Energy management of a smart autonomous electrical grid with a hydrogen storage system

被引:54
作者
Chamandoust, Heydar [1 ]
Hashemi, Abozar [2 ]
Bahramara, Salah [3 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Damavand Branch, Tehran, Iran
[2] Islamic Azad Univ, Dept Elect Engn, Shahr E Qods Branch, Tehran, Iran
[3] Islamic Azad Univ, Dept Elect Engn, Sanandaj Branch, Sanandaj, Iran
关键词
Energy management; Hydrogen storage system; Multi-objective optimization; approach; Responsive consumers; Shuffled frog leaping algorithm; POWER-SYSTEM; DESALINATION SYSTEMS; OPTIMIZATION; DESIGN; PERFORMANCE; MICROGRIDS; PV;
D O I
10.1016/j.ijhydene.2021.02.174
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The problem of energy management in the smart autonomous electrical grids (SAEGs) is a main challenge in the active distribution networks. In such systems, the operator of the network decides on the optimal scheduling of the resources to supply the local demand. In this paper, a multi-objective optimization model is developed for a SAEG considering responsive consumers (RCs) and a hydrogen storage system (HSS). The objective functions are maximizing the reliability and minimizing both the operation cost and the gap between the energy consumption and its optimal value. The participation of the RCs is modeled through the demand shifting strategy and the local generation of the plug-in electric vehicles. To model the uncertainties of the renewable energy sources and the demand, the Monte Carlo simulation approach is used. The resulted model is solved using the shuffled frog leaping algorithm (SFLA) regarding which the non-dominated solutions are generated. Then, the best solution is obtained using the fuzzy and the weighted sum methods. To investigate the effectiveness of the proposed model, it is applied on a 24-node test system through defining four case studies. The results shown that in the presence of the RCs and the HSS, the operation cost and the reliability of the system both improve. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:17608 / 17626
页数:19
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