Renewable Energy Sources for Isolated Self-sufficient Microgrids: Comparison of Solar and Wind Energy for UAE

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1 Available online at ScienceDirect Energy Procedia 103 (2016 ) Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid, April 2016, Maldives Renewable Energy Sources for Isolated Self-sufficient Microgrids: Comparison of Solar and Wind Energy for UAE Sayyad Basim Qamar a and Isam Janajreh a * a Masdar Institute, Masdar City, Abu Dhabi 54224, UAE Abstract Renewable energies are a fast growing sector, working towards satisfying global energy demands. With the advent of smart and microgrids the power production from such technologies has seen a boom in integrating with energy needs of today. This paper looks into the deployment of an isolated microgrid to power small settlements in remote locations. It performs an economic feasibility analysis of deployment of wind and solar energy to satisfy the energy requirements of these microgrids, as an alternative to using fossil fuel generators. The energy production is estimated using data analysis of wind and solar irradiation. Both solar and wind energy would be suitable for replacing current generators, with a profit in savings. Solar was found to be the better alternative in the UAE compared to wind Published The Authors. by Elsevier Published Ltd. This is by an Elsevier open access Ltd. article under the CC BY-NC-ND license ( Selection and/or peer-review under responsibility of REM2016 Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. Keywords: Wind Energy, Solar Energy, Economic Analysis, NPW, IRR 1. Introduction The foremost problems faced by the world today are energy and environmental issues. Renewable energies are a shining beacon of hope, revolutionizing the energy industry and the way energy demands are met, with low carbon footprints. With advances in technology and improvements in grids, many of these energy sources have started to come online as commercially feasible alternate energy solutions. Remote areas pose a unique challenge for power production and delivery. Developing solutions to make these areas self-sufficient for energy is critical, as the costs of fuel delivery and grid extension are too extreme for the consumer base as mentioned by Lew [1]. In equatorial areas, such as the UAE, the potential for solar energy is vast as published by Islam et al. [2]. Wind energy has also shown strong * Corresponding author. Tel.: ; fax: address:ijanajreh@masdar.ac.ae Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. doi: /j.egypro

2 414 Sayyad Basim Qamar and Isam Janajreh / Energy Procedia 103 ( 2016 ) potential as a renewable energy source, with modern turbines competing with conventional power systems as one of the most economic renewable energy sources in many areas of the world as reported by McQueen and Watson [3] and by Alnaser and Alnaser [4]. With the application of renewable energy powered microgrids, these remote locations can be made energy self-sufficient. These microgrids have been implemented in many locations across the world in such an attempt, using either single or hybrid renewable energy sources. These tend to be either solar, wind or both in standalone or hybrid configurations with diesel generators and batteries with good success as reported by Li and Xiang [5] as well as Abdilahi et al. [6]. In this paper, we evaluate the potential of wind energy from wind data obtained through measurement stations. The potential for solar energy is also analyzed using published data. Two scenarios are considered for powering isolated microgrids; using only wind or using only solar energy. The economic benefits and feasibility of these two scenarios are analyzed, applied to a worker camp of small size. This helps to shed light on the potential of each source to power the microgrid and make it self-sufficient. 2. Methodology A small community of approximately 100 individuals is considered, typical of camps of mining or petroleum industries. The energy demand of this community is forecasted for a year. These camps tend to have a life of approximately 5 years, hence, a redeployment scheme was implemented to shift the power production setup to the new camp locations, every 5 years. To meet the energy demand, standalone diesel generators are analyzed as the baseline to analyze the cost savings. The energy requirements for the microgrid are shown in Table 1. Table 1. Energy Requirements of the Microgrid Energy Requirement per Capita 2MWh/year Number of People 100 Diesel Cost 3 AED/liter Diesel Required 350liters/MWh Diesel Generator 42,500 AED* Cost Saving per year using Renewable Energy AED *3.667AED=1$ To determine how many units of either wind turbines or solar panels would be required, an analysis was carried out using the available wind data from measurement stations, as well as the data banks in the System Advisor Model software published by NREL. 2.1 Wind power analysis Wind speed measurements were taken from meteorological stations and data from the National Center of Meteorology and Seismology, UAE [7]. The mean wind speeds at different locations in the UAE are displayed in Figure 1a. One of the measurement sets was fitted to a Weibull distribution to assist in predicting power production capability of the turbine, according to Equation 1. The Weibull density curve overlaid upon the raw data histogram is shown in Figure 1b. (1)

3 Sayyad Basim Qamar and Isam Janajreh / Energy Procedia 103 ( 2016 ) Fig. 1. (a) Mean Wind Speeds across UAE; (b) Data with Weibull Distribution Plot Using the Weibull distribution parameters, the wind turbine power calculator tool [8] was used to estimate the power generation from a specific horizontal axis wind turbine, whose specifications are shown in Table 2. This tool was used due to its fast computation using the statistical data to estimate production. To verify the results of the tool an algorithm was implemented for power production in Matlab, using hourly data from the raw measurements to estimate the real power production capability of the same turbine, using its power curve. The power curve and algorithm are displayed in Figure 2a(i) and 2b. The power prediction from the two sources is compared in Figure 2a (ii). Table 2. Turbine Specifications Turbine Rated Power Cut-in Speed Cut-out Speed Rotor Diameter RPM Range Hub Height 150 kw 3 m/s 25 m/s 27 m m The power of the turbine is calculated by Equation 2. Power = 1 2 A v3 Cp (2) Where, is the fluid density, A is the swept area of the turbine blades, v is the wind velocity and Cp is the turbine s coefficient of performance. The Cp is found from the performance curve, using the tip speed ratio as per Equation 3. (3) Where, is the rotational speed of the turbine and r is the radius of the turbine.

4 416 Sayyad Basim Qamar and Isam Janajreh / Energy Procedia 103 ( 2016 ) Fig. 2. (a) (i) Power Curve for Turbine, (ii) Comparison of Prediction Models; (b) Algorithm for Power Prediction 2.2 Solar power analysis The System Advisor Model (SAM) software of NREL was used to estimate the solar potential for Abu Dhabi as the standard for UAE. An expected 10 hours of production per day could be expected from PV panels in the region. This was used to calculate the number of panels required to produce the required power. The panel details and system requirements are shown in Table 3. Table 3. Panel Specifications Panel Type Panel Peak Rating Panel Nominal Rating Panel Size No. of Panels Required PV 320W 245W 1955x990 mm 224 Since, solar power is produced only for 10 hours per day, and wind energy also faces fluctuations in production, a storage mechanism is required to satisfy the energy requirements for the microgrid. To compensate for this and any unusual power requirement patterns, a decision was taken to implement a storage battery bank. The battery specifications and storage requirements for both wind and solar are shown in Table 4. Table 4. Battery Specification & Requirements Battery Capacity Avg. Hourly Requirement Storage Required No. of Batteries Storage Required/Day Total Storage Required (Solar) No. of Batteries Required (Solar) (Wind) Required (Solar) 10 kwh ~22.5 kwh 24 hours kwh (14 hours) 28 hours Economic analysis The economic analysis for both technologies was carried out by calculating their Net Present Worth (NPW) along with their Payback Period and Internal Rate of Return (IRR). The interest rate for the UAE

5 Sayyad Basim Qamar and Isam Janajreh / Energy Procedia 103 ( 2016 ) as reported by [9] was selected as 1.25%. The formulae used for these calculations were as shown in Equations 4, 5 and 6 (Equations taken from [10]). NPW=Capital Costs+Initial Savings+PW Annual Costs+Savings + PW Periodic Costs (4) 1 PW Periodic Cash Flow =Future Cash Flow* (5) (1+i) N PW Annual Cash Flow =Annual Cash Flow* (1+i)N -1 (6) i(1+i) N Where, PW represents the present worth of the cash flows incurred in the future, i is the interest rate and N is the period in which the cash flow is incurred. The study lifetime was set as 20 years (typical life of solar and wind energy equipment). The costs of the systems were determined from data published by [11], [12], [13] and [14], shown in Table 5. Table 5. Cost Details Wind Turbine AED 9175 /kw Solar Panels AED 0.46 /kwh Battery AED Land AED25 /sqft Redeployment Cost for Wind 5% of Capital Cost Redeployment Solar 15% of Capital Cost Maintenance Wind 3% of Capital Annually Generator Cost AED 42,500 Fuel Cost AED 3/liter 3. Results According to the data presented in the previous section, the cash flow diagrams for both technologies were generated and are shown in Figure 3a & 3b. Fig.3. (a) Cash Flow Diagram for Wind Energy; (b) Cash Flow Diagram for Solar Energy

6 418 Sayyad Basim Qamar and Isam Janajreh / Energy Procedia 103 ( 2016 ) The Payback Period Diagram for both technologies is shown in Figure 4a. A comparison of NPW, IRR and Payback Period is shown in Figure 4b. Both the technologies would result in a profit over their lifetimes, compared to the current power production technologies in place. 4. Conclusion Fig. 4. (a) Payback Period Diagram; (b) Economic Measure Comparison for Both Technologies From the above figures, it is easy to see that both technologies produce a profit when compared to the cost of current isolated microgrids powered by diesel generators. However, it was observed that in a region such as the UAE, sunlight is abundant in good quality, whereas, wind resources are not promising (maximum average speeds ~ 4-6 m/s). This leads to low capacity factors for the wind turbines, such as in the studied case (~ 27%). The solar energy is cheaper to deploy in term of CAPEX (nearly half) and also breaks even quicker. Due to this fact, it has a much higher Net Present Worth, generating greater profit, making it the most attractive best alternative to produce clean electricity for isolated microgrids. However, it should be noted that solar energy requires large spaces to accommodate the necessary solar panels and batteries. Redeployment costs are also larger due to the large amount of transportation required. For areas with better wind resources, wind energy could prove to be feasible, especially for larger populations. It also holds an advantage of requiring lesser storage as, theoretically, 24-hour production can be expected. References [1] Lew, D. (2000). Alternative to coal and candles: wind power in China. Energy Policy, 28, [2] M.D. Islam, I. K. (2009, April). Measurement of solar energy radiation in Abu Dhabi, UAE. Applied Energy, 86, [3] D. McQueen, S. W. (2006). Validation of wind speed prediction methods at offshore sites. Wind Energy, 9, [4] W.E. Alnaser, N. A. (2009). Soalr and wind energy potential in GCC countries and some related projects. Journal of Renewable and Sustainable Energy, 1(2). [5] W.W.J. Li, J. X. (2012). A simple sizing algorithm for stand-alone PV/Wind/Battery hybrid microgrids. Energies. [6] A.M.Abdilahi, A. Y. (2014). Feasibility study of renewable energy-based microgrid system in Somaliland's urban centers. Renewable and Sustainable Energy Reviews, [7] UAE National Centre for Meteorology and Seismology, [8] Wind Turbine Power Calculator, Danish Wind Industry Association, [9] Trading Economics (from Central Bank of the UAE), [10] W. Sullivan, E. Wicks, C. Koelling. Engineering Economy, 15th Edition, Pearson (Prentice Hall), p [11] DS72 series, [12] Wind Power, IRENA Working Paper, Renewable Energy Technologies: Cost Analysis Series vol. 1(5); [13] [14] Masdar Institute/IRENA, Renewable Energy Prospects: United Arab Emirates, REmap 2030 analysis. IRENA, Abu Dhabi