. 3.2. Theoretical Analysis: Wind Turbine Coefficient and Power 3.2. Theoretical Analysis: Wind Turbine Coefficient and Power The efficiency of the wind turbine is referred to as power coefficient C , which is a measure that is The efficiency of the wind turbine is referred to as power coefficient p , which is a measure that often used by the . The efficiency is a ratio of the actual electric power produced is often used by the wind power industry. The efficiency is a ratio of the actual electric power by a wind turbine divided by the total wind power flowing into the turbine blades at a specific wind produced by a wind turbine divided by the total wind power flowing into the turbine blades at a speed [13]: specific wind speed [13]: Actual Electrical Power Produced Pout Cp = = (1) ActualWindElectrical PowerPower into TurbineProduced P = = in (1) Wind Power into Turbine The wind power entering the turbine blades Pin is calculated from the following equation:

The wind power entering the turbine blades is calculated from the following equation: 1 3 Pin =1 ρAv (2) = 2 (2) 2 where ρ is the air density (equal to 1.225 kg/m3), A is the swept area, and v is the magnitude of the where is the air density (equal to 1.225 kg/m3), is the swept area, and is the magnitude of the horizontal velocity [14]. horizontal velocity [14]. The electrical power output P can be obtained through the efficiency of the turbine according The electrical power output out can be obtained through the efficiency of the turbine according to Equation (1) [15,16]: to Equation (1) [15,16]: 1 3 Pout = CpPin = ρACpv (3) 12 = = (3) The power coefficient Cp can also be calculated from2 the following equation [13]:

The power coefficient can also be calculated from the following equation [13]: Cp = ηbηmηe (4) = (4) where ηb is the blade aerodynamic efficiency, ηm is the mechanical efficiency, and ηe is the electrical where is the blade aerodynamic efficiency, is the mechanical efficiency, and is the electrical efficiency. Power flow in a typical wind turbine can be found in [13]. efficiency. Power flow in a typical wind turbine can be found in [13].

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The Betz limit shows the maximum possible energy that may be derived by means of an infinitely thin rotor from a fluid flowing at a certain speed [17]. The power coefficient Cp has a maximum value of Cp,max = 16/27 = 0.593 [18]. The Betz limit describes the maximum amount of energy a turbine can theoretically extract from the wind [14]:

1 P = · 0.593 · ρAv3 (5) out,max 2

3.3. Wind Turbine Specification The wind turbine WTT 5000S (small) produced by WTT GmbH (Reichling, Germany) and applied in this study was selected based on different criteria:

1. Output power: It fits home use as the harvested energy is in the range of the average consumption of a household; 2. Price (its price is competitive compared with others); 3. Operation speed (fits low speed as starts from 2.5 m/s until 15 m/s); 4. Efficiency is 30.5% which is relatively good; and 5. Weight and size are suitable for home installations.

Table1 shows the specifications of the WTT 5000S (small) wind turbine [ 19]. According to the manufacturer, it is an extremely quiet horizontal wind turbine, low speed, movable tail fin, slip rings, aluminum housing, permanent magnet direct drive, and it comes with a high-quality . The wind turbine is designed by the manufacturer to operate at a power of about 4 kW. If a larger inverter with a power of 5.5–6 kW is used and tail fin weights (100–300 g) are added, it reaches 4.5 kW–5 kW. As an approximation for the power coefficient which, in general, depends on the wind speed, we use the turbine’s total efficiency of 0.305 (a more sophisticated simulation approach is described in the next section). When calculating Pout and Pout,max for this turbine, we will cut the power at the maximum of 5 kW. Even for higher wind speeds, the turbine power will then not increase.

Table 1. Wind turbine specification.

Wind Turbine Type WTT 5000S (Small) Blade diameter 3.8 m Rated speed 450 rpm Power at 12.5 m/s 3800 W Power at 15.0 m/s 5000 W Start wind speed 2.5 m/s Total efficiency 30.5% Total weight of the system approx. 74 kg

The turbine itself costs around $4000 USD including shipping costs. Moreover, a charging controller and a DC/AC inverter for together about $2000 USD and a battery bank for about $2000 USD are necessary since the generated electricity cannot be fed into the local grid during blackouts. The costs for a tower and the installation at higher heights amount to approximately $1000 USD. Hence, total costs of around $9000 USD apply. When combining this turbine with other turbines or photovoltaic systems, the costs do not increase linearly.

3.4. Simulation Model Using TRNSYS Simulation models are useful tools for predicting system behavior without the need for constructing the system as a hardware. TRNSYS is a transient system simulation program with a modular structure that was designed to solve complex energy systems problems by breaking the problem down into a series of smaller components known as “types” [20,21]. It is one of the most Energies 2017, 10, 1229 6 of 13 reliable modeling and simulation programs oriented to deal with complicated energy systems [22]. The core TRNSYS components of the model are presented in Table2 and Figure4. Figure4 shows the TRANSYS interface of the model. It depends on a certain number of interconnectedEnergies 2017, components10, 1229 and each component has an input and an output. The description6 of of13 each componentFigure is shown 4 shows in Table the TRANSYS2. It should interface be noted of herethe model. that the It core depends component on a certain model number in the systemof is theinterconnected wind turbine components defined as Type90and each where component we configured has an input the and parameters an output. The of thisdescription component of each model accordingcomponent to the is specificationsshown in Table of2. It WTT should 5000S be noted small here wind that turbine.the core component Type109-TMY2 model in is the the system model for “Weatheris theData wind Readingturbine defined and Processing” as Type90 where which we consists configured of windthe parameters speed, wind of this direction, component and model ambient temperature.according The to the online_T65 specifications model of WTT creates 5000S plots small of wind wind speed,turbine. resulting Type109-TMY2 power is in the daily model and for hourly basis.“Weather The functionality Data Reading of Type25a and Processing” and Type25b/Daily which consists and of wind Total speed, Results wind models direction, are shownand ambient in Table 2. temperature. The online_T65 model creates plots of wind speed, resulting power in daily and hourly Opposite to the approaches in the previous section, the size of the power coefficient Cp in the TRANSYS basis. The functionality of Type25a and Type25b/Daily and Total Results models are shown in Table 2. model depends on the wind speed. Opposite to the approaches in the previous section, the size of the power coefficient in the TRANSYS model depends on the wind speed. Table 2. Explanation of TRNSYS model components following [23].

Table 2. Explanation of TRNSYS model components following [23]. Name Component type Description Name Component type Description Weather Data Reading and Processing.Typical WeatherWeather data Type109-TMY2 Weather Data Reading and Processing. Type109-TMY2 Meteorological Year (TMY) data data Typical Meteorological Year (TMY) data WindWind EnergyEnergy Conversion System System (WECS). (WECS). Power Power versus versus Wind Wind turbine Type90Type90 windwind speedspeed data are are read read in in a afile. file. The The impact impact of air of density air density turbine changeschanges andand wind speed speed increase increase with with height height are aremodeled. modeled. Online Online Plotter online_T65online_T65 Output/Online Output/Online Plotter/Online Plotter/Online Plotter Plotter With With File. File. Plotter Type25aType25a and and Type25b/Daily Type25b/ ItIt cancan printprint with with a a time time step step that that is different is different from from the the PrinterPrinter Dailyand and Total Total results results simulationsimulation time time step. step.

FigureFigure 4. 4.System System model model designeddesigned using using TRNSYS TRNSYS [23]. [23 ].

3.5. Extrapolation3.5. Extrapolation of Wind of Wind Speed Speed to to Different Different Heights Heights To calculateTo calculate the the effect effect of theof the height, height, the the wind wind speedsspeeds are are extrapolated extrapolated to todifferent different heights heights using using the powerthe power law law (e.g., (e.g., [14 ,[14,24]):24]):  z α = (6) v = vr (6) zr where denotes the wind speed extrapolated to height and the wind speed at reference height where v denotes the wind speed extrapolated to height z and vr the wind speed at reference height (10 m in our case). describes the stability of the atmosphere and is often assumed to be 1/7. zr (10 m in our case). α describes the stability of the atmosphere and is often assumed to be 1/7. According to Brown, Katz, and Murphy, the power law provides a ‘reasonable first approximation

Energies 2017, 10, 1229 7 of 13

AccordingEnergies 2017 to Brown,, 10, 1229 Katz, and Murphy, the power law provides a ‘reasonable first approximation7 of 13 to the change of wind speed with height under most meteorological conditions’ [24] (p. 1190). If data on toEnergies the change 2017, 10 , of1229 wind speed with height under most meteorological conditions’ [24] (p. 1190). If7 data of 13 surface roughness and atmospheric stability were available, a better approximation could be achieved on surface roughness and atmospheric stability were available, a better approximation could be usingto the the logchange wind of profilewind speed (e.g., with [25 ,height26]). under most meteorological conditions’ [24] (p. 1190). If data achieved using the log wind profile (e.g., [25,26]). on surface roughness and atmospheric stability were available, a better approximation could be achieved using the log wind profile (e.g., [25,26]). 4. Results4. Results and and Discussion Discussion = 4.Figure ResultsFigure5 shows and 5 shows Discussion the resultsthe results of the of hourlythe hourly power powerPout at atC p =0.305 0.305over over thethe yearyear basedbased onon thethe wind speedwind depicted speed depicted in Figure in1 Figure. It can 1. beIt can noticed be noticed that thethat maximumthe maximum power power output output ofof 50005000 W was was not Figure 5 shows the results of the hourly power at = 0.305 over the year based on the achievednot achieved due to toodue lowto too wind low wind speeds spee atds the at turbinethe turbine height height of of 10 10 m. m. wind speed depicted in Figure 1. It can be noticed that the maximum power output of 5000 W was not achieved5 due to too low wind speeds at the turbine height of 10 m.

5 4

4 3

3 2 P_out (kW) 2 P_out (kW) 1

1 0 1-Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Aug 1-Sep 1-Oct 1-Nov 1-Dec 0 1-JanFigure 1-Feb 5. Hourly 1-Mar distribution 1-Apr 1-May of power 1-Jun output 1-Jul for 1-Aug the typical 1-Sep meteorological 1-Oct 1-Nov year. 1-Dec Figure 5. Hourly distribution of power output for the typical meteorological year. Figure 5. Hourly distribution of power output for the typical meteorological year. A detailedA detailed visualization visualization of of the the hourlyhourly wind speeds speeds in in February February and and the thecorresponding corresponding power power output is presented in Figure 6. The maximum wind speed was 12.7 m/s on 15 February leading to a output isA presented detailed visualization in Figure6. Theof the maximum hourly wind wind speeds speed in wasFebruary 12.7 and m/s the on corresponding 15 February leading power to a power output of 4340 W. In addition, the daily cycles of wind speed and, hence, power become visible. poweroutput output is presented of 4340 W. in InFigure addition, 6. The themaximum daily cycles wind speed of wind was speed 12.7 m/s and, on hence, 15 February power leading become to visible.a Figure 7 first shows the energy that can be harvested in each month of the year based on the powerFigure output7 first of shows 4340 W. the In energyaddition, that the daily can becycles harvested of wind speed in each and, month hence, ofpower the become year based visible. on the simulations using TRNSYS for the typical meteorological year, denoted . The months of January simulationsFigure using 7 first TRNSYS shows forthe theenergy typical that meteorologicalcan be harvested year,in each denoted month Eof the. The year months based on of the January and July have the highest expected energy yields, 225 kWh and 237 kWh, respectively.sim Since those simulations using TRNSYS for the typical meteorological year, denoted . The months of January andmonths July have are thelocated highest in winter expected and summer, energy this yields, indicates 225 that kWh it is and promising 237 kWh, to harvest respectively. energy in Since Gaza those and July have the highest expected energy yields, 225 kWh and 237 kWh, respectively. Since those monthsthroughout are located the year. in winter For the and whole summer, year, the this total indicates expected that energy it is promising amounts to to 2406 harvest kWh energy from one in Gaza months are located in winter and summer, this indicates that it is promising to harvest energy in Gaza throughoutturbine at the 10 year.m height For for the the whole typical year, meteorological the total expected year. energy amounts to 2406 kWh from one throughout the year. For the whole year, the total expected energy amounts to 2406 kWh from one turbine at 10 m height for the typical meteorological year. turbine5 at 10 m height for the typical meteorological year. 14 5 P_out Wind speed 14 12 4 P_out Wind speed 12 10 4 3 10 8 3 8 6 2 P_out (kW)

6 Wind speed (m/s) 2 4 P_out (kW) 1 4 Wind speed (m/s) 2 1 2 0 0

0 1/2/ 2/2/ 3/2/ 4/2/ 5/2/ 6/2/ 7/2/ 8/2/ 9/2/ 0 10/2/ 11/2/ 12/2/ 13/2/ 14/2/ 15/2/ 16/2/ 17/2/ 18/2/ 19/2/ 20/2/ 21/2/ 22/2/ 23/2/ 24/2/ 25/2/ 26/2/ 27/2/ 28/2/ 1/2/ 2/2/ 3/2/ 4/2/ 5/2/ 6/2/ 7/2/ 8/2/ 9/2/ Figure 6. Hourly wind speed and10/2/ 11/2/ corresponding12/2/ 13/2/ 14/2/ 15/2/ 16/2/ power17/2/ 18/2/ output19/2/ 20/2/ in21/2/ February22/2/ 23/2/ 24/2/ 25/2/ for 26/2/ the27/2/ typical28/2/ meteorological year. FigureFigure 6. 6.Hourly Hourly wind wind speedspeed andand corresponding power power output output in inFebruary February for the for typical the typical

meteorologicalmeteorological year. year.

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E_sim E_out E_out,max E_in 1000 900 800 700 600 500 400 Energy (kWh) 300 200 100 0

Figure 7. Harvested energy for each month of the year. Figure 7. Harvested energy for each month of the year.

Figure7 also depicts the expected monthly energy Ein, Eout,max, and Eout at Cp = 0.305 according Figure 7 also depicts the expected monthly energy , , , and at = 0.305 to the power in Equations (2), (3), and (5), respectively. Not surprisingly, Ein has the highest value since according to the power in Equations (2), (3), and (5), respectively. Not surprisingly, has the highestit describes value the since kinetic it describes energy of the the kinetic wind arrivingenergy of at the turbine.wind arriving It can beat the seen turbine. that the It kinetic can be energy seen thatis lowest the kinetic in the energy months is October lowest in to the December, months whichOctober also to leadsDecember, to the which lowest also power leads outputs to the inlowest these months. The maximum amount that can be harvested theoretically, Eout,max, corresponds to 59.3% of power outputs in these months. The maximum amount that can be harvested theoretically, ,, Ein. Given the efficiency of our turbine to be Cp = 0.305, only 51.4% of Eout,max can be achieved with corresponds to 59.3% of . Given the efficiency of our turbine to be = 0.305, only 51.4% of our turbine, leading to a power output Eout of 2695 kWh for the entire year. This shows that there is , can be achieved with our turbine, leading to a power output of 2695 kWh for the entire year.only aThis slight shows difference that betweenthere is theonly results a slight from difference the TRNSYS between simulations the results and the from calculations the TRNSYS based simulationson Equation and (3). the calculations based on Equation (3). ForFor a moremore detaileddetailed perspective, perspective, the the hourly hourly power power output output and windand wind speeds speeds on the 1ston ofthe February 1st of Februaryare shown are in shown Figure 8in. OnFigure this 8. day On of this the day typical of th meteorologicale typical meteorological year, the peak year, wind the peak speed wind is 6.9 speed m/s isat 6.9 7:00 m/s PM at (19.00)7:00 PM and (19.00) leads and to expected leads to powersexpected of powers 2280 W, of 1350 2280 W, W, 696 1350 W, andW, 696 610 W, W forandP 610in, P Wout ,formax , Pout, and Psim, respectively. It is confirmed that the simulation results lie very close to the theoretical , ,, , and , respectively. It is confirmed that the simulation results lie very close to theresults theoretical of theactual results power of the producedactual power with produced the wind with turbine the typewind (WTT turbine 5000S) type with (WTT an 5000S) overall with turbine an efficiency of Cp = 0.305. overall turbine efficiency of = 0.305. Figure9 shows the different expected powers with respect to wind speed. Generally, an increase Figure 9 shows the different expected powers with respect to wind speed. Generally, an increase of the wind speed leads to an increase of the power output. The available power Pin increases of the wind speed leads to an increase of the power output. The available power increases continuously, whereas Psim, Pout,max, and Pout are bounded by the turbine capacity. continuously, whereas , ,, and are bounded by the turbine capacity.

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P_sim P_out,max P_out P_in Wind speed 3 P_sim P_out,max P_out P_in Wind speed 7 3 7 2.5 6 2.5 6 2 5 2 5 1.5 4 1.5 4

Power (kW) 1 3 Power (kW) 1 3 (m/s) Wind speed

0.5 2 (m/s) Wind speed 0.5 2 0 1 0 0 5 10 15 20 1 0 5 10Hour of the day 15 20 Hour of the day

FigureFigure 8. Hourly8. Hourly power power output output and and wind wind speed speed on on the the 1st 1st of February.of February. Figure 8. Hourly power output and wind speed on the 1st of February. 16 16 14 14 P_sim P_out P_out,max P_in 12 P_sim P_out P_out,max P_in 12 10 10 8 8 6 Power (kW) 6 Power (kW) 4 4 2 2 0 0 02468101214 02468101214Wind speed (m/s) Wind speed (m/s) FigureFigure 9. The9. The relationship relationship of powerof power output output with with wind wind speed. speed. Figure 9. The relationship of power output with wind speed. AllAll the the results results mentioned mentioned before before were were based based on on wind wind speeds speeds of theof the typical typica meteorologicall meteorological year year measuredmeasuredAll the at results aat heighta height mentioned of of 10 10 m m above before above ground. were ground. based If aIf wind aon wind wind turbine turbine speeds is installedis of installed the typica on on top ltop meteorological of of a roof,a roof, however, however, year muchmeasuredmuch larger larger at heightsa heightheights can of can be10 be achieved.m achieved.above ground. To To study study If the a thewind potential potential turbine of increasingofis increasinginstalled height, on height, top the of the winda roof, wind speeds however, speeds are are extrapolatedmuchextrapolated larger heights to differentto different can be heights achieved.heights according according To study to Equationto the Equation potential (6). (6). of increasing height, the wind speeds are extrapolatedFigureFigure 10 to depicts10 different depicts the heightsthe expected expected according wind wind speeds to speeds Equation at a heightat a (6). height of 70 of m 70 for m the for month the month of February of February and the and correspondingtheFigure corresponding 10 powerdepicts output. powerthe expected Comparedoutput. wind Compared to speeds Figure at6to, thea Figureheight maximum of6, 70the windm maximu for speedthe monthm has wind now of speedFebruary increased has and tonow 16.77theincreased corresponding m/s, which to 16.77 leads powerm/s, to which the output. maximum leads Compared to powerthe maximum outputto Figure ofpower 5000 6, theoutput W. maximu of 5000m W.wind speed has now increased to 16.77 m/s, which leads to the maximum power output of 5000 W.

Energies 2017, 10, 1229 10 of 13 Energies 2017, 10, 1229 10 of 13

6 18.00 P_out 70 m Wind speed 70 m 16.00 5 14.00 4 12.00 10.00 3 8.00

P_out (kW) 2 6.00 Wind speed (m/s) 4.00 1 2.00 0 0.00 1/2/ 2/2/ 3/2/ 4/2/ 5/2/ 6/2/ 7/2/ 8/2/ 9/2/ 10/2/ 11/2/ 12/2/ 13/2/ 14/2/ 15/2/ 16/2/ 17/2/ 18/2/ 19/2/ 20/2/ 21/2/ 22/2/ 23/2/ 24/2/ 25/2/ 26/2/ 27/2/ 28/2/ FigureFigure 10. 10. HourlyHourly wind wind speed speed at at height height 70 70 m m and and corresponding corresponding power power output output in in February. February.

Figure 11 shows the resulting monthly expectations for at heights of 20 m, 30 m, 50 m, and Figure 11 shows the resulting monthly expectations for Eout at heights of 20 m, 30 m, 50 m, 70and m 70above m above the ground. the ground. According According to this, to the this, same the turbine same turbine can achieve can achieve a much a higher much energy higher output energy foroutput higher for heights. higher Compared heights. Compared to the energy to the at a energy height atof a10 height m, the of yearly 10 m, energy the yearly output energy increases output by 35%increases for a height by 35% of for20 m, a height by 60% of for 20 30 m, m, by and 60% 97% for fo 30r 50 m, m. and At a 97% height for of 50 70 m. m, At the a expected height of yearly 70 m, energythe expected output yearly corresponds energy outputto 6055 corresponds kWh, which to corresponds 6055 kWh, which to a correspondssurplus of 125% to a surpluscompared of 125%to a heightcompared of 10 to m. a height It should of 10 be m. noted It should that bethe noted installa thattion the of installation a wind turbine of a wind on the turbine roof of on a the residential roof of a buildingresidential requires building a careful requires analysis a careful of safety analysis issues. of safety These issues. safety Theseissues, safety however, issues, will however, be manageable will be consideringmanageable the considering use of a small the use wind of aturbine small windwith a turbine weight withof around a weight 74 kg. of aroundCompared 74 kg.with Compared the costs ofwith a turbine the costs and of its a turbine installation and itsat a installation higher height at a of higher about height $9000 of USD about in $9000total, the USD yearly in total, yield the of yearly 6055 kWhyield at of 70 6055 m brings kWh atin 70more m brings than 9% in of more the thaninitial 9% costs of theper initialyear assuming costs per a year price assuming of $0.14 USD/kWh a price of according$0.14Energies USD/kWh 2017 to, 10 [27]., 1229 according to [27]. 11 of 13 To put these results in perspective, we compare them with the potential of solar energy production700 in Gaza. According to the PVWatts Calculator, an annual photovoltaic energy output of 7196 kWh can be expected from E_outa comparable20 m 5 kW30 photovoltaic m 50 m system70 min a nearby region with similar600 conditions like Gaza. Hence, the harvested annual energy of the considered small wind turbine at a height of 10 m corresponds to 37% of the solar energy or even 84% at a height of 70 m above500 ground. Figure 12 depicts the monthly comparison between the wind energy output at 70 m and the photovoltaic output. Whereas the solar output outperforms the wind turbine’s output in the 400 summer months, the harvested wind energy is higher in the winter months December to February. Hence,300 a combination of wind and solar energy has a great potential to stabilize the decentralized energyEnergy (kWh) production in Gaza. 200

100

0

Figure 11. Expected energy output at different heights. Figure 11. Expected energy output at different heights. To put these results in perspective, we compare them with the potential of solar energy production in Gaza.800 According to the PVWatts Calculator, an annual photovoltaic energy output of 7196 kWh can E_Wind E_PV be expected700 from a comparable 5 kW photovoltaic system in a nearby region with similar conditions

600

500

400

300 Energy (kWh) 200

100

0

Figure 12. Expected energy output for a wind turbine at 70 m height and a comparable photovoltaic system.

Finally, we want to compare the potential of wind and solar energy with the average electricity consumption of a household in Gaza. According to a household energy survey conducted by the Palestinian Central Bureau of Statistics for January 2015 [28], the average electricity consumption in the Gaza Strip in January 2015 amounts to 265 kWh per household (with on average 5.7 persons). Based on our calculations for a typical meteorological year, the expected output of a wind turbine amounts to 558 kWh in January, which corresponds to the consumption of 2.1 households. The expected output of a photovoltaic system in January is 433 kWh, which would be sufficient for 1.6 households. Hence, a combination of one wind turbine and one photovoltaic system could energize 3.7 households. This number can be increased by installing more or larger turbines or photovoltaic systems on the roof of a residential building. For a high density of turbines, however, shadowing effects would have to be considered [29].

Energies 2017, 10, 1229 11 of 13

700 E_out 20 m 30 m 50 m 70 m 600

500

400

300 Energy (kWh) 200

Energies 2017, 10, 1229 11 of 13 100

0 like Gaza. Hence, the harvested annual energy of the considered small wind turbine at a height of 10 m corresponds to 37% of the solar energy or even 84% at a height of 70 m above ground. Figure 12 depicts the monthly comparison between the wind energy output at 70 m and the photovoltaic output. Whereas the solar output outperforms the wind turbine’s output in the summer months, the harvested wind energy is higher in the winter months December to February. Hence, a combination of wind and solar energy has a great potentialFigure 11. to Expected stabilize energy the decentralized output at different energy heights. production in Gaza.

800 E_Wind E_PV 700

600

500

400

300 Energy (kWh) 200

100

0

FigureFigure 12. 12. ExpectedExpected energy energy output output for a wind for aturbine wind at turbine 70 m height at 70 and m a height comparable and a photovoltaic comparable system.photovoltaic system.

Finally,Finally, we we want want to to compare compare the the potential potential of of wi windnd and and solar solar energy energy with with the the average average electricity electricity consumptionconsumption of of a a household household in in Gaza. Gaza. According According to to a a household household energy energy survey survey conducted conducted by by the the PalestinianPalestinian Central Central Bureau ofof StatisticsStatistics forfor January January 2015 2015 [28 [28],], the the average average electricity electricity consumption consumption in thein theGaza Gaza Strip Strip in January in January 2015 2015 amounts amounts to 265 to kWh 265 perkWh household per household (with on (with average on average 5.7 persons). 5.7 persons). Based on Basedour calculations on our calculations for a typical for a meteorological typical meteorologic year, theal year, expected the expected output of output a wind of turbine a wind amountsturbine amountsto 558 kWh to 558 in January,kWh in whichJanuary, corresponds which correspon to theds consumption to the consumption of 2.1 households. of 2.1 households. The expected The expectedoutput of output a photovoltaic of a photovoltaic system in system January in is Janu 433ary kWh, is which433 kWh, would which be sufficientwould be for sufficient 1.6 households. for 1.6 households.Hence, a combination Hence, a combination of one wind turbineof one wind and one turb photovoltaicine and one systemphotovoltaic could energizesystem could 3.7 households. energize 3.7This households. number can This be increasednumber can by installingbe increased more by or in largerstalling turbines more or photovoltaiclarger turbines systems or photovoltaic on the roof systemsof a residential on the building.roof of a Forresidential a high densitybuilding. of turbines,For a high however, density shadowing of turbines, effects however, would shadowing have to be effectsconsidered would [29 have]. to be considered [29].

5. Conclusions In this paper, we have conducted a feasibility study for wind energy production with small turbines in Gaza. With the turbine used in this study installed at a height of 10 m above ground, around 2406 kWh (TRANSYS simulation) or 2695 kWh (own calculations) of wind energy can be harvested per year. At higher altitudes between 20 m and 70 m above ground, an increase of the total harvested energy between 34% and 118% can be expected, but safety issues have to be considered then. The harvested energy of the considered small wind turbine at a height of 10 m corresponds to 37% of an equivalent 5 kW photovoltaic system or even 84% at a height of 70 m above ground. Moreover, it was shown that the harvested wind energy could compensate the weakness in the harvested photovoltaic energy in the winter months. One wind turbine and one comparable photovoltaic system together could provide enough energy for 3.7 households. This is a promising result for a region where people seek to reach energy self-sufficient buildings due to the severe electricity shortage in the local grid. Energies 2017, 10, 1229 12 of 13

Given the small size of the wind turbine and the large number of flat roofs in Gaza, a high number of turbines could be used to complement solar energy and to lead to a more reliable and environment-friendly energy supply. There are challenges coming from the import restrictions on Gaza, but this might be solved by local manufacturing of these turbines. Our future work will focus on studying the effect of height in practice through measurements. This research will open the door for finding better solutions to harvest the wind energy in Gaza, which is not exploited so far.

Acknowledgments: Financial support from the joint German-Palestinian research project POWERUS (PALGER2015-34-025) funded by BMBF and MoEHE and from the German Research Foundation are gratefully acknowledged. Author Contributions: Mohamed Elnaggar created the main structure for the paper, collected the wind data, wrote the draft paper, and contributed to the tools selection for data analysis. Matthias Ritter analyzed the data, confirmed the validity, worked on the comparison with a solar PV system, and reorganized the paper to include the effect of height. Ezzaldeen Edwan incorporated the comparison criteria with a PV system, revised the paper, and contributed in orienting the paper in its comparative study. Conflicts of Interest: The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

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