FEASIBILITY OF RENEWABLE ENERGY BASED DISTRIBUTED GENERATIONS IN YANBU, SAUDI ARABIA

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1 FEASIBILITY OF RENEWABLE ENERGY BASED DISTRIBUTED GENERATIONS IN YANBU, SAUDI ARABIA Alaa Alaidroos Civil, Environmental, and Architectural Engineering University of Colorado at Boulder Long He Department of Physics University of Colorado at Boulder Moncef Krarti, PhD, PE, LEED AP Civil, Environmental, and Architectural Engineering University of Colorado at Boulder Boulder, CO , USA ABSTRACT A Small residential community in Yanbu industrial city in Saudi Arabia has been selected to evaluate the economic feasibility and optimal renewable energy combination systems that cover the energy demands of the community and help in reducing carbon emissions. The community s hourly electrical load is generated using equest energy simulation which then applied to HOMER software for DG optimization analysis. The economic analysis is performed for the grid connected to the wind farm, PV system and hybrid system. Sensitivity analysis is applied for different rebate levels for PV system and annual average wind speed. Sensitivity analysis is also applied for the utility rates to evaluate the cost effectiveness of the renewable options when the utility rates increases. The analysis indicates that the wind farm has a good potential in increasing the renewable fraction and decreasing the carbon dioxide emission while maintaining a relative low cost of energy. At the same time, the PV system is still an expensive choice unless the government rebate is raised to a high level. An optimization analysis is conducted to find the optimal hybrid DG system that has the lowest cost of energy and a relatively high percentage of carbon emission reduction. The optimal hybrid system had a COE equals to $/kwh and significant carbon reduction percentage that equals to 103%. This hybrid system consists of wind turbines, converters and the grid. 1. BACKGROUND Yanbu is a 30 years old industrial city that has an effective and major role to the economy of the Kingdom of Saudi Arabian About two third of the area of the city consists of industrial companies ranging from petrochemical, mineral, manufacturing. The population of this important industrial city is around 50,000. In this case study, we will analyze a small community in Yanbu that represents a private residential complex of two hundred residential buildings for one of the biggest petrochemical companies in Yanbu. 1.1 Electricity In Yanbu Fig. 1: Location of the case study The major utility company in Saudi Arabia that serves most of the country s regions is the Saudi Electric Company (SEC). Most of the electricity is generated by using Diesel, heavy oil, and natural gas. Desalination plants are also used to help in generating electricity by using the steam that is a byproduct of the desalination process. The power generation 1

2 plant in Yanbu Industrial City has a capacity of 1,030 MW with an average leveled cost of production equals to 0.10 $/kwh. Diesel cost is $/L which is about $/gal. The average cost of electricity for a residential building in Yanbu is about 0.03 $/kwh [12]. 1.2 Energy Demand In Saudi Arabia At this time, the capacity of generating power in Saudi Arabia is 46,000 MW. Power demand is growing every year by 3,000 MW. This annual growth is very big comparing to other countries. The investments in power demand for the years between 2009 to 2018 as the experts indicated is about 1,125 billion dollars. In terms of oil usage, Saudi Arabia has used 100 million barrels of oil in 2009 to produce electricity. Over one quarter of the oil production in Saudi Arabia is consumed by the country it self! [15,18] 53% of the consumed power in Saudi Arabia is by households and most of the power consumption is used for cooling. This demand of electricity will increase from today s 46,000 MW to 120,000 MW within 20 years. At this rate of growth in electricity consumption, the country s energy and oil consumption will be multiplied in a decade. This will affect the economy in Saudi Arabia very badly in the future because the economy in this country is depending on oil export revenues. The growth of local consumption will jeopardize the ability of exporting to the international markets. In fact, this rate of local energy consumption growth is not a sign of economic development; actually it s a sign of inefficient use of energy. [15,18] 1.3 Electricity Prices And Subsidies The current cost of electricity production is $0.10/kWh. And the average electricity price is about $0.03/kWh. [15] The question here, Is the low prices charged are subsidized or simply low prices? Based on the International Energy Agency (IEA), Fuel subsidies are what governments spend to provide fuel prices for the citizens that are lower than the cost of production. The difference between prices and cost are paid from the government resources. There are many countries that are subsidizing fuel and electricity prices to their citizens; Saudi Arabia is the second largest country after Iran who is subsidizing prices as shown in Fig % of the fuel consumption is subsidies to oil and 30% to electricity. This subsidies is costing Saudi Arabia about $188 billions. Politically speaking, this very expensive subsidizing system is part of a political settlement to redistribute the country s oil wealth to the citizens. However, these low prices are preventing investments in renewable energy generation and efficiency improvements as described in this case study. [16,17] Fig. 2: Fuel subsidies in different countries [16] 2. OBJECTIVES The objective of this study is to investigate the ability of utilizing renewable energy systems to provide the chosen community with its needs of electricity. This hybrid system will help the community to have better energy efficiency along with environmental benefits by reducing emissions. A feasibility study of using an integrated renewable energy system along with the traditional power plants could be applied because the community is already connected to the grid. 3. SOURCES AND DATA COLLECTION Some of the data required for this study has been requested directly from the original sources in Yanbu industrial city such as Marafiq (utility company in Yanbu) and the Royal Commission in Yanbu which is responsible for residential development. Some other data were collected from different previous related researches, especially renewable energy researches done specifically for Yanbu. 3.1 Electrical Load The total electrical load for the residential community has been obtained directly from Marafiq (the utility company). Electricity is used for heating domestic water and there are 2

3 no heating loads in the winter due to the moderate temperature. Moreover, a building energy simulation has been implemented using equest to generate the hourly electrical load for this community to be used in HOMER. A typical two-story residential building design was used in equest. The hourly electrical load generated by equest is for a single house. This load will be multiplied by 200 that is the number of residential buildings in this community. Fig. 3 shows the details of electricity consumption of the residential building by equest. Fig. 4: Hourly electrical load for a single house [HOMER] 3.2 Wind Energy Fig. 3: Electric consumption for the residential building [equest] The hourly simulation results, as shown in Fig. 4, indicate that the average electrical load for one residential building is 10.5 kwh. The community consists of 200 buildings, so if we multiply the number of buildings by the 10.5 kwh we will have a total electrical load of 2,100 kwh for the whole community. The actual load that has been obtained from the utility company in Yanbu was 55,000 kwh for one day for the whole community. Therefore, the hourly load will be 55,000 divided by 24 and that will be around 2,291 kwh. The difference between the actual hourly load and the loads that we had from the simulation is about 8%. This small difference between the actual and simulation load could be because of the behavior of different occupants when dealing with lighting and comfort situations, and the construction materials. In Saudi Arabia, the first wind atlas was reported by S. Ansari. In 1986 Rehman calculated the Weibull parameters for ten anemometer locations in Saudi Arabia. Rehman and Halawani presented the statistical characteristics of wind speed and its diurnal variation. Their analysis showed that the minimum cost (US$ ) of electricity production was found for Yanbu [8]. In 2004, Rehman presents longterm wind data analysis in terms of annual, seasonal and diurnal variations at Yanbu. Most of the wind in Yanbu comes from the south with a speed of up to 8 m/s [8] as shown in Fig. 5 this will help when choosing the orientation of the wind turbines to have the best performance in power generation. Fig. 5: Wind rose chart at 40m above ground in Yanbu [8] The averaged wind data with monthly and diurnal variations at Yanbu presented by Rehman s 2004 paper has been used in this case study. This wind data will be used in the HOMER simulation as the wind resource. Fig. 6 show the averaged monthly data from Rehman, based on the 14 years data between 1970 and

4 energy sources. Therefore, this source of energy will be implemented and evaluated for our location in Yanbu to make sure if it is cost effective or not. Fig. 6: Monthly Mean Wind Speed In Yanbu [3] As we know, Saudi Arabia is a country located in the Middle East, with strong demand of the electricity for cooling in the summer. That also matches the simulation results where the electrical load peak is between June and September. We notice that the wind speed during summer is higher than that in winter. Fig. 8: PV Installed Capacity In Saudi Arabia [9] Yanbu has a latitude of and a longitude of The average solar radiation for this specific location is given by HOMER as illustrated in Fig Solar Energy Saudi Arabia in general is one of the best areas to take advantage of solar energy. The annual rate of solar radiation in Saudi Arabia is about 250 w/m2, that s almost double the quantity of solar radiation in most parts of the world [6]. That is also 105 trillion kilowatt hours a day, which is roughly the equivalent of 10 billion barrels of crude oil in energy terms [11]. Fig. 7 shows the global solar radiation map in Saudi Arabia. Fig. 9: Average Solar Radiation In Yanbu [HOMER] Fig. 7: Global Solar Radiation In KSA [13] Solar data provided for this region shows that there is potential for using solar energy as a renewable source. A the most important factor when thinking of utilizing solar energy is the intensity of solar radiation, the longitude and the width and height lines above the sea level, where the strength of solar radiation has the primary role in determining if it is possible to use solar panels or not. Total PV installation capacity is increasing each year in Saudi Arabia as shown in Fig. 8. That means that there is a high potential for using solar energy beside other efficient 4

5 4. RENEWABLE ENERGY PROPOSED DESIGN To satisfy the community energy demand, PV panels and wind turbines has been chosen to establish a grid-connected renewable energy system. No generators are considered in the system because there are no heating loads required. For the initial attempt of simulation, we consider the PV system sizes, 0, 500 and 1000 kw, and the wind turbine quantities to be 0, 5, 10, 15, 20 and 25. The proposed DG design is shown in Fig.10. interval of 10%. The cost of the PV produced electricity is only competitive with grid electricity rate when the rebate level is up to 80%. From the economics aspect, the government rebate is necessary for the PV technology to be applicable. 4.2 Wind Speed Sensitivity Study A sensitivity analysis has been conducted for the wind speed for a grid connected wind farm with the size of 900kW. The scaled annual average wind speed is varied from 2m/s to 9m/s. From Fig. 11, it is noticed that the cost of electricity generated by the wind turbines at the actual wind speed condition is higher than the grid electricity rate. But the wind farm becomes cost-effective, when the annual averaged wind speed increases to 6m/s. On the other hand, the cost of energy wind farm increases rapidly along with the decrease of the annual averaged wind speed. Fig. 10: Proposed DG Design For The Residential Community [HOMER] The preliminary results have shown that the electricity generated by the solar and wind resources is more expensive than that from the grid. The combination of grid and wind turbine is recommended after the grid. The results also indicate that the wind turbine produces cheaper electricity than PV. PV system produced electricity significantly increased the cost of energy (COE). From this initial attempt of simulation, we conclude that the wind turbine and PV system are not cost effective in Yanbu due to the remarkable low grid electricity price. Nevertheless, the fossil fuel based electricity would not maintain such low price forever. The renewable technology will play an importance role in the near future. Therefore, sensitivity analysis is performed to evaluate the influence of various parameters on the cost effectiveness of different options. These parameters include rebate levels for PV, annual wind speed, utility rates and carbon emission penalty. 4.1 PV System Rebate Study Sensitivity study has been conducted on the influence of the rebate level on the cost-effectiveness of the PV system. In HOMER simulation, the PV system is set to be 1000kW, and panel slope equals the longitude of Yanbu city. The range of the rebate level is set to be from 0 to 90%, with Fig. 11: Wind Speed vs. Wind Turbine COE 4.3 Comparison Between Wind Farm And PV Two independent renewable generating systems has been compared: 1) the grid connected to the PV system, with the size varying between 0 and 5MW. 2) the grid connected to the wind farm using the 150kW Nordex N27 turbines, with total capacity varying between 0 and 10.5MW. In the following figures, we plot the renewable fraction vs COE and CO2 emission vs COE. The two figures clearly indicate that the wind farm provide higher renewable fraction than the PV system at the same COE level. What is more, the wind farm can reduce the CO2 emission dramatically, and the CO2 emission can go to negative region because the wind farm generate more electricity than the actual load, then sell the extra electricity back to grid. 5

6 is always the best choice for the community in the economic aspect as shown in Fig. 14. Fig. 12: Wind And PV COE vs Renewable Fraction Fig. 12 shows the simulated renewable fraction at different COE levels. The red line is the simulation results for different sizes of the grid connected wind farm (from left 0kW to right 10.5MW with interval 1.5MW). The blue line is for different sizes of the grid connected PV system (from left 0kW to right 5MW with interval 0.5MW). Fig. 14: Utility Rate & Wind Speed Sensitivity Analysis The similar sensitivity analysis is performed for the PV rebate level and the utility rate as shown in Fig. 15. As expected, as the utility rate decrease, we need more rebate level to reduce the PV system cost and make the PV system cost-effective. Fig. 15: Utility Rate Sensitivity Analysis For PV Cost Fig. 13: COE For Wind And PV vs CO2 Emissions The carbon penalty is also considered for the wind farm. We performed the sensitivity analysis for the carbon emission penalty and the utility rate. Fig. 16 shows that when the CO2 penalty is higher than $40/ton, the wind farm will become the firm solution to reduce the energy cost. Fig. 13 shows the carbon dioxide emission amounts at different COE levels. The red line is the simulation results for different sizes of the grid connected wind farm (from left 0kW to right 10.5MW with interval 1.5MW). The blue line is for different sizes of the grid connected PV system (from left 0kW to right 5MW with interval 0.5MW). 4.4 Sensitivity Analysis For Utility Rate The utility rate is ranged from $0.01/kWh to $0.1/kWh, and the averaged wind speed is set to be from 2m/s to 9m/s. The analysis result intuitively tells that wind farm will be costeffective under high wind speed and high utility rate. However, it is noticed that when the wind speed is below 3m/s, or the utility rate is below $0.02/kWh, the grid utility Fig. 16: Utility Rate & CO2 Penalty Sensitivity Analysis For Wind Energy 6

7 The same sensitivity analysis is also performed for the PV system with various values of carbon emission penalty and utility rate. It is noticed that for the condition with no rebate for PV system, the PV system is only cost-effective under the high utility rate and high CO2 emission penalty assumption. This result indicates that the CO2 penalty cannot significantly help the PV system s cost-effectiveness. Fig. 19 shows the comparison of the different hybrid systems in terms of COE and carbon emission reduction. From this figure we can see that the best system can be the one with the highest carbon emission reduction at the same time has a reasonable COE comparing to the ideal option, which is the grid. In this case as illustrated in Fig. 19 the optimal hybrid DG system gives a carbon reduction of 103% with a COE equals to $/kwh. This hybrid system consists of 71% renewable fraction that include the 40 Nordex N27/150 wind turbines and the grid. Fig. 17: Utility Rate & CO2 Penalty Sensitivity Analysis For PV Energy 4.5 Sensitivity Analysis For The Hybrid System A sensitivity analysis was performed for the annual averaged wind speed and rebate level for the PV system. A total of 90 parameters were evaluated. Fig. 18 shows that the hybrid system is only applicable in the economics aspect, when the wind speed in a small region is over 5.5 m/s and the rebate level for the PV system is over 73%. Fig. 18: Sensitivity Analysis Results For The Hybrid System 4.6 The Optimal Hybrid System For The Community The final optimization analysis process was to find the lowest COE and the highest percentage reduction of carbon emission of the hybrid system. The grid only option has a cost of energy equals to 0.03 $/kwh with carbon emissions equal to 11,649,345 kg/year. Fig. 19: Optimum Hybrid Design Based On COE and CO2 Emission Reduction 5. CONCLUSION A renewable energy feasibility study has been conducted in this case study for a residential community in Yanbu industrial city, Saudi Arabia. The economic analysis is performed for the grid connected to the wind farm, PV system and the hybrid system. The sensitivity analysis is discussed for the different rebate level for the PV system and annual averaged wind speed. The analysis indicates that the wind farm has a good potential in increasing the renewable fraction and decreasing the carbon dioxide emission while maintaining a relative low cost of energy. At the same time, the PV system is still an expensive choice unless the government rebate is raised to a high level. An optimization analysis is conducted to find the optimal DG system that has a relative low cost of energy and a high percentage of carbon emission reduction. The optimal system had a COE equals to $/kwh and significant carbon reduction percentage that equals to 103%. This hybrid system consists of wind turbines and the grid. The fraction of the renewable energy produced by this system is 71%. The real concern, specifically in Yanbu and generally in Saudi Arabia, is pollution. Since the location is in an industrial city, most of the gas emissions come from the 7

8 industrial plants. The residential communities are also contributing in the amount of CO2 emissions released to the environment. Incorporating renewable energy facilities to serve these communities can help decreasing the amount of emissions dramatically. Therefore, from an economic feasibility point of view, renewable energy is not likely to be applicable due to high pricing subsidies of electricity and fuel that lead to low cost of energy comparing to other sources of energy production like renewable sources. Consequently, environment concerns stress more on how the renewable energy is really a necessitate at Yanbu industrial city. In general as we have seen, the trend of energy demand in Saudi Arabia is not only wasting the country s resources and generating pollution, but also leading the country to financial crises. Additionally, the low energy prices, whether subsidized or not, is not healthy for the country s economy in the long term. Finally, Saudi Arabia most have a long term sustainable energy consumption plan to help in involving new sustainable energy sources and more importantly increasing energy efficiency. A comprehensive incentive packages has to be implemented to make the renewable energy production more feasible and attractive. REFERENCES [1] A. Khogali, Wind and Solar Energy Potential in Makkah (Saudi Arabia) Comparison with Red Sea Coastal Sites, 1991 [2] S. A. M. Said, Renewable Energy Potentials in Saudi Arabia [3] S. Rehman, Wind energy resources assessment for Yanbu, Saudi Arabia, August, 2003 [4] E. Al-Ammar, N. Malik, M. Usman, Application of Using Hybrid Renewable Energy in Saudi Arabia, 2011 [5] A. Ahmad, Energy Simulation for a Typical Built With Different Types of Masonry Building Materials, October 2004 [6] E. Al-Ammar, A. Al-Aotabi, Feasibility Study of Establishing a PV Power Plant to Generate Electricity in Saudi Arabia from Technical, Geographical, and Economical Viewpoints, March 2010 [7] S. Rehman, Wind energy resources assessment for Yanbo, Saudi Arabia, November 2003 [8] N. Alabbadi, Wind energy resource assessment for five locations in Saudi Arabia, December 2004 [9] S. Rehman, Saudi Arabian Geothermal Energy Resources, April 2010 [10] Yousef, Yanbu industrial city, < January 2005 [11] Royal embassy of Saudi Arabia, About Saudi Arabia, Solar energy, < diembassy.net/about/country-information/energy/ solar_energy.aspx>, October 2011 [12] Electricity and Co-Generation Regulatory Authority, Electric Energy Production Costing for The Saudi Electricity Sector, November 2004 [13] M. Monads and S. Rehman, Global solar radiation of Saudi Arabia, King Fahad University of Petroleum and Minerals, January 2009 [14] Marafiq, Power and water utility company for Jubail and Yanbu. Power generation and distribution in Yanbu [15] Gulfnews, Saudi Arabia excludes homes from increased power prices, < January 2011 [16] IER, Countries subsidize fossil fuel consumption, creating artificially lower prices, < November 2011 [17] Allam, A, Subsidies give saudies an appetite for oil, < feabdc0,Authorised=false.html?_i_location=http%3A%2F%2Fwww.ft.com%2Fcms %2Fs%2F0%2F110337b6-7cbd-11e0-994d feabdc0.html&_i_referer=#axzz1kov39Lst>, May 2011 [18] Lahn, G. and Stevens, P., Burning Oil to Keep Cool, The Hidden Energy Crisis in Saudi Arabia, December