计及不确定性和混合储能设备的综合能源系统多目标优化调度模型
CSTR:
作者:
中图分类号:

TM732

基金项目:

国网宁夏电力有限公司科技项目(5229JY190014)


Multi-objective optimal scheduling model for multi-energy system considering uncertainty and hybrid energy storage devices
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [18]
  • | | | |
  • 文章评论
    摘要:

    为提高综合能源系统内可再生能源消纳水平,量化不确定性机组出力对系统调度的影响,首先构建包含氢能—天然气混合储能的综合能源系统,分析混合储能在系统中的运行特性;其次,构建综合能源系统多目标优化调度模型,利用多目标CVaR方法对风电机组不确定性风险进行描述;然后,采用模糊C均值—综合质量评估方法(FCM-CCQ)与改进的粒子群算法将系统不确定性问题转化为确定性问题;最后,分别求解不考虑不确定性的单目标优化结果和考虑不确定性的综合目标优化结果。结果表明:混合储能设备能够有效地提高可再生能源消纳水平,实现能量的多级转化;可再生能源不确定性将增加综合能源系统综合成本,系统风险承受能力越强,调度结果越优。

    Abstract:

    Aiming at improving the renewable energy consumption level in the multi-energy system and quantify the influence of uncertain unit output on system scheduling, a multi-energy system containing hydrogen and gas energy storage is constructed and the operation characteristics of hybrid energy storage in the system are analyzed in this paper. Then, a multi-objective optimal scheduling model for multi-energy systems is proposed, and the uncertainty risk of wind turbines is described by the multi-objective conditional value at risk method. In addition, the fuzzy C-mean-comprehensive quality assessment and improved particle swarm optimization are utilized to transform the system uncertainty problem into a deterministic problem. Finally, the single-objective optimization results without uncertainty and the comprehensive objective optimization results with uncertainty are solved respectively. It is shown that (1) hybrid energy storage devices can effectively improve the consumption level of renewable energy and realize the multi-stage energy conversion. (2) the uncertainty of renewable energy increases the comprehensive cost of a multi-energy system. (3) the improved risk tolerance of system can improve scheduling results.

    参考文献
    [1] 屈小云,吴鸣,李奇,等.多能互补综合能源系统综合评价研究进展综述[J].中国电力,2021,54(11):153-163.QU Xiaoyun,WU Ming,LI Qi,et al.Review on comprehensive evaluation of multi-energy complementary integrated energy systems[J].Electric Power,2021,54(11):153-163.
    [2] 国家能源局.国家能源局发布1-2月份全国电力工业统计数据[EB/OL].http://www.nea.gov.cn/2022-03/21/c_1310522988.htm.
    [3] 马令希,付学谦.考虑农业-气象-能源耦合的农业能源互联网理论及应用[J].中国电力,2021,54(11):115-124.MA Lingxi,FU Xueqian.Theory and application of agricultural energy internet considering coupling of agriculture,meteorology and energy[J].Electric Power,2021,54(11):115-124.
    [4] 付菊霞,陈洁,邓浩,等.平抑风电波动的混合储能系统控制策略[J].电测与仪表,2020,57(5):94-100.FU Juxia,CHEN Jie,DENG Hao,et al.Control strategy of hybrid energy storage system for mitigating wind power fluctuations[J].Electrical Measurement & Instrumentation,2020,57(5):94-100.
    [5] 郜宁,张慧媛,王子琪,等.区域电网分布式储能选址定容规划[J].高压电器,2020,56(8):52-58.GAO Ning,ZHANG Huiyuan,WANG Ziqi,et al.Planning for site selection and capacity determination of distributed energy storage in regional power grid[J].High Voltage Apparatus,2020,56(8):52-58.
    [6] MIAO D,HOSSAIN S.Improved gray wolf optimization algorithm for solving placement and sizing of electrical energy storage system in micro-grids[J].ISA Transactions,2020,102:376-387.
    [7] 邓逸天,王宇辉,黄景光,等.考虑需求响应的含P2G电-气综合能源系统优化调度[J].智慧电力,2020,48(12):8-13,32.DENG Yitian,WANG Yuhui,HUANG Jingguang,et al.Optimal dispatch of integrated electricity-gas system with power to gas considering demand response[J].Smart Power,2020,48(12):8-13,32.
    [8] ZHOU S,SUN K,WU Z,et al.Optimized operation method of small and medium-sized integrated energy system for P2G equipment under strong uncertainty[J].Energy,2020,199:117269.
    [9] REZAEI N,KHAZALI A,MAZIDI M,et al.Economic energy and reserve management of renewable-based microgrids in the presence of electric vehicle aggregators:A robust optimization approach[J].Energy,2020,201:117629.
    [10] 风—光—蓄—火联合发电系统的两阶段优化调度策略[J].电网与清洁能源,2020,36(5):75-82.WANG Mingsong.Two-stage optimal dispatching strategy of the wind-solar-pumped storage-thermal combined system[J].Power System and Clean Energy,2020,36(5):75-82.
    [11] ABREU L V L.Risk-constrained coordination of cascaded hydro units with variable wind power generation[J].IEEE Transactions on Sustainable Energy,2012,3(3):359-368.
    [12] 应飞祥,徐天奇,李琰,等.含电动汽车充电站商业型虚拟电厂的日前调度优化策略研究[J].电力系统保护与控制,2020,48(21):92-100.YING Feixiang,YING Feixiang,YING Feixiang,et al.Research on day-to-day scheduling optimization strategy of a commercial virtual power plant with an electric vehicle charging station[J].Power System Protection and Control,2020,48(21):92-100.
    [13] 周星球,郑凌蔚,杨兰,等.考虑多重不确定性的综合能源系统日前优化调度[J].电网技术,2020,44(7):2466-2473.ZHOU Xingqiu,ZHENG Lingwei,YANG Lan,et al.Day-ahead optimal dispatch of an integrated energy system considering multiple uncertainty[J].Power System Technology,2020,,44(7):2466-2473.
    [14] PU L,WANG X H,TAN Z F,et al.Is China's electricity price cross-subsidy policy reasonable?comparative analysis of eastern,central,and western regions[J].Energy Policy,2020,138:111250.
    [15] PU L,WANG X H,TAN Z F,et al.Feasible electricity price calculation and environmental benefits analysis of the regional nighttime wind power utilization in electric heating in Beijing[J].Journal of Cleaner Production,2019,212:1434-1445.
    [16] 古哲源,苏小林,秦宏,等.综合能源系统储能规划研究[J].电气自动化,2019,41(5):31-34.GU Zheyuan,SU Xiaolin,QIN Hong,et al.Research on energy storage planning of the integrated energy system[J].Electrical Automation,2019,41(5):31-34.
    [17] 仇知,王蓓蓓,贲树俊,等.计及不确定性的区域综合能源系统双层优化配置规划模型[J].电力自动化设备,2019,39(8):176-185.QIU Zhi,WANG Beiei,BEN Shujun,et al.Bi-level optimal configuration planning model of regional integrated energy system considering uncertainties[J].Electric Power Automation Equipment,2019,39(8):176-185.
    [18] 胡伟,杨梓俊,王瑾然,等.园区综合能源系统日前多目标优化调度[J].电力科学与技术学报,2021,36(1):13-20.HU Wei,YANG Zijun,WANG Jinran,et al.Multi-objective optimal scheduling of integrated energy system in the industry park[J].Journal of Electric Power Science and Technology,2021,36(1):13-20.
    相似文献
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

马艳霞,周静涵,董晓晶,等.计及不确定性和混合储能设备的综合能源系统多目标优化调度模型[J].电力科学与技术学报,2022,37(3):19-32.
MA Yanxia, ZHOU Jinghan, DONG Xiaojing, et al. Multi-objective optimal scheduling model for multi-energy system considering uncertainty and hybrid energy storage devices[J]. Journal of Electric Power Science and Technology,2022,37(3):19-32.

复制
分享
文章指标
  • 点击次数:211
  • 下载次数: 985
  • HTML阅读次数: 0
  • 引用次数: 0
历史
  • 在线发布日期: 2022-07-24
文章二维码