Optimal Allocation of Renewable Energy Sources to Enhance Distribution System Reliability with Confidence Interval Considerations

سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 34

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شناسه ملی سند علمی:

JR_JOAPE-13-4_008

تاریخ نمایه سازی: 7 اردیبهشت 1404

چکیده مقاله:

Due to ever-increasing energy requirements, modern distribution systems are integrated with renewable energy sources (RESs), such as wind turbines and photovoltaics. They also bring economic, environmental, and technical advantages. However, they face the network operator with decision-making challenges due to their uncertain nature. Modern distribution systems usually operate at safety margins, and any contingency may lead to power supply losses. In this regard, any attempts to increase the planner/operator's awareness of the network situation will help improve the decision quality. This paper determines the optimal locations of the RESs to enhance the expected power not served as a reliability index. Besides, it reduces power losses and minimizes the ۹۵\% confidence interval of power losses, as much as possible for having more awareness of network states. The K-medoids data clustering method is applied to handle the uncertainties of the RESs and demand loads. The MOPSO, NSGA II, and MOGWO algorithms are used to solve the proposed problem. The efficiency of the proposed approach is tested on the IEEE standard ۳۳-bus and ۱۱۸-bus distribution networks. The obtained results show that it is possible to reach a better confidence interval while keeping the losses and reliability index at a desired level. Considering solutions with identical losses and reliability index, the confidence interval of power losses using the MOPSO algorithm is ۶.۸۶% and ۳۹.۸۲% better rather than the NSGA II and MOGWO algorithms in the ۳۳-bus distribution network and it is ۳۰.۲۳% and ۱۲۹.۶۳% better in the ۱۱۸-bus distribution network.

نویسندگان

Mahdi Hajibeigy

Department of Power Engineering, Faculty of Electrical and Computer Engineering, Urmia University, Urmia, Iran.

Vahid Talavat

Department of Power Engineering, Faculty of Electrical and Computer Engineering, Urmia University, Urmia, Iran.

Sadjad Galvani

Department of Power Engineering, Faculty of Electrical and Computer Engineering, Urmia University, Urmia, Iran.

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