Analysis of Relationship between Climatic Variables and Electricity Consumption and Estimated Demand by General Circulation Models in Western Iran

Document Type : Full length article


1 MA in Climatology, Geography Department, Razi University, Kermanshah, Iran

2 Associate Professor of Climatology, Geography Department, Razi University, Kermanshah, Iran


Electricity energy has no storage capacity on a large scale. Given the importance of this energy in various programs and increasing consumption in the context of global warming, it seems necessary to forecast its future consumption with in the energy sector policy. Therefore, awareness of the variables affecting electricity consumption and the impact of each of them will enable policy makers to make more precise planning and prediction of electricity consumption in the coming years. Therefore, accurate estimation of the consumption with regard to climatic conditions can play an important role in the economic use of electrical energy. The purpose of this research is to investigate the relationship between climatic variables with electricity consumption and prediction of electricity consumption under the influence of climate change in western Iran.
Materials and methods 
The study area of this research is western Iran including provinces of Kermanshah, Kurdistan, Hamedan, Ilam and Lorestan. This region has a variety of climate conditions due to its location on the path of hot and cold air masses and mid-latitude cyclones. The data used in this study are including 1) meteorological data of 13 stations in the region over a 28-year period (1987 to 2014), including minimum temperature, maximum temperature, relative humidity, wind speed, sunshine hours and rainfall, 2) data on monthly electricity consumption during the corresponding period, 3) data simulated by CCSM4 General Circulation Model. To calculate the heating and cooling requirements, values of Heating Degree Days (HDD) and Cooling Degree Days (CDD) were calculated using the minimum and maximum temperature data. First, the relationship between climatic variables and electricity consumption at stations was modeled using multiple regression equations. In the case of significant models based on the data of the CCSM4 model, the electricity consumption at the stations during the period 2080-2080 was estimated under two scenarios RCP4.5 and RCP8.5. Future climate scenarios were then downscaled using the "change factor" method. To verify the downscaled data, we used the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R2).
Results and discussion
At all stations, the CDD have a direct and significant relationship with electricity consumption, due to the high consumption of air conditioning/cooling equipment in summer. But the relationship between the HDD and electricity consumption is weaker than the CDD; because in winter, less electricity is used to heat the environment. Especially in warm stations such as Ilam, Dehloran and Sarpole-Zahab, the relationship between the HDD and electricity consumption is not substantially significant. At these stations, during the cold season due to the mildness and shortness of the cold, there is little need for electrical equipment for heating purposes. In contrast, in these three stations, humidity has a significant and inverse relationship with electricity consumption. Other climatic parameters have no significant relationship with the consumption. The mean maximum and minimum temperatures in the region in the future period (2021-2080) will increase on average under the RCP4.5 scenario by 1.95ºC and 2.01ºC, respectively, and under the RCP8.5 scenario by 3.46ºC and 3.81ºC. Therefore, electricity consumption at all stations in the upcoming period (2021-2080) will increase more than the past period. This increase will be much higher in the warm period of the year. The average increase in consumption during the warm period at the stations under the two scenarios will be 80% and 150%, respectively. Particularly warm stations in the west of the region, such as Dehloran, Sarpole-Zahab and Ilam in the warm months (6 months, from May to October) will experience the highest increase in electricity consumption under two scenarios, about 110% and 210%, respectively. The lowest increase in demand for electricity in the upcoming period is related to the relatively cold stations of Hamedan, Sanandaj, Saqez and Bijar. Because of the mountainous nature, the high altitude and the longer cold period, the main need of these stations is heating, a significant part of which is supplied by natural gas. This clearly has little dependence on electricity. During the warm period of these stations, which is shorter and lasts for 4 months (June to September), the increase in consumption is lower than that in warm stations and under the two scenarios, it would be about 60% And 110%, respectively. Other stations like Khorramabad, Kermanshah, Kangavar, Boroujerd and Islamabad will have an intermediate level of consumption. However, it should be noted that regardless of the increase, electricity supply for larger and more populous cities such as Kermanshah and Hamedan will be more important than warm cities. There is not much increase in consumption in cold-period months at any warm and cold station.
Since a significant part of the electricity consumption in the region is due to the use of conditioning/cooling equipment, any change in temperature during the warm period will be effective on increasing or decreasing trends using  the equipment, and consequently, increasing power consumption. Given the significant increase in the temperature of the region during the 2021-2080 period under the two scenarios, it is necessary to take appropriate strategies to deal with the drastic increase in electricity consumption in the future, especially during the warm period of the year.  


Main Subjects

اکبری شهر‏بندی، ز.؛ رمضانی، ف. و مؤتمنی، ه. (1394). پیش‏بینی مصرف انرژی الکتریکی با استفاده از مدل رگرسیون (مطالعة موردی شرکت توزیع نیروی برق مازندران)، کنفرانس ملی فناوری، انرژی، و داده با رویکرد مهندسی برق و کامپیوتر، کرمانشاه، ص ۱۱۳۴-1140.
آشفته، پ.‏س. و مساح ‏بوانی، ع.ر. (1389). تأثیر تغییر اقلیم بر دبی‏های حداکثر: مطالعۀ موردی، حوضة آیدوغموش، آدربایجان شرقی، علوم و فنون کشاورزی و منابع طبیعی، 14(۵۳): ۲۵-39.
بابائیان، ا.؛ عرفانی، ع.؛ کریمیان، م. و مدیریان، ر. (1393). شبیه‏سازی اثر تغییر اقلیم بر مصرف برق کشور در دورۀ 2۰۱1-2۱۰0 با استفاده از ریزمقیاس‏نمایی برونداد مدل گردش عمومی جو، دهمین همایش بینالملی انرژی، تهران.
بابائیان، ا.؛ عرفانی، ع.؛ انتظاری، ع. و باعقیده، م. (1395). چشم‏انداز مصرف برق کشور در دورۀ ۲۰۱۱-2100 تحت شرایط تغییر اقلیم با استفاده از ریزمقیاس‏نمایی برونداد مدل‏های گردش عمومی جو، جغرافیا و برنامه‏ریزی محیطی، 27(۴): ۱۳۱-144.
ترابی، م.؛ روزبه، م. و هاشمی، س. (1394). حساسیت مصرف کوتاه‏مدت انرژی الکتریکی نسبت به دما و رطوبت، سومین کنفرانس بینالمللی پژوهش‏های کاربردی در مهندسی برق، مکانیک و مکاترونیک، تهران، ص ۱-11.
جعفرپور، ش. و کانونی، ا. (1394). سناریوهای تغییر اقلیم در گزارش پنجم هیئت بین‏الدول تغییر اقلیم و مقایسة آن با گزارش قبلی، دومین همایش ملی صیانت از منابع طبیعی و محیط زیست، اردبیل، دانشگاه محقق اردبیلی.
جلایی، س.‌‏ع.؛ جعفری، س. و انصاری لاری، ص. (1392). برآورد تابع تقاضای برق خانگی در ایران با استفاده از داده‏های تابلویی استانی، فصل‏نامۀ اقتصاد انرژی ایران، 2(۸): ۶۹-92.
شکوری گنجوی، ح. و نظرزاده، ج. ‏(1383). مطالعۀ اثر تغییرات دمای هوا بر میانگین زمان مصرف روزانۀ انرژی الکتریکی درکشور، نشریة انرژی ایران، 9(۲۰): ۲۷-40.
علیجانی، ب.؛ شمسیپور، ع.ا. و مطمئن آرانی، ع. (1396). تحلیل آماری بحران‏های دمایی شهر قم در رابطه با مصارف انرژی، جغرافیا و مخاطرات محیطی، ۶(۲۱): ۱-17.
لطفعلی‏پور، م.ر.؛ چشمی، ع. و پاکرو، ب. (1392). مقایسة الگوهای رشد لجستیک، لجستیک هاروی، و هاروی در پیش‏بینی مصرف برق بخش‏های اقتصادی در ایران، نظریه‏های کاربردی اقتصاد، 1(۳): ۵۷-80.
محمدی، ا.؛ یزدان‏پناه، ح. و محمدی، ف. (1393). بررسی رخداد تغییر اقلیم و تأثیر آن بر زمان کاشت  و طول دورة رشد گندم دوروم (دیم) مطالعة موردی: ایستگاه سرارود کرمانشاه، پژوهش‏های جغرافیای طبیعی، 46(۲): ۲۳۱-246.
مسعودیان، س.ا.؛ علیجانی، ب. و ابراهیمی، ر. (1390). واکاوی میانگین مجموع درجه- روز مورد نیاز (گرمایش و سرمایش) در قلمرو ایران، جغرافیا و پایداری محیط، 1(۱): ۲۳-36.
مسعودیان، س.ا.؛ ابراهیمی، ر. و محمدی، م. (1393). پهنهبندی مکانی- زمانی نیاز گرمایش و سرمایش فصلی و سالانة ایران، اطلاعات جغرافیایی (سپهر)، 23(۹۰): ۸۳-90.
یاوری، ک. و ذوالفقاری، م. (1391). مدل‏سازی و پیش‏بینی مصرف کوتاه‏مدت برق کشور با استفاده از شبکه‏های عصبی و تبدیل موجک (با تأکید بر اثرات محیطی و اقلیمی)، فصلنامۀ مطالعات اقتصاد انرژی، 9(۳۳): ۱-29.
Akbari Shahbandi, Z.; Ramezani, F. and Motameni, H. (2015). Estimation of Electricity Consumption Using Regression Model (Case Study of Mazandaran Power Distribution Company), National Conference of Technology, Energy and Data on Electrical & Computer Engineering, Kermanshah, pp. 1134-1140.
Alijani, B.; Shamsipour, A.A. and Motmaen Arani, A. (2017). Statistical Analysis of Thermal Crisis of Qom in Relation to Energy Consumption, Geography and Environmental Hazards, 6(21): 1-13.
Al-Zayer, J. and Al-Ibrahim, A.A. (1996). Modelling the Impact of Temperature on Electricity Consumption in the Eastern Province of Saudi Arabia, Journal of Forecasting, 15(2): 97-106.
Ashofteh, P. and Massah Bouani, A.R. (2010). Impact of Climate Change on Maximum Discharges: Case Study of Aidoghmoush Basin, East Azerbaijan, Journal of Water and Soil Science (Science and Technology of Agriculture and Natural Resources), Vol. 14(53): 25-39.
Babaeian, I.; Erfani, A.; Karimian, M. and Modirian, R. (2014). Simulation of the Climate Change Effect on Iran's Electricity Consumption in the Period of 2011-2100 using Downscaling of Output of the General Circulation Model, The 10th International Energy Conference, Tehran.
Babaeian, I.; Erfani, A.; Entezari, A. and Baaghideh, M. (2016). Future Perspective of Electricity Consumption in Iran during the Period 2011-2100 under Climate Change Scenarios using Downscaling of General Circulation Models, Geography and Environmental Planning, 27(4): 131-144.
Beccali, M.; Cellura, M.; Lo Brano, V. and Marvuglia, A. (2008). Short-Term Prediction of Household Electricity Consumption: Assessing Weather Sensitivity in a Mediterranean Area, Renewable and Sustainable Energy Reviews, 12: 2040-2065.
Bessec, M. and Fouquau, J. (2008). The Non-Linear Link between Electricity Consumption and Temperature in Europe: A Threshold Panel Approach, Energy Economics, 30: 2705-2721.
Damm, A.; Koberl, J.; Prettenthaler, F.; Rogler, N. and Christoph, T. (2017). Impacts of +2ºC global Warming on Electricity Demand in Europe, Climate Services, 7: 12-30.
Hor, C.L.; Watson, S.J. and Majithia, S. (2005). Analyzing the Impact of Weather Variables on Monthly Electricity Demand, IEEE Transactions on Power Systems, Vol. 20(4): 2078-2085.
Jafarpoor, Sh. and Kanooni, A. (2015). Climate Change Scenarios in the Fifth Report of the Intergovernmental Panel on Climate Change (IPCC) and its Comparison with the Previous Report, 2nd National Conference on Natural Resources and Environmental Conservation, Ardebil, University of Mohaghegh Ardabili.
Jalaee, S.A.; Jafari, S. and Ansari Lari, S. (2013). The Estimation of Electricity Consumption in the Residential Sector in Iran: A Provinces Panel, Journal of Iranian Energy Economics, 2(8): 69-92.
Jovanovic, S.; Savic, S.; Bojic, M.; Djordjevic, Z. and Nikolic, D. (2015). The Impact of the Mean Daily Air Temperature Change on Electricity Consumption, Energy, 88: 604-609.
Kamerschen, D.R. and Porter, D.V. (2004). The Demand for Residential, Industrial and Total Electricity 1973-1998, Energy Economics, 26: 87-100.
Lotfalipour, M.R.; Cheshmi, A. and Pakroo, B. (2015). Comparison of Logistic, Harvey-logistic and Harvey Models for forecasting electricity consumption of Consumer Sectors in Iran, Applied Theories of Economics, 1(3): 57-80.
Masoodian, S.A.; Alijani, B. and Ebrahimi, R. (2012). A Tempo-Spatial Survey of Degree Day (Heating and Cooling) in Iran, Geography and Sustainability of Environment, Vol. 1(1): 23-36.
Masoodian, S.A.; Ebrahimi, R. and Mohammadi, M. (2014). Spatial- Temporal Zoning of Iran's Seasonal and Annual Heating and Cooling Requirements, Geographical Data (Sepehr), 23(90): 83-90.
Mohammadi, E.; Yazdanpnah, H. and Mohammadi, F. (2014). Event of Climate Change, its Impact on Durum Wheat Planting and Duration of Growing Season, Case Study: Station of Sararood, Kermanshah, Physical Geography Research Quarterly, 46(2): 231-246.
Shkoori Ganjavi, H. and Nazarzadeh, J. (2004). Study of the Effect of Air Temperature Changes on Average Daily Electricity Consumption in Iran, Iranian Journal of Energy, 9(20): 27-40.
Torabi, M.; Roozbeh, M. and Hashemi, S. (2015). Short-Term Electrical Energy Sensitivity to Temperature and Humidity, 3rd National and first International Conference in Applied Research on Electrical, Mechanical and Mechatronics Engineering, Tehran, pp. 1-11.
Vine, E. (2008). Adaptation of California’s Electricity Sector to Climate Change, Public Policy Institute of California, San Francisco, CA.
Vu, D.H.; Muttaqi, K.M. and Agalgaonkar, A.P. (2014). Assessing the Influence of Climatic Variables on Electricity Demand, in IEEE Power and Energy Society General Meeting, pp. 1-5.
Yan, Y.Y. (1998). Climate and Residential Electricity Consumption in Hong Kong, Energy, 23(1): 17-20.
Yavari, K. and Zolfaghari, M. (2012). Modeling and Predicting Short-Term Power Consumption of Iran using Neural Networks and Wavelet Transform (with Emphasis on Environmental and Climatic Effects), Quarterly Energy Economics Review, 9(33): 1-29.