alizadeh M, jafari M, shahabi M. Resiliency improvement of distribution network considering the charge/discharge management of electric vehicles in parking lots through Bi-level optimization approach. Journal of Iranian Association of Electrical and Electronics Engineers 2022; 19 (4) :195-211
URL:
http://jiaeee.com/article-1-1345-en.html
Faculty of Electrical and Computer Engineering, Imam Khomeini maritime University, nowshahr
Abstract: (1115 Views)
Due to the growing use of Plug-in Electric vehicles in transportation networks, scheduling the charge/discharge of electric vehicles in parking lots can have great impacts on the distribution network's resiliency. This paper presents a Bi-level optimization model to improve the resiliency of the distribution network that takes into account the interaction between the distribution network islanding problem and the charge/discharge scheduling of electric vehicles in available parking lots. In the upper-level problem, regarding the electrical loads and managing the charge/discharge of electric vehicles in electrified parking lots, the island boundaries are determined with the aim of maximize the load restoration. By knowing the islands' boundaries and restored parking lots from the upper-level problem, the changes in destination parking lots and travels characteristics are determined in lower-level problem to minimize the shortest path between the out-of-service destinations and in-service parking lots. The proposed model has been implemented and validated through applying several concurrent faults to the 118-bus active distribution network in presence of electric vehicles in the 25-node traffic network. A combination of mathematical programming and the evolutionary algorithm is applied to reach the final solution. The case studies' results confirm the efficiency of the proposed model for improving the resiliency of distribution networks with managing the charge/discharge of electric vehicle fleets in restored parking lots.
Type of Article:
Research |
Subject:
Power Received: 2021/07/6 | Accepted: 2021/11/7 | Published: 2022/10/28