A MILP Model Incorporated With the Risk Management Tool for Self-Healing Oriented Service Restoration
سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 65
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شناسه ملی سند علمی:
JR_JOAPE-12-1_001
تاریخ نمایه سازی: 13 آبان 1402
چکیده مقاله:
The inevitable emergence of intelligent distribution networks has introduced new features in these networks. According to most experts, self-healing is one of the main abilities of smart distribution networks. This feature increases the reliability and resiliency of networks by reacting fast and restoring the critical loads (CLs) during a fault. Nevertheless, the stochastic nature of the components in a power system imposes significant computational risk in enabling the system to self-heal. In this paper, a mathematical model is introduced for the self-healing operation of networked Microgrids (MGs) to assess the risk in the optimal service restoration (SR) problem. Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) and their stochastic nature besides the distributed generation units (DGs), the ability to reconfiguration, and demand response program are considered simultaneously. The objective function is designed to maximize the restored loads and minimize the risk. The Conditional Value-at-Risk (CVaR) is used to calculate the risk of the SR as one of the most efficient and famous risk indices. In the general case study and considering \beta equal to the ۰, ۱, ۲, ۳, and ۴, expected values of SR for the risk-averse problem is ۲۱.۲, ۲۰, ۱۹.۳, ۱۹.۱, and ۱۹\% less than the risk-neutral problem, respectively. The formulation of the problem is mixed-integer linear programming (MILP), and the model is tested in the modified Civanlar test system. The analysis of several case studies has proved the performance of the proposed model and the importance of risk management in the problem.
کلیدواژه ها:
نویسندگان
N. Afsari
Department of Technical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
S.J. SeyedShenava
Department of Technical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
H. Shayeghi
Department of Technical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
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