اثرات محدودیت منابع آبی بر برنامه‌ریزی گسترش ظرفیت تولید برق: کاربرد الگوی چند هدفه تحت شرایط نااطمینانی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری علوم اقتصادی دانشکده مدیریت و اقتصاد دانشگاه شهید باهنر کرمان

2 دانشیار گروه اقتصاد دانشکده مدیریت و اقتصاد دانشگاه شهید باهنر کرمان، کرمان، ایران

3 استاد گروه اقتصاد دانشکده مدیریت و اقتصاد دانشگاه شهید باهنر کرمان

4 دانشیار گروه مهندسی برق- قدرت دانشکده مهندسی دانشگاه شهید باهنر کرمان، کرمان، ایران

چکیده

هدف مطالعه حاضر، برنامه‌ریزی گسترش ظرفیت تولید برق با تأمین همزمان اهداف اقتصادی و زیست محیطی تحت نا‌اطمینانی جهت تأمین تقاضای برق است. نا‌اطمینانی­ تقاضا و ضریب ظرفیت تولیدی برق (نا‌اطمینانی­ عرضه) به صورت یک مجموعه فازی بیان شد. همچنین، اثرات محدودیت منابع آبی بر برنامه گسترش ظرفیت تولید بررسی گردید. الگوی غیرخطی چند هدفه فازی برای یک نمونه واقعی سیستم برنامه‌ریزی گسترش ظرفیت تولید برق استان کرمان برای یک دوره 12 ساله با و بدون محدودیت منابع آبی به کار گرفته شد. نتایج نشان داد که محدودیت منابع آبی باعث تغییر برنامه گسترش ظرفیت استان خواهد شد. با در نظر گرفتن محدودیت منابع آبی، ظرفیت نیروگاه­های بادی، گاز-چرخه ترکیبی و فتوولتائیک در طول افق برنامه‌ریزی به ترتیب 1000، 950/924 و 500 مگاوات افزایش خواهد یافت. این در حالی است که نتایج الگو بدون محدودیت منابع آبی نشان داد که در طول افق برنامه‌ریزی ظرفیت نیروگاه­های بادی، آبی و زغال سنگ به ترتیب 1000، 130/983 و 720/163 مگاوات افزایش می‌یابد. بنابراین برای مناطقی که در شرایط بحرانی منابع آب قرار دارند، تولید کمتر برق با سوخت زغال سنگ و آبی پیشنهاد می‌شود. تفاوت در نتایج، اهمیت تحلیل یکپارچه و جامع برنامه‌ریزی گسترش ظرفیت تولید برق را نمایان می‌سازد.

کلیدواژه‌ها


عنوان مقاله [English]

Effects of Water Resources Limitation on Capacity Expansion Planning of Power Generation: An Application of Multi-Objective Model under Uncertainty Conditions

نویسندگان [English]

  • Yahya Hatami 1
  • Zeinolabedin Sadeghi 2
  • Seyed Abdolmajid Jalaei 3
  • Amir Abdollahi 4
1 PhD Candidate in Economics, Faculty of Managemnt and Economics, Shahid Bahonar University of Kerman
2 Associate Professor of Economics, Faculty of Managemnt and Economics, Shahid Bahonar University of Kerman, Kerman, Iran
3 Professor of Economics, Faculty of Managemnt and Economics, Shahid Bahonar University of Kerman, Kerman, Iran
4 Associate Professor of Electrical Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman
چکیده [English]

The purpose of the present study is capacity expansion planning of power generation by simultaneously achieving economic and environmental objectives under uncertainty to meet electicity demand. Uncertainty in demand and power generation capacity factor (supply uncertainty) were expressed as a fuzzy set. Also, the effects of water resources limitation were investigated on power generation capacity expansion planning. Fuzzy multi-objective non-linear model was used for a case study of Kerman power generation capacity expansion planning system for a 12-year period with and without water resources limitation. The results show that water resource limitation will change the province power capacity expansion plan. Considering the water resources limitation, capacity of wind, gas-cycle combined and photovoltaic plants are increased 1000, 924.950 and 500 MW respectively during the planning horizon.The results of model without water resources limitation show that capacity of wind, hydro and coal fuel are increased 1000, 983.130 and 163.720 MW during planning horizon. Therefore, less power generation of coal fuel and hydro are suggested for area that are in critical conditions of water resources. The difference in results reveals the importance of integrated and comprehensive planning for the power generation capacity expansion.

کلیدواژه‌ها [English]

  • Power Generation Capacity Expansion Planning
  • Fuzzy Multi-objective Non-linear Model
  • Water Resources Limitation
- Beard, L. M., Cardell, J. B., Dobson, I., Galvan, F., Hawkins, D., Jewell, W. & Tylavsky, D. J. (2010). Key technical challenges for the electric power industry and climate change. IEEE Transactions on Energy Conversion, 25(2), 465-473.

- Bistline, J. E. (2016). Electric sector capacity planning under uncertainty: Climate policy and natural gas in the US. Energy Economics, 51, 236-251.

- Charitopoulos, V. M., & Dua, V. (2017). A unified framework for model-based multi-objective linear process and energy optimisation under uncertainty. Applied Energy, 186, 539-548.

- Edalati, S., Ameri, M., Iranmanesh, M. & Sadeghi, Z. (2017). Solar photovoltaic power plants in five top oil-producing countries in Middle East: A case study in Iran. Renewable and Sustainable Energy Reviews, 69, 1271-1280.

- El-Khattam, W., Hegazy, YG. & Salama, MMA. (2005). An integrated distributed generation optimization model for distribution system planning. IEEE Transaction on Power Systems, 20(2):1158–65.

- Fazlollahi, S. & Maréchal, F. (2013). Multi-objective, multi-period optimization of biomass conversion technologies using evolutionary algorithms and mixed integer linear programming (MILP). Applied Thermal Engineering, 50 (2), 1504-1513.

- Hu, Y., Bie, Z. H., Ding, T. & Lin, Y. (2016). An NSGA-II based multi-objective optimization for combined gas and electricity network expansion planning. Applied Energy, 167, 280-293.

- Huang, G.H., Zhang, X.Y., Zhu, H. & Li, Y.P. (2017). A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties. Energy, 123, 664-676.

- Jin, S. W., Li, Y. P., Huang, G. H., Hao, Q. and Nie, S. (2015). Development of an integrated optimization method for analyzing effect of energy conversion efficiency under uncertainty – A case study of Bayingolin Mongol Autonomous Prefecture, China. Energy Conversion and Management, 106, 687-702.

- Li, Y. F., Huang, G. H., Li, Y. P., Xu, Y. & Chen, W. T. (2010). Regional-scale electric power system planning under uncertainty—A multi stage interval-stochastic integer linear programming approach. Energy Policy, 38, 475-490.

- Li, FF. & Qiu, J. (2015). Multi-objective optimization for integrated hydro–photovoltaic power system. Applied Energy, 167, 377-384.

- Lin, Q.G., Huang, G.H., Bass, B. & Qin, X.S. (2009). An interval-fuzzy two-stage stochastic optimization model for regional energy system planning under uncertainty. Energy Policy, 37, 868-878.

- Macknick, J., Sattler, S., Averyt, K., Clemmer, S., & Rogers, J. (2012). The water implications of generating electricity: water use across the United States based on different electricity pathways through 2050. Environmental Research Letters, 7(4), 1-10.

- Marler, RT. & Arora, JS. (2004). Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization26(6), 369–395.

- Martin, M. A., Cuadrado, M. L. & Romero, C. (2011). Computing efficient financial strategies: An extended compromise programming approach. Applied Mathematics and Computation, 217, 7831-7837.

- Maulbetsch, S. & Michael, N. (2006). Cost and Value of Water Use at Combined Cycle Power Plants, California Energy Commission.

- McDermott, R. & Nilsen, A. (2014).Electricity prices, river temperatures, and cooling water scarcity. Land Economics, 90 (1), 131–148.

- Monsef, H., Bagheri, A. & lesani, H. (2015). Integrated distribution network expansion planning incorporating distributed generation considering uncertainties, reliability, and operational conditions. Electrical Power and Energy Systems, 73, 56-70.

- Razavi, S. A. & Ahmadi-Shadmehri, M. T. (2014). Investigating the factors influencing the demand for electricity in service providing sector using Firefly and Cuckoo algorithmsJournal of Economics and Modelling, 5, 111-134.(In Persian).

- Ricardo, J., Sailor, J. (1998) .A modelling methodology for assessing the impact of climate variability and climatic change on hydro-electric generation. Energy Conversion Management, 39 (14), 1459–1469.

- Sadeghi, H., Abdollahi, A., & Rashidinejad, M. (2015). Evaluating the impact of FIT financial burden on social welfare in renewable expansion planning. Renewable Energy, 75, 199-209.

- Schewe, J., Heinke, J., Gerten, D., Haddeland, I., Arnell, W., Clark, B., Dankers, R., Eisner, S., Fekete, M., Colón-González, J. & et al. (2014). Multi model assessment of water scarcity under climate change. Proceedings of the National Academy of Sciences111 (9), 3245–3250.

- Sharifi, A. R., Kalin, L. & Tajrishi, M. (2013). A system dynamics approach for hydropower generation assessmant in developing watersheds: A case study of Karkheh river basin. Journal of Hydrologic Engineering, 18 (8), 1007-1017.

- Statistical Review of World Energy. (2016). http://www.bp.com/statistical review.

- Tong, LI., Saminathan, R. & Chang, CW. (2016). Uncertainty assessment of non-normal emission estimates using non-parametric bootstrap confidence intervals. Journal Environmental of Informatics, 28(1), 61-70.

- Wu, Y. & Guu, S. (2001). A compromise model for solving fuzzy multiple objective linear programming problems. Journal of the Chinese Institute of Industrial Engineers, 18 (5), 87-93.

- Zhang, X. Y., Huang, G. H., Zhu, H. & Li, Y. P. (2017). A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties. Energy, 123, 664-676.

- www.www.amar.org.ir