Economic Evaluation of Whole Life Cycle of the Micro-grid System Under the Mode of Residual Power Connection/Hydrogen Production

被引:0
作者
Sun C. [1 ]
Li Q. [1 ]
Qiu Y. [1 ]
Ai Y. [1 ]
Li R. [1 ]
Huang L. [1 ]
Chen W. [1 ]
机构
[1] School of Electrical Engineering, Southwest Jiaotong University, Chengdu
来源
Li, Qi (liqi0800@163.com) | 1600年 / Power System Technology Press卷 / 45期
基金
中国国家自然科学基金;
关键词
Adaptive particle swarm optimization; Bilevel optimization; Cost-benefit analysis; Distributed power capacity configuration; Hydrogen production by surplus electricity;
D O I
10.13335/j.1000-3673.pst.2021.0090
中图分类号
学科分类号
摘要
In order to comprehensively evaluate the economy of the microgrid system under different operation modes, this paper, from the perspective of the whole society, comprehensively analyzes the cost and benefit of the microgrid system under the two operation modes of surplus electricity online and surplus electricity hydrogen production. Considering the influence of different types and capacities of distributed power on the performance of microgrid system, this paper firstly studies the constant volume problem of distributed power in microgrid. Under the premise of satisfying the specific constraints, a two-level optimization model of microgrid system is established with the objective function of maximizing the comprehensive benefits of the whole life cycle. In this two-layer optimization model, adaptive particle swarm optimization algorithm is used to solve the optimal configuration of the system in the upper optimization model, and CPLEX solver is used to solve the optimal scheduling scheme in the lower optimization model. On this basis, the economic evaluation model of the whole life cycle is used to make a comparative analysis of the costs, benefits and self-balance rate under the optimal configuration of the specific example, and the conclusion is drawn that the operation mode of residual electricity hydrogen production plan is more economic. © 2021, Power System Technology Press. All right reserved.
引用
收藏
页码:4650 / 4659
页数:9
相关论文
共 25 条
  • [11] XU Shisen, ZHANG Ruiyun, CHENG Jian, Et al., Application and development of electrolytic hydrogen production and high temperature fuel cell in electric power industry, Proceedings of the CSEE, 39, 9, pp. 2531-2537, (2019)
  • [12] JIN Xue, ZHUANG Yuxuan, WANG Hui, Et al., Feasibility analysis research on abandoning wind and solar energy with hydrogen energy storage technology, Electrician, 4, pp. 63-68, (2019)
  • [13] CHEN Zhaoyu, WANG Dan, JIA Hongjie, Et al., Research on optimal day-ahead economic dispatching strategy for microgrid considering P2G and multi-source energy storage system, Proceedings of the CSEE, 37, 11, pp. 3067-3077, (2017)
  • [14] DONG Weiqiang, LI Yanjun, JI Xiang, Optimal sizing of a stand-alone hybrid power system based on battery/hydrogen with an improved ant colony optimization, Energies, 9, 10, (2016)
  • [15] CHEN Jian, WANG Chengshan, ZHAO Bo, Et al., Optimal sizing for stand-alone microgrid considering different control strategies, Automation of Electric Power Systems, 37, 11, pp. 1-6, (2013)
  • [16] LIANG Huishi, CHENG Lin, SU Jian, Cost benefit analysis for microgrid, Proceedings of the CSEE, 31, pp. 38-44, (2011)
  • [17] SUN Ke, Environmental cost analysis and research of different power plants, Energy Engineering, 3, pp. 23-26, (2004)
  • [18] WU Yaowen, MA Xiyuan, SUN Yuanzhang, Et al., Overall economic evaluation and analysis of accession of microgrids with high penetration, Power System Protection and Control, 40, 13, pp. 49-54, (2012)
  • [19] SHI Y, EBERHART R., A modified particle swarm optimizer, IEEE International Conference on Evolutionary Computation Proceedings, pp. 69-73, (1998)
  • [20] LUO Yi, ZHANG Ruohan, Immune particle swarm optimization and application based on dynamically changing learning factors, Power System and Clean Energy, 30, 2, pp. 76-80, (2014)