energies Article
Wind Energy Potential of Gaza Using Small Wind Turbines: A Feasibility Study Mohamed Elnaggar 1 , Ezzaldeen Edwan 1 and Matthias Ritter 2, * 1 2
*
ID
Department of Engineering, Palestine Technical College, College street, 920, Deir El-Balah, Gaza Strip, Palestine;
[email protected] (M.E.);
[email protected] (E.E.) 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 wind turbine 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: renewable energy; 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 wind power 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
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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:
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•
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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
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energy systems are concerned [10]. Moreover, this location, as a residential area, makes it a good candidate exploiting wind energy this for home usage solve energy systems arefor concerned Moreover, location, as atoresidential area,shortages. makes it a good candidate Energies 2017, 10, 1229 [10]. 3 of 13 for The climate database is constructed Meteonorm software (Meteotest, Bern, exploiting wind energy for home usage to solvebased energyon shortages. energy systems are concerned Moreover, this location, a residential area, makes itSwitzerland, a good Switzerland, meteonorm) the[10]. period fromon 1991 to 2010. as Meteonorm provides hourly data for a The climate database isfor constructed based Meteonorm software (Meteotest, Bern, candidate for exploiting wind energy for home usage to solve energy shortages. ‘typical meteorological year’from based1991 on nearby stations and stochastic meteonorm) for the period to 2010.weather Meteonorm provides hourly weather data for generators a ‘typical Thebeclimate database is constructed based on Meteonorm year software (Meteotest, Bern, (details can found in [11]). there is no stations typical meteorological datagenerators for Gaza, specifically, meteorological year’ based onSince nearby weather and stochastic weather (details can Switzerland, meteonorm) for the period from 1991 to 2010. Meteonorm provides hourly data for a wefound will rely on Ashdod climatic duemeteorological to the similarity between these two cities. Ashdod is only be in [11]). Since there is nodata typical year data for Gaza, specifically, we will rely ‘typical meteorological year’ based on nearby weather stations and stochastic weather generators 30 Ashdod km away from Gaza, located also in the between coastal plain of the Mediterranean Sea 30 at km the away same on climatic data due to the similarity these two cities. Ashdod is only (details can be found in [11]). Since there is no typical meteorological year data for Gaza, specifically, elevation, solocated they climatic conditions. This makesSea it a at reasonable candidate for from Gaza, alsocomparable in climatic the coastal plain ofthe thesimilarity Mediterranean thecities. sameAshdod elevation, so Gaza they we will rely onhave Ashdod data due to between these two is only wind30 data other studies, aslocated well (e.g., have comparable climatic conditions. This[9]). it a reasonable candidate for Gaza wind data in other km in away from Gaza, also inmakes the coastal plain of the Mediterranean Sea at the same Figure 1 so depicts the comparable histogram climatic of windconditions. speed data atmakes 10 m itheight for a typical meteorological elevation, they have This a reasonable candidate for Gaza studies, as well (e.g., [9]). wind data in other studies, as well (e.g., [9]). year.Figure It can be noticed that the wind speed can reach above 13 m/s for a few hours in certain days. 1 depicts the histogram of wind speed data at 10 m height for a typical meteorological Figure 1 depicts the histogram of wind speed data at 10 m height for a typical meteorological In Figure thenoticed wind situation is summarized a wind rose. for Most of the times, wind comes year. It can2,be that the wind speed canthrough reach above 13 m/s a few hours in certain days. year. It canthis noticed that thebetween speed can reach above and 13 m/s for a few hours inMost certain from the 2, sea, means from south-southwest north-northwest. of days. thecomes wind In Figure the be wind situation is wind summarized through a wind rose. Most of the times, wind In Figure 2, the wind situation is summarized through a windmeans rose. Most of thespeed. times, wind comes clear speeds lie between 2 and 6 m/s. Figure 3 shows the monthly of wind It becomes from the sea, this means from between south-southwest and north-northwest. Most of the wind speeds from the sea, this means from between south-southwest and north-northwest. Most of the wind that the average speed mostly 4 m/s,means except of forwind October andItNovember. Thethat highest lie between 2 andmonthly 6 m/s. Figure 3 showsexceeds the monthly speed. becomes clear the speeds lie between 2 and 6 m/s. Figure 3 shows the monthly means of wind speed. It becomes clear average wind speeds are achieved in February and September. average monthly speed mostly exceeds 4 m/s, except for October and November. The highest average that the average monthly speed mostly exceeds 4 m/s, except for October and November. The highest
windaverage speeds wind are achieved inachieved February September. speeds are in and February and September.
Figure 1. Histogram of wind speeds and the fitted Weibull distribution function (red) for the typical
Figure Figure 1. 1. Histogram Histogram of of wind wind speeds speeds and and the the fitted fitted Weibull Weibull distribution distribution function function (red) (red) for for the the typical typical meteorological year. meteorological meteorological year. year.
Figure 2. Wind rose for the typical meteorological year.
Figure 2. Wind rose rose for for the the typical typical meteorological meteorological year. year.
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Wind speed (m/s)
4.6 4.4 4.2 4 3.8 3.6 3.4
Figure3.3.Monthly Monthlyaverage averagewind windspeed speedininaatypical typicalmeteorological meteorologicalyear. year. Figure
Methodology 3.3.Methodology 3.1.Wind WindHarvesting HarvestingSystem SystemBasics Basics 3.1. Thewind windturbine turbineused usedfor forharvesting harvestingwind windenergy energyneeds needstotobe bemounted mountedatataarelatively relativelylarge large The heightabove abovethe theground groundtotoavoid avoidlocal localobstacles. obstacles.To Toovercome overcomethe theintermittency intermittencyofofwind windenergy, energy, height harvested energy is stored in battery banks and a DC/AC inverter is used to convert it to AC electrical harvested energy is stored in battery banks and a DC/AC inverter is used to convert it to AC electrical power.Home Homewind windturbines turbinesconsist consistofofaarotor, rotor,aagenerator generatormounted mountedon onaaframe, frame,and and(usually) (usually)aatail. tail. power. Throughthe thespinning spinningof ofturbine turbineblades, blades,the therotor rotorcaptures capturesthe thekinetic kineticenergy energyof ofthe thewind windand andconverts converts Through it into rotary motion to drive the generator. The rotor can have two, three, or more blades, butthe the it into rotary motion to drive the generator. The rotor can have two, three, or more blades, but mostcommon common rotors rotors have have three three blades. to to its most blades. The The input inputpower powerthat thatisisfed fedtotothe theturbine turbineisisproportional proportional swept area, which is proportional to the blade diameter. Details about the structure of wind turbines its swept area, which is proportional to the blade diameter. Details about the structure of wind can be found [12]. in [12]. turbines can beinfound 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 wind power industry. 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) ActualWind Electrical Produced Pin PowerPower into Turbine = = (1) Wind Power The wind power entering the turbine blades into P isTurbine calculated from the following equation: in
is calculated from the following equation: The wind power entering the turbine blades 1 Pin =1 ρAv3 (2) (2) = 2 2 where ρ is the air density (equal to 1.225 kg/m3 3 ), A is the swept area, and v is the magnitude of the where is the air density (equal to 1.225 kg/m ), is the swept area, and is the magnitude of the horizontal velocity [14]. horizontal velocity [14]. The electrical power output Pout can be obtained through the efficiency of the turbine according The electrical power output can be obtained through the efficiency of the turbine according to Equation (1) [15,16]: to Equation (1) [15,16]: 1 Pout = C p Pin = ρAC p v3 (3) 12 (3) = = 2 The power coefficient C p can also be calculated from the following equation [13]: The power coefficient
can also be calculated from the following equation [13]: C p = ηb ηm ηe =
(4) (4) where η is the blade aerodynamic efficiency, η is the mechanical efficiency, and η is the electrical where b is the blade aerodynamic efficiency, m is the mechanical efficiency, and e 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 C p has a maximum value of C p,max = 16/27 = 0.593 [18]. The Betz limit describes the maximum amount of energy a turbine can theoretically extract from the wind [14]: Pout,max =
1 · 0.593 · ρAv3 2
(5)
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. 2. 3. 4. 5.
Output power: It fits home use as the harvested energy is in the range of the average consumption of a household; Price (its price is competitive compared with others); Operation speed (fits low speed as starts from 2.5 m/s until 15 m/s); Efficiency is 30.5% which is relatively good; and Weight and size are suitable for home installations.
Table 1 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 power inverter. 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 Rated speed Power at 12.5 m/s Power at 15.0 m/s Start wind speed Total efficiency Total weight of the system
3.8 m 450 rpm 3800 W 5000 W 2.5 m/s 30.5% 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
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reliable modeling and simulation programs oriented to deal with complicated energy systems [22]. The core TRNSYS components of the model are presented in Table 2 and Figure 4. Figure 4 shows the TRANSYS interface of the model. It depends on a certain number of Energies 2017, 10, 1229 6 of 13 interconnected components and each component has an input and an output. The description of each component is shown in Table 2. It should be noted that theIt core component modelnumber in the system Figure 4 shows the TRANSYS interface of here the model. depends on a certain of is theinterconnected wind turbinecomponents defined as Type90 we configured of this component model and eachwhere component has an inputthe andparameters an output. The description of each according to theisspecifications 5000S small wind Type109-TMY2 is the thesystem model for component shown in Table of 2. ItWTT should be noted here that turbine. the core component model in is theData windReading turbine defined as Type90 where weconsists configured the parameters of this component model “Weather and Processing” which of wind speed, wind direction, and ambient according to the specifications of WTT 5000S small wind turbine. Type109-TMY2 is the model temperature. The online_T65 model creates plots of wind speed, resulting power in daily andfor hourly Data Reading and Processing” which consistsand of wind wind direction, and ambient basis.“Weather The functionality of Type25a and Type25b/Daily Totalspeed, Results models are shown 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 C p 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 TRANSYS model depends on the wind speed. Table 2. Explanation of TRNSYS model components following [23]. Name Name Weather Weather data data Wind turbine
in the
Table 2. Explanation of TRNSYS model components following [23].
Component type Component type
Type109-TMY2
Type109-TMY2
Description
Description Weather Data Reading and Processing.Typical Weather Data Reading and Processing. Meteorological Year (TMY) data Typical Meteorological Year (TMY) data Wind ConversionSystem System (WECS). Power versus WindEnergy Energy Conversion (WECS). Power versus wind areread readinina afile. file. The impact ofdensity air density windspeed speed data data are The impact of air changes windspeed speedincrease increase with height modeled. changes and and wind with height are are modeled.
Wind turbine
Type90 Type90
OnlineOnline Plotter
online_T65 online_T65
Output/Online Plotter/Online Plotter Output/Online Plotter/Online Plotter WithWith File. File.
Type25aand and Type25b/ Type25a Type25b/Daily Dailyand and Total results Total results
ItItcan withaatime timestep step that is different from can print print with that is different from the the simulation time step. simulation time step.
Plotter
Printer Printer
Figure 4. 4. System usingTRNSYS TRNSYS [23]. Figure Systemmodel model designed designed using [23].
3.5. Extrapolation of Wind Speed DifferentHeights Heights 3.5. Extrapolation of Wind Speed to to Different To calculate effect of the height,the thewind wind speeds speeds are to to different heights usingusing To calculate the the effect of the height, areextrapolated extrapolated different heights the power law (e.g., [14,24]): the power law (e.g., [14,24]): α z (6) v ==vr (6) zr denotes wind speed extrapolatedto to height height zand speed at reference height wherewhere v denotes the the wind speed extrapolated and vrthe thewind 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
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Energies 2017, 10, 1229 Katz, and Murphy, the power law provides a ‘reasonable first approximation 7 of 13 According to Brown, to the change of wind speed with height under most meteorological conditions’ [24] (p. 1190). If data on Energies 2017, 10, 1229 7 of 13 to the change of wind speed with height under most meteorological conditions’ [24] (p. 1190). If data 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 tothe the log change of profile wind speed height under most meteorological conditions’ [24] (p. 1190). If data using wind (e.g.,with [25,26]). 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. Results and Discussion 4. Results and Discussion
Figure 5 shows the the results of the hourly power Pout at at C p ==0.305 Figure 5 shows results of the hourly power 0.305over over the the year year based based on on the the wind 4. Results and Discussion speed depicted in Figure 1. It can be noticed that the maximum power output of 5000 W was not wind speed depicted in Figure 1. It can be noticed that the maximum power output of 5000 W was Figure 5 shows the results of the hourly power at = 0.305 over the year based on the achieved due to too wind speeds at the height of of 1010 m.m. not achieved due low to too low wind speeds at turbine the turbine height wind speed depicted in Figure 1. It can be noticed that the maximum power output of 5000 W was not achieved due to too low wind speeds at the turbine height of 10 m. 5
P_outP_out (kW)(kW)
5 4 4 3 3 2 2 1 1 0 1-Jan 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
1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Sep 1-Oct 1-Nov 1-Dec Figure 5. Hourly distribution of power output for1-Aug the typical meteorological year. 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 detailed visualizationofofthe thehourly hourly wind wind speeds andand the the corresponding powerpower A detailed visualization speedsininFebruary February corresponding output is presented in Figure 6.The Themaximum maximum wind speed was 12.7 m/s on 15 February leading to a output isApresented in Figure 6. wind speed was 12.7 m/s on 15 February leading detailed visualization of the hourly wind speeds in February and the corresponding power to a power output of 4340 W. In addition, the daily cycles of wind speed and, hence, power become visible. power output of 4340 W. addition, daily cycles of wind speed and, powerleading become output is presented in In Figure 6. Thethe maximum wind speed was 12.7 m/s onhence, 15 February to visible. a Figure 7 first shows the energy that can be harvested in each month of the year based on the Figure 7 firstofshows energy that can cycles be harvested in each of thebecome year based power output 4340 W.the In addition, the daily of wind speed and,month hence, power visible.on the simulations using TRNSYS for the typical meteorological year, denoted . The months of January Figure 7 first shows for the the energy that meteorological can be harvestedyear, in each month Eofsimthe yearmonths based on simulations using TRNSYS typical denoted . The of the January and July have the highest expected energy yields, 225 kWh and 237 kWh, respectively. Since those simulations using TRNSYS for the typical meteorological year, denoted . The months of January and months July have the highest expected energy yields, 225 kWh and 237 kWh, respectively. Since those are located in winter and summer, this indicates that it is promising to harvest energy in Gaza andare Julylocated have the expected energy yields, 225 kWh and kWh, respectively. Since those months in highest winter and summer, this indicates thatenergy it is237 promising to2406 harvest in Gaza throughout the year. For the whole year, the total expected amounts to kWhenergy from one months are located in winter and summer, this indicates that it is promising to harvest energy in Gaza throughout Forfor thethe whole the total expected energy amounts to 2406 kWh from one turbine atthe 10 year. m height typicalyear, meteorological year. 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. 14 5 turbine at 10 m height for the typical meteorological year. P_out
Wind speed
4
P_out
Wind speed
P_outP_out (kW)(kW)
4 3
14 12 12 10 10 8
3
8 6
2
6 4
2 1
4 2
WindWind speedspeed (m/s)(m/s)
5
1 2 0
0
1/2/ 1/2/ 2/2/ 2/2/ 3/2/ 3/2/ 4/2/ 4/2/ 5/2/ 5/2/ 6/2/ 6/2/ 7/2/ 7/2/ 8/2/ 8/2/ 9/2/ 9/2/ 10/2/10/2/ 11/2/11/2/ 12/2/12/2/ 13/2/13/2/ 14/2/14/2/ 15/2/15/2/ 16/2/16/2/ 17/2/17/2/ 18/2/18/2/ 19/2/19/2/ 20/2/20/2/ 21/2/21/2/ 22/2/22/2/ 23/2/23/2/ 24/2/24/2/ 25/2/25/2/ 26/2/26/2/ 27/2/27/2/ 28/2/28/2/
0
0
Figure 6. Hourly wind speed and corresponding power output in February for the typical meteorological year. Figure 6. 6. Hourly poweroutput output February for typical the typical Figure Hourlywind wind speed speed and and corresponding corresponding power in in February for the meteorological year. meteorological year.
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E_sim
E_out
E_out,max
E_in
1000 900 800 Energy (kWh)
700 600 500 400 300 200 100 0
Figure 7. Harvested energy for each month of the year. Figure 7. Harvested energy for each month of the year.
Figure 77 also thethe expected monthly energy Ein , Eout,max Eout at C p = 0.305 Figure alsodepicts depicts expected monthly energy , , and , and at according = 0.305 , to the power in Equations (2), (3), and (5), respectively. Not surprisingly, E has the highest in surprisingly, value according to the power in Equations (2), (3), and (5), respectively. Not hassince the it describes the kinetic energy of the wind arriving at the turbine. It can be seen that the kinetic energy highest value since it describes the kinetic energy of the wind arriving at the turbine. It can be seen is lowest in theenergy monthsisOctober to the December, also to thewhich lowestalso power outputs these that the kinetic lowest in months which October to leads December, leads to the in lowest months. The maximum amount that can be harvested theoretically, E , corresponds to 59.3% of out,max theoretically, power outputs in these months. The maximum amount that can be harvested , , E . Given the efficiency of our turbine to be C = 0.305, only 51.4% of E can be achieved with p out,max in corresponds to 59.3% of . Given the efficiency of our turbine to be = 0.305, only 51.4% of our turbine, leading to awith power output Eout of 2695 kWh for the entire year. This kWh shows can be achieved our turbine, leading to a power output of 2695 forthat thethere entireis , only a slight difference between the results from the TRNSYS simulations and the calculations based year. This shows that there is only a slight difference between the results from the TRNSYS on Equationand (3).the calculations based on Equation (3). simulations For a more thethe hourly power output and wind speedsspeeds on the 1st February For a moredetailed detailedperspective, perspective, hourly power output and wind on of the 1st of are shown in Figure 8. On this day of the typical meteorological year, the peak wind speed is 6.9 m/s February are shown in Figure 8. On this day of the typical meteorological year, the peak wind speed 7:00 PM and leads and to expected of powers 2280 W,of 1350 W,W, 6961350 W, and 610 W, W for out,max in , PW isat6.9 m/s at(19.00) 7:00 PM (19.00) leads to powers expected 2280 W, 696 andP610 for , Pout , and P , respectively. It is confirmed that the simulation results lie very close to the theoretical sim , , , and , respectively. It is confirmed that the simulation results lie very close to , results of the actual power withproduced the wind with turbine 5000S) an5000S) overallwith turbine the theoretical results of theproduced actual power thetype wind(WTT turbine typewith (WTT an efficiency of C = 0.305. p overall turbine efficiency of = 0.305. Figure 9 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 whereas Psim,, Pout,max ,, and continuously, and Pout are are bounded bounded by by the the turbine turbine capacity. capacity. ,
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P_sim P_sim
P_out,max P_out,max
P_out P_out
P_in P_in
Wind speed Wind speed
7 7 Wind speed (m/s) Wind speed (m/s)
6 6
5
Power (kW) Power (kW)
3 3 2.5 2.5 2 2 1.5 1.5 1 1 0.5 0.5 0 0 0 0
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5
4
4
3
3
2
2 1 5
10 15 10Hour of the day 15
5
20 20
1
Hour of the day Figure 8. Hourly power output and wind speed of February. Figure 8. Hourly power output and wind speed on on thethe 1st1st of February. Figure 8. Hourly power output and wind speed on the 1st of February.
P_sim P_sim
P_out P_out
P_out,max P_out,max
P_in P_in
Power (kW) Power (kW)
16 16 14 14 12 12 10 10 8 8 6 6 4 4 2 2 0 0 0 0
2 2
4 4
6 8 6Wind speed 8(m/s) Wind speed (m/s)
10 10
12 12
14 14
Figure 9. The relationship of power output with wind speed. Figure 9. The relationship of power output with wind speed. Figure 9. The relationship of power output with wind speed.
results mentioned before were based wind speeds of the typical meteorological year AllAll thethe results mentioned before were based onon wind speeds of the typical meteorological year All the results mentioned before were based on wind speeds of the typical meteorological year measured at a height of 10 m above ground. If a wind turbine is installed on top of a roof, however, measured at a height of 10 m above ground. If a wind turbine is installed on top of a roof, however, measured atheights a height ofcan 10 be m achieved. above ground. Ifthe a the wind turbine is increasing installedheight, on topthe ofthe a roof, however, much larger heights study potential of height, wind speeds much larger can be achieved. ToTo study potential of increasing wind speeds areare much larger heights can be achieved. To study the potential of increasing height, the wind speeds are extrapolated to different heights according to Equation (6). extrapolated to different heights according to Equation (6). extrapolated to different heights according to Equation (6). Figure 10 depicts the expected wind speeds at a height of 70 m for the month of February and Figure 10 depicts the expected wind speeds at a height of 70 m for the month of February and the Figure 10 depicts the expected wind speeds at a height of 70 m for the month of February and the corresponding power Compared output. Compared to the Figure 6, thewind maximum wind has to now corresponding power output. to Figure 6, maximum speed has nowspeed increased the corresponding power output. Compared to Figure 6, the maximum wind speed has now increased to 16.77 m/s, which leads to the maximum power output of 5000 W. 16.77 m/s, which leads to the maximum power output of 5000 W. increased to 16.77 m/s, which leads to the maximum power output of 5000 W.
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6
18.00 P_out 70 m
Wind speed 70 m
16.00 14.00
4
12.00 10.00
3
8.00
2
6.00
Wind speed (m/s)
P_out (kW)
5
4.00
1
2.00
0 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/
0.00
Figure Figure10. 10. Hourly Hourlywind windspeed speedat atheight height70 70 m m and and corresponding corresponding power power output output in in February. February.
Energy (kWh)
Figure expectations forfor E at heights of 20 m, 30 m, 50 m, and Figure 11 11shows showsthe theresulting resultingmonthly monthly expectations out at heights of 20 m, 30 m, 50 m, 70 m above the ground. According to this, the same turbine can achieve a much and 70 m above the ground. According to this, the same turbine can achieve ahigher much energy higher output energy for higher heights. Compared to the energy at a height of 10 m, the yearly energy output increases by output for higher heights. Compared to the energy at a height of 10 m, the yearly energy output 35% for a height 20 m, by 60%offor 97% At a97% height thea expected increases by 35%offor a height 2030 m,m,byand 60% forfor 3050 m,m.and for of 5070 m.m,At height ofyearly 70 m, energy output corresponds to 6055 kWh, which corresponds to a surplus of 125% compared to a the expected yearly energy output corresponds to 6055 kWh, which corresponds to a surplus of 125% height of 10 It should that be thenoted installation a wind turbine on the roof of residential compared tom. a height of 10bem.noted It should that theofinstallation of a wind turbine onathe roof of a building requires a careful analysis of safety issues. These safety issues, however, will be manageable residential building requires a careful analysis of safety issues. These safety issues, however, will be considering use of a small wind with aturbine weightwith of around 74 kg. Compared with the costs manageablethe considering the use of aturbine small wind a weight of around 74 kg. Compared of a turbine and installation at ainstallation higher height about $9000ofUSD in $9000 total, the yearly yield 6055 with the costs of its a turbine and its at a of higher height about USD in total, theofyearly kWh at 70 m brings in more than 9% of the initial costs per year assuming a price of $0.14 USD/kWh yield of 6055 kWh at 70 m brings in more than 9% of the initial costs per year assuming a price of according to10, [27]. Energies 2017, 1229 11 of 13 $0.14 USD/kWh according to [27]. To put these results in perspective, we compare them with the potential of solar energy production in Gaza. According to the PVWatts Calculator, an annual photovoltaic energy output of 700 7196 kWh can be expected from E_out a comparable photovoltaic in a nearby region with 20 m 5 kW30 m 50 m system 70 m similar 600conditions 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, 300a combination of wind and solar energy has a great potential to stabilize the decentralized energy 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 800 According to the PVWatts Calculator, an annual photovoltaic energy output of 7196 kWh can in Gaza. E_Wind E_PV be expected from a comparable 5 kW photovoltaic system in a nearby region with similar conditions 700
rgy (kWh)
600 500 400
Energy (
400 300 200
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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 Figure 11.to Expected energy output at different heights. solar energy has a great potential stabilize the decentralized energy production in Gaza. 800 700
E_Wind
E_PV
Energy (kWh)
600 500 400 300 200 100 0
Figure12. 12.Expected Expected energy output for aturbine wind at turbine at 70 and m aheight and aphotovoltaic comparable Figure energy output for a wind 70 m height comparable photovoltaic system. system.
Finally, Finally,we wewant wantto tocompare comparethe thepotential potentialof ofwind windand andsolar solarenergy energywith withthe theaverage averageelectricity electricity consumption of a household in Gaza. According to a household energy survey conducted consumption of a household in Gaza. According to a household energy survey conductedby bythe the Palestinian Central Bureau of Statistics for January 2015 [28], the average electricity consumption in Palestinian Central Bureau of Statistics for January 2015 [28], the average electricity consumption in the the Gaza Strip in January 2015 amounts to 265 kWh per household (with on average 5.7 persons). Gaza Strip in January 2015 amounts to 265 kWh per household (with on average 5.7 persons). Based on Based on our calculations for ameteorological typical meteorological the expected a windamounts turbine our calculations for a typical year, the year, expected output ofoutput a windofturbine amounts to 558 kWh in January, which corresponds to the consumption of 2.1 households. The to 558 kWh in January, which corresponds to the consumption of 2.1 households. The expected expected of a photovoltaic is which 433 kWh, which would befor sufficient for 1.6 output ofoutput a photovoltaic system in system JanuaryinisJanuary 433 kWh, would be sufficient 1.6 households. households. Hence, a combination of one wind turbine and one photovoltaic system could energize Hence, a combination of one wind turbine and one photovoltaic system could energize 3.7 households. 3.7 households. number can be increased more or or photovoltaic larger turbines or photovoltaic This number canThis be increased by installing morebyorinstalling larger turbines systems on the roof systems on the roof of a residential building. For a high density of turbines, however, shadowing of a residential building. For a high density of turbines, however, shadowing effects would have to be effects would have to be considered [29]. 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.
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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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