考虑需求侧管理的冷热电联供微电网优化配置方法
|
摘要
冷热电联供微电网可提高供用电系统灵活多样的能量优化调度调控水平,已成为微电网技术发展的必然趋势之一。对冷热电联供微电网系统引入了需求侧管理手段,充分利用需求侧资源发掘了系统的经济性。首先对系统中所采取的需求侧管理技术进行建模,包括对需求侧管理的采用方式以及调用成本。其次以综合优化配置成本为目标函数,计及多种必要的约束条件,建立考虑需求侧管理的冷热电联供微电网优化配置模型。采用混沌粒子群算法对所建立的模型进行求解。优化配置结果表明,离网模式下系统优化配置成本要高于并网模式下的,而考虑需求侧管理技术的系统优化配置成本要小于不考虑需求侧管理手段的。通过对系统引入需求侧管理手段能够降低系统优化配置成本,证明了该模型的正确性和有效性。
The CCHP microgrid can improve the level of flexible and diversified energy optimization and regulation of the power supply system, which has become one of the inevitable trends in the development of microgrid technology. The DSM method is introduced to CCHP microgrid system, and the economy of the system is excavated by full use of the demand side resources. Firstly, this paper models the DSM technology adopted in the system, including method of adoption and the cost. Secondly, taking the comprehensive optimization allocation cost as the objective function and taking various necessary constraints into account, an optimal configuration model of CCHP microgrid considering DSM is established. The chaotic Particle Swarm Optimization(PSO) is used to solve the model. The optimal configuration results show that the optimal configuration cost of the system is higher in grid off mode than that under grid connected mode, while the cost of system considering DSM technology is less than that without DSM. The introduction of DSM to the system can reduce the optimal configuration cost of the system, which proves the correctness and effectiveness of the model.
The CCHP microgrid can improve the level of flexible and diversified energy optimization and regulation of the power supply system, which has become one of the inevitable trends in the development of microgrid technology. The DSM method is introduced to CCHP microgrid system, and the economy of the system is excavated by full use of the demand side resources. Firstly, this paper models the DSM technology adopted in the system, including method of adoption and the cost. Secondly, taking the comprehensive optimization allocation cost as the objective function and taking various necessary constraints into account, an optimal configuration model of CCHP microgrid considering DSM is established. The chaotic Particle Swarm Optimization(PSO) is used to solve the model. The optimal configuration results show that the optimal configuration cost of the system is higher in grid off mode than that under grid connected mode, while the cost of system considering DSM technology is less than that without DSM. The introduction of DSM to the system can reduce the optimal configuration cost of the system, which proves the correctness and effectiveness of the model.
引文
[1]LASSETER R,AKHIL A,MARNAY C,et al.Integration of distributed energy resources[C]//Proceedings of Consortium for Electric Reliability Technology Solutions,California:Lawrence Berkeley National Laboratory,2002:2-6.
[2]刘舒,李正力,王翼,等.含分布式发电的微电网中储能装置容量优化配置[J].电力系统保护与控制,2016,44(3):78-84.LIU Shu,LI Zhengli,WANG Yi,et al.Optimal capacity allocation of energy storage in micro-grid with distributed generation[J].Power System Protection and Control,2016,44(3):78-84.
[3]杨新法,苏剑,吕志鹏,等.微电网技术综述[J].中国电机工程学报,2014,34(1):57-70.YANG Xinfa,SU Jian,LüZhipeng,et al.Overview on microgrid technology[J].Proceedings of the CSEE,2014,34(1):57-70.
[4]范龙,李献梅,陈跃辉,等.激励CCHP参与需求侧管理双向峰谷定价模型[J].电力系统保护与控制,2016,44(17):45-51.FAN Long,LI Xianmei,CHEN Yuehui,et al.Pricing model of bidirectional peak-valley for motivating CCHPto participate in DSM[J].Power System Protection and Control,2016,44(17):45-51.
[5]LI Han,ESEYE A T,ZHANG Jianhua,et al.Optimal energy management for industrial microgrids with high-penetration renewable[J].Protection and Control of Modern Power Systems,2017,2(2):122-135.DOI:10.1186/s41601-017-0040-6.
[6]李正茂,张峰,梁军,等.计及附加机会收益的冷热电联供型微电网动态调度[J].电力系统自动化,2015,39(14):8-15.LI Zhengmao,ZHANG Feng,LIANG Jun,et al.Dynamic scheduling of CCHP type of microgrid considering additional opportunity income[J].Automation of Electric Power Systems,2015,39(14):8-15.
[7]王成山,王守相.分布式发电功能系统若干问题研究[J].电力系统自动化,2008,32(20):1-4.WANG Chengshan,WANG Shouxiang.Study on some key problems related to distributed generation systems[J].Automation of Electric Power Systems,2008,32(20):1-4.
[8]WANG J J,JING Y Y,ZHANG C F.Optimization of capacity and operation for CCHP system by genetic algorithm[J].Applied Energy,2010,87(4):1325-1335.
[9]王锐,顾伟,吴志.含可再生能源的热电联供型微网经济运行优化[J].电力系统自动化,2011,35(8):1-6.WANG Rui,GU Wei,WU Zhi.Optimization of economic operation in CHP micro grid including renewable energy[J].Automation of Electric Power Systems,2011,35(8):1-6.
[10]吴宏斌,王东旭,刘星月.太阳能冷热电联供系统的策略评估和优化配置[J].电力系统自动化,2015,39(21):46-51.WU Hongbin,WANG Dongxu,LIU Xingyue.Strategies evaluation and optimal allocation of combined cooling heating and power system with solar[J].Automation of Electric Power Systems,2015,39(21):46-51.
[11]魏大均,孙波,赵峰,等.小型生物质沼气冷热电联供系统多目标优化设计与运行分析[J].电力系统自动化,2015,39(12):7-12.WEI Dajun,SUN Bo,ZHAO Feng,et al.Multi-objective optimization design and operation analysis of small biomass biogas combined cooling heating and power system[J].Automation of Electric Power Systems,2015,39(12):7-12.
[12]肖小清,阚伟民,杨允,等.有蓄能的联供系统超结构优化配置[J].中国电机工程学报,2012,32(32):8-14.XIAO Xiaoqing,KAN Weimin,YANG Yun,et al.Superstructure-based optimal planning of cogeneration systems with storage[J].Proceeding of the CSEE,2012,32(32):8-14.
[13]WANG J J,ZHAI Z Q,JING Y Y,et al.Particle swarm optimization for redundant building cooling heating and power system[J].Applied Energy,2010,87(12):3668-3679.
[14]WANG J J,ZHANG C F,JING Y Y.Multi-criteria analysis of combined cooling,heating and power systems in different climate zones in China[J].Applied Energy,2010,87(4):1247-1259.
[15]李朝振,石玉美,黄兴华.负荷结构对冷热电联供系统优化配置的影响[J].热能动力工程,2008,23(6):606-610.LI Zhaozhen,SHI Yumei,HUANG Xinghua.Influence of load composition on the optimized configuration of a combined cooling,heating and power cogeneration system[J].Journal of Engineering for Thermal Energy and Power,2008,23(6):606-610.
[16]唐学军,韩佶,苗世洪,等.基于需求侧响应的多类型负荷协调控制模型[J].电力系统保护与控制,2017,45(16):116-123.TANG Xuejun,HAN Ji,MIAO Shihong,et al.Coordinated control model of multi-type load based on demand response[J].Power System Protection and Control,2017,45(16):116-123.
[17]刘丽军,李捷,蔡金锭.基于强引导粒子群和混沌优化的电力系统无功优化[J].电力自动化设备,2010,30(4):71-75.LIU Lijun,LI Jie,CAI Jinding.Reactive power optimization based on induction-enhanced particle swarm optimization and chaos search[J].Electric Power Automation Equipment,2010,30(4):71-75.
[18]韩晓娟,程成,籍天明,等.计及电池使用寿命的混合储能系统容量优化模型[J].中国电机工程学报,2013,33(34):83-89.HAN Xiaojuan,CHENG Cheng,JI Tianming,et al.Capacity optimal modeling of hybrid energy storage systems considering battery life[J].Proceedings of the CSEE,2013,33(34):83-89.
[19]邢龙,张沛超,方陈,等.基于广义需求侧资源的微电网运行优化[J].电力系统自动化,2013,37(12):7-12.XING Long,ZHANG Peichao,FANG Chen,et al.Optimal operation for microgrid using generalized demand side resources[J].Automation of Electric Power Systems,2013,37(12):7-12.
[20]张颖,容展鹏,张宇雄,等.基于微电网的电网需求响应研究[J].电力系统保护与控制,2015,43(21):20-26.ZHANG Ying,RONG Zhanpeng,ZHANG Yuxiong,et al.Study of grid demand response based on micro grid[J].Power System Protection and Control,2015,43(21):20-26.
[21]毛晓明,陈深,吴杰康,等.分时电价机制下含蓄电池微电网的优化调度[J].电网技术,2015,39(5):1192-1197.MAO Xiaoming,CHEN Shen,WU Jiekang,et al.Optimal dispatching of microgrid containing battery under time-of-use price mechanism[J].Power System Technology,2015,39(5):1192-1197.
[2]刘舒,李正力,王翼,等.含分布式发电的微电网中储能装置容量优化配置[J].电力系统保护与控制,2016,44(3):78-84.LIU Shu,LI Zhengli,WANG Yi,et al.Optimal capacity allocation of energy storage in micro-grid with distributed generation[J].Power System Protection and Control,2016,44(3):78-84.
[3]杨新法,苏剑,吕志鹏,等.微电网技术综述[J].中国电机工程学报,2014,34(1):57-70.YANG Xinfa,SU Jian,LüZhipeng,et al.Overview on microgrid technology[J].Proceedings of the CSEE,2014,34(1):57-70.
[4]范龙,李献梅,陈跃辉,等.激励CCHP参与需求侧管理双向峰谷定价模型[J].电力系统保护与控制,2016,44(17):45-51.FAN Long,LI Xianmei,CHEN Yuehui,et al.Pricing model of bidirectional peak-valley for motivating CCHPto participate in DSM[J].Power System Protection and Control,2016,44(17):45-51.
[5]LI Han,ESEYE A T,ZHANG Jianhua,et al.Optimal energy management for industrial microgrids with high-penetration renewable[J].Protection and Control of Modern Power Systems,2017,2(2):122-135.DOI:10.1186/s41601-017-0040-6.
[6]李正茂,张峰,梁军,等.计及附加机会收益的冷热电联供型微电网动态调度[J].电力系统自动化,2015,39(14):8-15.LI Zhengmao,ZHANG Feng,LIANG Jun,et al.Dynamic scheduling of CCHP type of microgrid considering additional opportunity income[J].Automation of Electric Power Systems,2015,39(14):8-15.
[7]王成山,王守相.分布式发电功能系统若干问题研究[J].电力系统自动化,2008,32(20):1-4.WANG Chengshan,WANG Shouxiang.Study on some key problems related to distributed generation systems[J].Automation of Electric Power Systems,2008,32(20):1-4.
[8]WANG J J,JING Y Y,ZHANG C F.Optimization of capacity and operation for CCHP system by genetic algorithm[J].Applied Energy,2010,87(4):1325-1335.
[9]王锐,顾伟,吴志.含可再生能源的热电联供型微网经济运行优化[J].电力系统自动化,2011,35(8):1-6.WANG Rui,GU Wei,WU Zhi.Optimization of economic operation in CHP micro grid including renewable energy[J].Automation of Electric Power Systems,2011,35(8):1-6.
[10]吴宏斌,王东旭,刘星月.太阳能冷热电联供系统的策略评估和优化配置[J].电力系统自动化,2015,39(21):46-51.WU Hongbin,WANG Dongxu,LIU Xingyue.Strategies evaluation and optimal allocation of combined cooling heating and power system with solar[J].Automation of Electric Power Systems,2015,39(21):46-51.
[11]魏大均,孙波,赵峰,等.小型生物质沼气冷热电联供系统多目标优化设计与运行分析[J].电力系统自动化,2015,39(12):7-12.WEI Dajun,SUN Bo,ZHAO Feng,et al.Multi-objective optimization design and operation analysis of small biomass biogas combined cooling heating and power system[J].Automation of Electric Power Systems,2015,39(12):7-12.
[12]肖小清,阚伟民,杨允,等.有蓄能的联供系统超结构优化配置[J].中国电机工程学报,2012,32(32):8-14.XIAO Xiaoqing,KAN Weimin,YANG Yun,et al.Superstructure-based optimal planning of cogeneration systems with storage[J].Proceeding of the CSEE,2012,32(32):8-14.
[13]WANG J J,ZHAI Z Q,JING Y Y,et al.Particle swarm optimization for redundant building cooling heating and power system[J].Applied Energy,2010,87(12):3668-3679.
[14]WANG J J,ZHANG C F,JING Y Y.Multi-criteria analysis of combined cooling,heating and power systems in different climate zones in China[J].Applied Energy,2010,87(4):1247-1259.
[15]李朝振,石玉美,黄兴华.负荷结构对冷热电联供系统优化配置的影响[J].热能动力工程,2008,23(6):606-610.LI Zhaozhen,SHI Yumei,HUANG Xinghua.Influence of load composition on the optimized configuration of a combined cooling,heating and power cogeneration system[J].Journal of Engineering for Thermal Energy and Power,2008,23(6):606-610.
[16]唐学军,韩佶,苗世洪,等.基于需求侧响应的多类型负荷协调控制模型[J].电力系统保护与控制,2017,45(16):116-123.TANG Xuejun,HAN Ji,MIAO Shihong,et al.Coordinated control model of multi-type load based on demand response[J].Power System Protection and Control,2017,45(16):116-123.
[17]刘丽军,李捷,蔡金锭.基于强引导粒子群和混沌优化的电力系统无功优化[J].电力自动化设备,2010,30(4):71-75.LIU Lijun,LI Jie,CAI Jinding.Reactive power optimization based on induction-enhanced particle swarm optimization and chaos search[J].Electric Power Automation Equipment,2010,30(4):71-75.
[18]韩晓娟,程成,籍天明,等.计及电池使用寿命的混合储能系统容量优化模型[J].中国电机工程学报,2013,33(34):83-89.HAN Xiaojuan,CHENG Cheng,JI Tianming,et al.Capacity optimal modeling of hybrid energy storage systems considering battery life[J].Proceedings of the CSEE,2013,33(34):83-89.
[19]邢龙,张沛超,方陈,等.基于广义需求侧资源的微电网运行优化[J].电力系统自动化,2013,37(12):7-12.XING Long,ZHANG Peichao,FANG Chen,et al.Optimal operation for microgrid using generalized demand side resources[J].Automation of Electric Power Systems,2013,37(12):7-12.
[20]张颖,容展鹏,张宇雄,等.基于微电网的电网需求响应研究[J].电力系统保护与控制,2015,43(21):20-26.ZHANG Ying,RONG Zhanpeng,ZHANG Yuxiong,et al.Study of grid demand response based on micro grid[J].Power System Protection and Control,2015,43(21):20-26.
[21]毛晓明,陈深,吴杰康,等.分时电价机制下含蓄电池微电网的优化调度[J].电网技术,2015,39(5):1192-1197.MAO Xiaoming,CHEN Shen,WU Jiekang,et al.Optimal dispatching of microgrid containing battery under time-of-use price mechanism[J].Power System Technology,2015,39(5):1192-1197.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |