电力市场环境下风-储混合发电商的偏差电量考核模型
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摘要
在含风电现货市场形成前的过渡阶段,风电商的偏差电量考核是完善含风电电力市场建设的过程中不可缺少的环节之一。为了更直观地分析偏差电量考核对风电商经济效益的影响,构建了风电商的偏差电量考核模型,同时采取风-储联合运营的方式来减少风电商需要被考核的偏差电量,并在此基础上建立了储能系统在不同控制模式下风-储混合系统的收益模型。基于混合整数规划技术调用CPLEX优化软件对模型进行求解,对比分析了储能系统对风电商经济效益的影响,并对偏差单位电量考核成本、偏差免考核系数进行敏感性分析。结果表明,在控制储能系统充放电次数的模式下,风-储联合运营能获得更好的经济效益。
As a transitional stage before the formation of the wind power spot market,the assessment of wind power supplier's deviation power is one of the indispensable links in the process of building a wind power market. In order to more intuitively analyze the impact of the deviation power assessment on the economic benefits of wind power suppliers,the wind power supplier's deviation power assessment model is constructed,and the wind storage joint operation measures are adopted to reduce the deviation power that wind power suppliers need to be assessed. On this basis,the revenue model of the windstorage system in the energy storage system is constructed under different control modes. On the basis of the mixed integer programming technique,the CPLEX optimization software is used to solve the model. The comparison of the energy storage system on the economic benefits of the wind power supplier is carried out,and the sensitivity analysis of the deviation unit power assessment cost and the deviation exemption evaluation coefficient is carried out. The results show that under the mode of controlling the number of times of charge and discharge of the energy storage system,the combined operation of wind power and storage can obtain better economic benefits.
As a transitional stage before the formation of the wind power spot market,the assessment of wind power supplier's deviation power is one of the indispensable links in the process of building a wind power market. In order to more intuitively analyze the impact of the deviation power assessment on the economic benefits of wind power suppliers,the wind power supplier's deviation power assessment model is constructed,and the wind storage joint operation measures are adopted to reduce the deviation power that wind power suppliers need to be assessed. On this basis,the revenue model of the windstorage system in the energy storage system is constructed under different control modes. On the basis of the mixed integer programming technique,the CPLEX optimization software is used to solve the model. The comparison of the energy storage system on the economic benefits of the wind power supplier is carried out,and the sensitivity analysis of the deviation unit power assessment cost and the deviation exemption evaluation coefficient is carried out. The results show that under the mode of controlling the number of times of charge and discharge of the energy storage system,the combined operation of wind power and storage can obtain better economic benefits.
引文
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[2]马莉,范孟华,郭磊,等.国外电力市场最新发展动向及其启示[J].电力系统自动化,2014,38(13):1-9.MA Li,FAN Menghua,GUO Lei,et al.Latest development trends of international electricity markets and their enlightenment[J].Automation of Electric Power Systems,2014,38(13):1-9.
[3]丁明,张颖媛,茆美琴,等.包含钠硫电池储能的微网系统经济运行优化[J].中国电机工程学报,2011,31(4):7-14.DING Ming,ZHANG Yingyuan,MAO Meiqin,et al.Economic operation optimization for microgrids including Na/S battery storage[J].Proceedings of the CSEE,2011,31(4):7-14.
[4]张刘冬,袁宇波,孙大雁,等.基于两阶段鲁棒区间优化的风储联合运行调度模型[J].电力自动化设备,2018,38(12):59-66,93.ZHANG Liudong,YUAN Yubo,SUN Dayan,et al.Joint operation model of wind-storage system based on two-stage robust interval optimization[J].Electric Power Automation Equipment,2018,38(12):59-66,93.
[5]孙辉,刘鑫,贲驰,等.含风储一体化电站的电力系统多目标风险调度模型[J].电力系统自动化,2018,42(5):94-101.SUN Hui,LIU Xin,BEN Chi,et al.Multi-objective risk scheduling model of power system containing power station with integrated wind power and energy storage[J].Automation of Electric Power Systems,2018,42(5):94-101.
[6]郑宇,李杨,焦丰顺,等.含风电机组与电转气设备的虚拟电厂竞价策略[J].电力建设,2017,38(7):88-95.ZHENG Yu,LI Yang,JIAO Fengshun,et al.Bidding strategies for virtual power plants including wind power generation units and power-to-gas facilities[J].Electric Power Construction,2017,38(7):88-95.
[7]李丹,刘俊勇,刘友波,等.考虑风储参与的电力市场联动博弈分析[J].电网技术,2015,39(4):1001-1007.LI Dan,LIU Junyong,LIU Youbo,et al.Analysis on electricity market linkage game considering participation of wind power and energy storage[J].Power System Technology,2015,39(4):1001-1007.
[8]江岳文,陈梅森,温步瀛.基于鲁棒后悔度的含风电日前和日内市场两阶段出清优化[J].电力系统自动化,2019,43(9):59-71.JIANG Yuewen,CHEN Meisen,WEN Buying.Robust regret based two-stage clearing optimization of day-ahead and intra-day markets with wind power[J].Automation of Electric Power Systems,2019,43(9):59-71.
[9]姚高瑞,雷雪姣,刘西林,等.促进风电消纳的供需互动合约机制与多市场购电策略[J].电力系统自动化,2019,43(7):113-119.YAO Gaorui,LEI Xuejiao,LIU Xilin,et al.Supply-demand interaction contract mechanism and multi-market electricity purchasing strategy for improving wind power accommodation[J].Automation of Electric Power Systems,2019,43(7):113-119.
[10]郑亚先,武泽辰,王秀丽,等.基于卖方灵活电力合约的风电中长期交易策略[J].电力建设,2016,37(12):128-133.ZHENG Yaxian,WU Zechen,WANG Xiuli,et al.A wind power long-term trading strategy based on seller-side flexible electricity contract[J].Electric Power Construction,2016,37(12):128-133.
[11]李竹,赵博石,延星,等.跨区跨省电力交易中的偏差电量分析与基于虚拟分时电价的偏差电量处理方法[J].电力建设,2016,37(7):40-46.LI Zhu,ZHAO Boshi,YAN Xing,et al.Deviation electric quantity processing method in cross-regional and cross-province electricity transaction based on virtual time-of-use power price[J].Electric Power Construction,2016,37(7):40-46.
[12]马佳乐,谭忠富,喻小宝,等.计及实时电量交易的售电公司日偏差电量考核优化模型[J].电力建设,2019,40(2):11-19.MA Jiale,TAN Zhongfu,YU Xiaobao,et al.Optimal model for daily deviation penalty of electricity retailer considering real-time electricity trading[J].Electric Power Construction,2019,40(2):11-19.
[13]王晛,黄蒙涛,张少华.考虑风电投标偏差惩罚的电力市场均衡分析[J].电网技术,2016,40(2):602-607.WANG Xian,HUANG Mengtao,ZHANG Shaohua.Equilibrium analysis of electricity market considering penalties for wind power's bidding deviation[J].Power System Technology,2016,40(2):602-607.
[14]吴雄,王秀丽,李骏,等.风电储能混合系统的联合调度模型及求解[J].中国电机工程学报,2013,33(13):10-17.WU Xiong,WANG Xiuli,LI Jun,et al.A joint operation model and solution for hybrid wind energy storage systems[J].Proceedings of the CSEE,2013,33(13):10-17.
[15]孙波,董浩,陈纲,等.电动汽车-风储混合系统联合运行的日内优化调度模型[J].可再生能源,2018,36(7):1033-1038.SUN Bo,DONG Hao,CHEN Gang,et al.An intraday optimal scheduling model for joint operation of electric vehicles and windstorage hybrid systems[J].Renewable Energy Resources,2018,36(7):1033-1038.
[16]吴雄,王秀丽,王建学,等.微网经济调度问题的混合整数规划方法[J].中国电机工程学报,2013,33(28):1-8.WU Xiong,WANG Xiuli,WANG Jianxue,et al.Economic generation scheduling of a microgrid using mixed integer programming[J].Proceedings of the CSEE,2013,33(28):1-8.