考虑碳排放成本的风光储多能互补系统优化运行研究
|
摘要
为提高风电、光伏等新能源的消纳能力,提升多能互补微网系统运行经济性,提出了一种风光储多能互补微网系统并网日前调度的优化模型。模型的目标函数变量包括储能电池运行成本、系统弃风弃光成本、削负荷成本以及从上级电网购电成本,同时考虑到系统从上级电网购电将产生碳排放,基于此建立碳排放成本计算模型,并计入目标函数中。约束条件中考虑了储能电池充放电功率和容量、购售电功率平衡以及上级电网交换功率上限等约束。采用粒子群算法对模型进行求解。算例分析结果表明,所建模型能够充分考虑碳排放的环境因素以及系统实际运行特点,通过调节系统与上级电网的交换功率以及储能电池的充放电功率,能在实现系统运行成本最小的同时减少弃风弃光与削负荷情况。
An optimization model of day-ahead scheduling for micro-grid with wind-PV-ES complementary system is proposed to improve the absorptive capacity and power supply reliability of wind power and photovoltaic and the economy of multi energy complementary micro network system. The objective function of the model include the operating cost of the energy storage battery, the cost of the system abandoning the wind and light, the cost of cutting the load and the cost of purchasing electricity from the higher power grid, at the same time, considering the carbon emission from the higher power grid, the carbon emission cost model is established, and the cost of the carbon emission is included in the objective function of the model. Constraints of energy storage battery, power balance and switching limit with upper power grid are considered in the model as well. Particle Swarm Optimization(PSO) algorithm is used to solve the model. The result shows that the model can fully consider the environmental factors of carbon emission and the actual operating characteristics of the system; by adjusting the switching power between the system and the upper power grid and the charging and discharging power of the storage battery, the system can realize the minimum operating cost and reduce the discarding of the wind and light, as well as the cutting load of the system.
An optimization model of day-ahead scheduling for micro-grid with wind-PV-ES complementary system is proposed to improve the absorptive capacity and power supply reliability of wind power and photovoltaic and the economy of multi energy complementary micro network system. The objective function of the model include the operating cost of the energy storage battery, the cost of the system abandoning the wind and light, the cost of cutting the load and the cost of purchasing electricity from the higher power grid, at the same time, considering the carbon emission from the higher power grid, the carbon emission cost model is established, and the cost of the carbon emission is included in the objective function of the model. Constraints of energy storage battery, power balance and switching limit with upper power grid are considered in the model as well. Particle Swarm Optimization(PSO) algorithm is used to solve the model. The result shows that the model can fully consider the environmental factors of carbon emission and the actual operating characteristics of the system; by adjusting the switching power between the system and the upper power grid and the charging and discharging power of the storage battery, the system can realize the minimum operating cost and reduce the discarding of the wind and light, as well as the cutting load of the system.
引文
[1]中华人民共和国国家发展和改革委员会,中华人民共和国国家能源局.电力发展“十三五”规划(2016-2020)[R/OL].2016.National Development and Reform Commission,National Energy Administration.The 13th Five-Year Electric Power Planning(2016-2020)[R/OL].2016.
[2]李国庆,翟晓娟.基于层次分析法的孤立微电网多目标优化运行[J].电力系统保护与控制,2018,46(10):17-23.LI Guoqing,ZHAI Xiaojuan.Multi-objective optimal operation of island micro-grid based on analytic hierarchy process[J].Power System Protection and Control,2018,46(10):17-23.
[3]晁颖,金烨,朱晶亮,等.考虑光伏发电出力不确定性的年度最大负荷概率预测[J].广东电力,2018,31(9):83-89.CHAO Ying,JIN Ye,ZHU Jingliang,et al.Annual maximum load probability prediction considering the uncertainty of photovoltaic power output[J].Guangdong Electric Power,2018,31(9):83-89.
[4]王树东,杜巍,林莉,等.基于合作博弈的需求侧响应下光储微电网优化配置[J].电力系统保护与控制,2018,46(1):129-137.WANG Shudong,DU Wei,LIN Li,et al.Optimal allocation of photovoltaic energy storage micro-grid under the demand side response based on cooperative game[J].Power System Protection and Control,2018,46(1):129-137.
[5]陈磊,徐飞,王晓,等.储热提升风电消纳能力的实施方式及效果分析[J].中国电机工程学报,2015,35(17):4283-4290.CHEN Lei,XU Fei,WANG Xiao,et al.Analysis of the implementation way of heat storage enhance the absorptive capacity of wind power and effect[J].Proceedings of the CSEE,2015,35(17):4283-4290.
[6]施泉生,郭良合,张孝君.综合考虑多主体经济效益的分布式电源优化配置研究[J].电力系统保护与控制,2016,44(1):85-91.SHI Quansheng,GUO Lianghe,ZHANG Xiaojun.Research on optimal configuration of distributed generation considering economic benefits of the multi-agent[J].Power System Protection and Control,2016,44(1):85-91.
[7]刘波,郭家宝,袁智强,等.风光储联合发电系统调度策略研究[J].华东电力,2010,38(12):1897-1899.LIU Bo,GUO Jiabao,YUAN Zhiqiang,et al.Research on dispatching strategy of wind solar storage combined power generation system[J].East China Electric Power,2010,38(12):1897-1899.
[8]陈中,胡吕龙,丁楠.基于改进熵的风光储互补并网系统优化运行[J].电力系统保护与控制,2013,41(21):86-91.CHEN Zhong,HU Lülong,DING Nan.Optimal operation of wind PV hybrid grid connected system based on improved entropy[J].Power System Protection and Control,2013,41(21):86-91.
[9]刘燕华,张楠,张旭.考虑储能运行成本的风光储微网的经济运行[J].现代电力,2013,30(5):13-18.LIU Yanhua,ZHANG Nan,ZHANG Xu.Economic operation of wind solar storage micro-grid considering energy storage operating costs[J].Modern Electric Power,2013,30(5):13-18.
[10]刘娇娇,王致杰,袁建华,等.基于PSO算法的风光储微电网优化调度研究[J].华东电力,2014,42(8):1534-1539.LIU Jiaojiao,WANG Zhijie,YUAN Jianhua,et al.Research on optimal scheduling of wind solar storage micro grid based on PSO algorithm[J].East China Electric Power,2014,42(8):1534-1539.
[11]李东东,徐连连,刘翔,等.考虑可削减负荷参与的含风光储微网经济优化调度[J].电力系统保护与控制,2017,45(2):35-41.LI Dongdong,XU Lianlian,LIU Xiang,et al.Economic optimal dispatch of microgrid with wind energy storage considering curtailment of load participation[J].Power System Protection and Control,2017,45(2):35-41.
[12]朱芃.风光储混合微电网的运行与优化[D].北京:华北电力大学,2016.ZHU Peng.Operation and optimization of wind,light and energy storage hybrid micro grid[D].Beijing:North China Electric Power University,2016.
[13]MOHAMED F A,KOIVO H N.System modelling and online optimal management of micro-grid using mesh adaptive direct search[J].International Journal of Electrical Power&Energy Systems,2010,32(5):398-407.
[14]牛冲宣.微电网的孤岛检测与孤岛划分[D].天津:天津大学,2008.NIU Chongxuan.Isolated island detection and islanding division in micro grid[D].Tianjin:Tianjin University,2008.
[15]李咸善,王锦龙,杨丝琪,等.基于RBHPSO-GSA算法的微电网优化运行方法[J].智慧电力,2018,46(9):26-32.LI Xianshan,WANG Jinlong,YANG Siqi,et al.Microgrid optimization operation method based on RBHPSO-GSA algorithm[J].Smart Power,2018,46(9):26-32.
[16]王彩霞,乔颖,鲁宗相,等.低碳经济下风火互济系统日前发电计划模式分析[J].电力系统自动化,2011,35(22):111-117.WANG Caixia,QIAO Ying,LU Zongxiang,et al.Analysis of the model of power generation plan for wind-fire mutual aid system under low carbon economy[J].Automation of Electric Power Systems,2011,35(22):111-117.
[17]闫秉科,李小平,舒欣,等.多种分布式电源随机性的配电网优化运行研究[J].智慧电力,2017,45(11):14-18,90.YAN Bingke,LI Xiaoping,SHU Xin,et al.Study on optimal operation of distribution network with random distribution generations[J].Smart Power,2017,45(11):14-18,90.
[18]王家兵.分布式光伏电站接入配电网优化规划研究[D].南京:东南大学,2017.WANG Jiabing.Optimal planning of distributed photovoltaic power station access to distribution network[D].Nanjing:Southeast University,2017.
[19]王庆斌,石亮缘,黄辉,等.基于改进粒子群算法的输电线路路径规划研究[J].广东电力,2018,31(9):135-141.WANG Qingbin,SHI Liangyuan,HUANG Hui,et al.Research on transmission line path planning based on improved particle swarm optimization[J].Guangdong Electric Power,2018,31(9):135-141.
[20]ENGELBRECHT A P.计算群体智能基础[M].北京:清华大学出版社,2009.
[21]SABER A Y,VENAYAGAMOORTHY G K.Plug-in vehicles and renewable energy sources for cost and emission reductions[J].IEEE Transactions on Industrial Electronics,2011,58(4):1229-1238.
[22]娄素华,胡斌,吴耀武,等.碳交易环境下含大规模光伏电源的电力系统优化调度[J].电力系统自动化,2014,38(17):91-97.LOU Suhua,HU Bin,WU Yaowu,et al.Optimal dispatch of power system integrated with large scale photovoltaic generation under carbon trading environment[J].Automation of Electric Power Systems,2014,38(17):91-97.
[23]LOU S,WANG Z,WU Y,et al.Coordinated economic dispatch for power system with significant wind power generation based on chance-constrained programming[J].Transactions of China Electrotechnical Society,2013,28(10):337-345.
[24]MORALES J M,CONEJO A J,PEREZ-RUIZ J.Economic valuation of reserves in power systems with high penetration of wind power[J].IEEE Transactions on Power Systems,2009,24(2):900-910.
[25]LIU G,TOMSOVIC K.Quantifying spinning reserve in systems with significant wind power penetration[J].IEEETransactions on Power Systems,2012,27(4):2385-2393.
[2]李国庆,翟晓娟.基于层次分析法的孤立微电网多目标优化运行[J].电力系统保护与控制,2018,46(10):17-23.LI Guoqing,ZHAI Xiaojuan.Multi-objective optimal operation of island micro-grid based on analytic hierarchy process[J].Power System Protection and Control,2018,46(10):17-23.
[3]晁颖,金烨,朱晶亮,等.考虑光伏发电出力不确定性的年度最大负荷概率预测[J].广东电力,2018,31(9):83-89.CHAO Ying,JIN Ye,ZHU Jingliang,et al.Annual maximum load probability prediction considering the uncertainty of photovoltaic power output[J].Guangdong Electric Power,2018,31(9):83-89.
[4]王树东,杜巍,林莉,等.基于合作博弈的需求侧响应下光储微电网优化配置[J].电力系统保护与控制,2018,46(1):129-137.WANG Shudong,DU Wei,LIN Li,et al.Optimal allocation of photovoltaic energy storage micro-grid under the demand side response based on cooperative game[J].Power System Protection and Control,2018,46(1):129-137.
[5]陈磊,徐飞,王晓,等.储热提升风电消纳能力的实施方式及效果分析[J].中国电机工程学报,2015,35(17):4283-4290.CHEN Lei,XU Fei,WANG Xiao,et al.Analysis of the implementation way of heat storage enhance the absorptive capacity of wind power and effect[J].Proceedings of the CSEE,2015,35(17):4283-4290.
[6]施泉生,郭良合,张孝君.综合考虑多主体经济效益的分布式电源优化配置研究[J].电力系统保护与控制,2016,44(1):85-91.SHI Quansheng,GUO Lianghe,ZHANG Xiaojun.Research on optimal configuration of distributed generation considering economic benefits of the multi-agent[J].Power System Protection and Control,2016,44(1):85-91.
[7]刘波,郭家宝,袁智强,等.风光储联合发电系统调度策略研究[J].华东电力,2010,38(12):1897-1899.LIU Bo,GUO Jiabao,YUAN Zhiqiang,et al.Research on dispatching strategy of wind solar storage combined power generation system[J].East China Electric Power,2010,38(12):1897-1899.
[8]陈中,胡吕龙,丁楠.基于改进熵的风光储互补并网系统优化运行[J].电力系统保护与控制,2013,41(21):86-91.CHEN Zhong,HU Lülong,DING Nan.Optimal operation of wind PV hybrid grid connected system based on improved entropy[J].Power System Protection and Control,2013,41(21):86-91.
[9]刘燕华,张楠,张旭.考虑储能运行成本的风光储微网的经济运行[J].现代电力,2013,30(5):13-18.LIU Yanhua,ZHANG Nan,ZHANG Xu.Economic operation of wind solar storage micro-grid considering energy storage operating costs[J].Modern Electric Power,2013,30(5):13-18.
[10]刘娇娇,王致杰,袁建华,等.基于PSO算法的风光储微电网优化调度研究[J].华东电力,2014,42(8):1534-1539.LIU Jiaojiao,WANG Zhijie,YUAN Jianhua,et al.Research on optimal scheduling of wind solar storage micro grid based on PSO algorithm[J].East China Electric Power,2014,42(8):1534-1539.
[11]李东东,徐连连,刘翔,等.考虑可削减负荷参与的含风光储微网经济优化调度[J].电力系统保护与控制,2017,45(2):35-41.LI Dongdong,XU Lianlian,LIU Xiang,et al.Economic optimal dispatch of microgrid with wind energy storage considering curtailment of load participation[J].Power System Protection and Control,2017,45(2):35-41.
[12]朱芃.风光储混合微电网的运行与优化[D].北京:华北电力大学,2016.ZHU Peng.Operation and optimization of wind,light and energy storage hybrid micro grid[D].Beijing:North China Electric Power University,2016.
[13]MOHAMED F A,KOIVO H N.System modelling and online optimal management of micro-grid using mesh adaptive direct search[J].International Journal of Electrical Power&Energy Systems,2010,32(5):398-407.
[14]牛冲宣.微电网的孤岛检测与孤岛划分[D].天津:天津大学,2008.NIU Chongxuan.Isolated island detection and islanding division in micro grid[D].Tianjin:Tianjin University,2008.
[15]李咸善,王锦龙,杨丝琪,等.基于RBHPSO-GSA算法的微电网优化运行方法[J].智慧电力,2018,46(9):26-32.LI Xianshan,WANG Jinlong,YANG Siqi,et al.Microgrid optimization operation method based on RBHPSO-GSA algorithm[J].Smart Power,2018,46(9):26-32.
[16]王彩霞,乔颖,鲁宗相,等.低碳经济下风火互济系统日前发电计划模式分析[J].电力系统自动化,2011,35(22):111-117.WANG Caixia,QIAO Ying,LU Zongxiang,et al.Analysis of the model of power generation plan for wind-fire mutual aid system under low carbon economy[J].Automation of Electric Power Systems,2011,35(22):111-117.
[17]闫秉科,李小平,舒欣,等.多种分布式电源随机性的配电网优化运行研究[J].智慧电力,2017,45(11):14-18,90.YAN Bingke,LI Xiaoping,SHU Xin,et al.Study on optimal operation of distribution network with random distribution generations[J].Smart Power,2017,45(11):14-18,90.
[18]王家兵.分布式光伏电站接入配电网优化规划研究[D].南京:东南大学,2017.WANG Jiabing.Optimal planning of distributed photovoltaic power station access to distribution network[D].Nanjing:Southeast University,2017.
[19]王庆斌,石亮缘,黄辉,等.基于改进粒子群算法的输电线路路径规划研究[J].广东电力,2018,31(9):135-141.WANG Qingbin,SHI Liangyuan,HUANG Hui,et al.Research on transmission line path planning based on improved particle swarm optimization[J].Guangdong Electric Power,2018,31(9):135-141.
[20]ENGELBRECHT A P.计算群体智能基础[M].北京:清华大学出版社,2009.
[21]SABER A Y,VENAYAGAMOORTHY G K.Plug-in vehicles and renewable energy sources for cost and emission reductions[J].IEEE Transactions on Industrial Electronics,2011,58(4):1229-1238.
[22]娄素华,胡斌,吴耀武,等.碳交易环境下含大规模光伏电源的电力系统优化调度[J].电力系统自动化,2014,38(17):91-97.LOU Suhua,HU Bin,WU Yaowu,et al.Optimal dispatch of power system integrated with large scale photovoltaic generation under carbon trading environment[J].Automation of Electric Power Systems,2014,38(17):91-97.
[23]LOU S,WANG Z,WU Y,et al.Coordinated economic dispatch for power system with significant wind power generation based on chance-constrained programming[J].Transactions of China Electrotechnical Society,2013,28(10):337-345.
[24]MORALES J M,CONEJO A J,PEREZ-RUIZ J.Economic valuation of reserves in power systems with high penetration of wind power[J].IEEE Transactions on Power Systems,2009,24(2):900-910.
[25]LIU G,TOMSOVIC K.Quantifying spinning reserve in systems with significant wind power penetration[J].IEEETransactions on Power Systems,2012,27(4):2385-2393.