风-光-抽水蓄能联合发电系统的优化运行

  • 杨森 ,
  • 张青 ,
  • 高立艾
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杨森(1995—),男,河北保定人,河北农业大学在读硕士研究生,主要从事地方电力系统及其自动化研究.
E-mail: 779488410@qq.com

收稿日期: 2020-04-07

  网络出版日期: 2021-02-05

基金资助

河北省重点研发计划项目(20327307D);河北省高等学校科学技术研究重点项目(ZD2020145)

Optimal operation of wind-light-pumped storage combined power generation system

  • YANG Sen ,
  • ZHANG Qing ,
  • Gao Liai
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  • College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071001, China

Received date: 2020-04-07

  Online published: 2021-02-05

摘要

针对风-光-抽水蓄能联合发电系统各部分出力不佳导致的收益不高问题,通过改进粒子群万有引力混合算法,将混沌算法、惯性权重和改进步长因子引入传统的粒子群万有引力算法,解决传统算法的寻优能力弱、精度不高的问题.将改进后的粒子群万有引力算法应用于实际工程算例当中,优化联合发电系统各部分的出力,进而得到最大经济效益.与粒子群算法、万有引力算法和未改进粒子群万有引力算法对比,结果表明,改进后的算法精度最佳,迭代数最少.优化后的联合发电系统各部分出力,所达到的经济效益最大.

本文引用格式

杨森 , 张青 , 高立艾 . 风-光-抽水蓄能联合发电系统的优化运行[J]. 河北大学学报(自然科学版), 2021 , 41(1) : 106 -112 . DOI: 10.3969/j.issn.1000-1565.2021.01.016

Abstract

Considering the wind - light - joint pumped storage power generation system low output due to the fact that each part is of low output, and to improve particle swarm gravitation hybrid algorithm, inertia weight and chaos algorithm were introduced into the traditional particle swarm algorithm of gravity. The capability and precision of the traditional algorithm optimization were Improved. precision is not high.The improved particle swarm gravitation algorithm is applied to a practical engineering example to optimize the output of each part of the co-generation system and obtain the maximum economic benefit.The results show that the improved algorithm has the best accuracy and the shortest iteration times. After the optimization of the output of each part of the joint generation system, the largest economic benefits were achieved.

参考文献

[1] 张宁,康重庆,肖晋宁,等.风电容量可信度研究综述与展望[J].中国电机工程学报,2015,35(1):82-94.DOI:10.13334/j.0258-8013.pcsee.2015.01.011.
[2] AEIDAPU M, KANWARJIT S S. Hybrid wind/photovoltaic energy system developments: critical review and findings[J]. Renewable and Sustainable Energy Reviews, 2015, 52: 1135-1147.DOI:10.1016/j.rser.2015.08.008.
[3] 丁明,王伟胜,王秀丽,等.大规模光伏发电对电力系统影响综述[J].中国电机工程学报,2014,34(1):1-14.DOI:10.13334/j.0258-8013.pcsee.2014.01.001.
[4] 邹金,赖旭,汪宁渤.以减少电网弃风为目标的风电与抽水蓄能协调运行[J].电网技术,2015,39(9):2472-2477.DOI:10.13335/j.1000-3673.pst.2015.09.015.
[5] 王辉,崔建勇.对应光伏并网的抽水蓄能电站优化运行[J].电网技术,2014,38(8):2095-2101.DOI:10.13335/j.1000-3673.pst.2014.08.012.
[6] BUENO C, CARTA J A. Technical-economic analysis of wind-powered pumped hydro storagesystems[J]. Solar Energy, 2005,78(3): 382-405.
[7] 郭伟钊.抽水蓄能、风力和光伏电站群联合运行研究[D].北京:华北电力大学,2011.
[8] 吕优.风-光-抽水蓄能联合发电系统优化调度研究[D].西安:西安理工大学,2018.
[9] 马实一.风电-光伏-抽水蓄能联合优化运行模型建立与应用[J].供用电,2018, 35(1): 80-85.DOI:10.19421/j.cnki.1006-6357.2018.01.014.
[10] 马实一,李建成,段聪,等.基于电力市场背景的风-光-抽水蓄能联合优化运行[J].新能源,2019,47(8): 43-49.
[11] 李鹏,徐伟娜,周泽远,等.基于改进万有引力搜索算法的微网优化运行[J].中国电机工程学报,2014,34(19):3073-3079.DOI:10.13334/j.0258-8013.pcsee.2014.19.005.
[12] 钱晨昊.抽水蓄能与风光联合运行成本效益研究[D].北京:华北电力大学,2018.
[13] RASHEDI E, NEZAMABADI-POUR H, SARYZZDI S. GSA: A gravitational search algorithm [J]. Information sciences, 2009, 179(13): 2232-2248.DOI:10.1016/j.ins.2009.03.004.
[14] MIRJALILI S, LWEIS A. Adaptive gbest-guided gravitational search algorithm [J]. Neural Computing and Application, 2014, 25(7/8): 1-16.DOI:10.1007/s00521-014-1640-y
[15] 马力,刘丽涛.万有引力搜索算法的分析与改进[J].微电子学与计算机,2015,32(9):76-80.DOI:10.19304/j.cnki.issn1000-7180.2015.09.015. (
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