促进风电消纳的配电网分布式电源与电动汽车充电站联合鲁棒规划
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摘要
分布式风电出力的不确定性和波动性会影响配电网运行。文章对配电网中的风电以及电动汽车充电桩进行联合优化配置,使其适应分布式风电的不确定性,提高了配电网对风电的消纳能力。同时,提出综合考虑网损成本、购电成本、投资成本以及弃风成本的鲁棒规划模型,并通过利用二阶锥松弛技术以及"ε松弛"法对模型进行线性化处理,并引入线性优化强对偶理论对转化后的模型进行对偶求解。最后算例证明了所提模型的有效性。
Biomass cookstove as a traditional cooking utility, has a long history and is widely used in China. Biomass stoves experienced several development phases since the 1980 s leading to the improvement of standards for biomass stoves testing method. The impacts of biomass cookstoves on air quality and health is serious, but currentlyIn the recent years, wind power has been widely deployed in the distribution network(DN) because of its energy-saving, environmental friendly and high flexibility. However, it has significant uncertainty and volatility, which will bring great challenge to the planning and operation of DN. This paper focuses on the joint planning of distributed generation and electric vehicle charging stations so as to improve the ability of DN to accommodate the wind power, and make it adapt to the uncertainty of wind power. Therefore, a robust model which considers the cost of network loss, power purchasing, investment and wind curtailment is presented. The second-order cone relaxation techniques and "ε relaxation" method is deployed to linearize the primal model, then strong duality theory is introduced transfer it into an equivalent maximization problem. Finally, experiment results indicate the effectiveness of the presented method.
Biomass cookstove as a traditional cooking utility, has a long history and is widely used in China. Biomass stoves experienced several development phases since the 1980 s leading to the improvement of standards for biomass stoves testing method. The impacts of biomass cookstoves on air quality and health is serious, but currentlyIn the recent years, wind power has been widely deployed in the distribution network(DN) because of its energy-saving, environmental friendly and high flexibility. However, it has significant uncertainty and volatility, which will bring great challenge to the planning and operation of DN. This paper focuses on the joint planning of distributed generation and electric vehicle charging stations so as to improve the ability of DN to accommodate the wind power, and make it adapt to the uncertainty of wind power. Therefore, a robust model which considers the cost of network loss, power purchasing, investment and wind curtailment is presented. The second-order cone relaxation techniques and "ε relaxation" method is deployed to linearize the primal model, then strong duality theory is introduced transfer it into an equivalent maximization problem. Finally, experiment results indicate the effectiveness of the presented method.
引文
[1]马钊,周孝信,尚宇炜,等.未来配电系统形态及发展趋势[J].中国电机工程学报,2015,35(6):1289-1298.
[2]桑静静,赵庆生,何志方.光伏并网对配电网电压及网损的影响[J].可再生能源,2013,31(4):11-14,19.
[3]汪文达,崔雪,马兴,等.考虑多个风电机组接入配电网的多目标无功优化[J].电网技术,2015,39(7):1860-1865.
[4]丁明,石雪梅.新能源接入对主动配电网的影响[J].电力建设,2015,36(1):76-84.
[5]王成山,陈恺,谢莹华,等.配电网扩展规划中分布式电源的选址和定容[J].电力系统自动化,2006,30(3):38-43.
[6]王再闯,袁铁江,李永东,等.基于储能电站提高风电消纳能力的电源规划研究[J].可再生能源,2014,32(7):954-960.
[7]贾龙,胡泽春,宋永华,等.储能和电动汽车充电站与配电网的联合规划研究[J].中国电机工程学报,2017,37(1):73-84.
[8]杨毅,韦钢,周冰,等.含分布式电源的配电网模糊优化规划[J].电力系统自动化,2010,34(13):19-23.
[9]曾鸣,杜楠,张鲲,等.基于多目标静态模糊模型的分布式电源规划[J].电网技术,2013,37(4):954-959.
[10]白牧可,唐巍,张璐,等.基于机会约束规划的DG与配电网架多目标协调规划[J].电工技术学报,2013,28(10):346-354.
[11]丛鹏伟,唐巍,张璐,等.基于机会约束规划考虑DG与负荷多状态的配电网重构[J].电网技术,2013,37(9):2573-2579.
[12]张沈习,程浩忠,邢海军,等.配电网中考虑不确定性的分布式电源规划研究综述[J].电力自动化设备,2016,36(8):1-9.
[13] Dutta S,Sharma R.Optimal storage sizing for integrating wind and load forecast uncertainties[A].2012 IEEE PES Innovative Smart Grid Technologies(ISGT)[C].Washington DC:IEEE,2012.1-7.
[14]梅生伟,郭文涛,王莹莹,等.一类电力系统鲁棒优化问题的博弈模型及应用实例[J].中国电机工程学报,2013,33(19):47-56,20.
[15]高红均,刘俊勇,魏震波.主动配电网分层鲁棒规划模型及其求解方法[J].中国电机工程学报,2017,37(5):1389-1400.
[16]温俊强,曾博,张建华.配电网中分布式风电可调鲁棒优化规划[J].电网技术,2016,40(1):227-233.
[17]李洪美,崔翰韬,万秋兰.考虑电动汽车充电策略的配网重构二阶锥规划模型[J].中国电机工程学报,2015,35(18):4674-4681.
[18] Ra Jabr.Radial distribution load flow using conic programming[J].IEEE Transactions on Power Systems,2006,21(3):1458-1459.
[19]郭小璇,龚仁喜,鲍海波,等.含新能源电力系统机会约束经济调度的二阶锥规划方法[J].电力系统保护与控制,2015,43(22):85-91.
[20] Beck A,Ben Tal A.Duality in robust optimization:primal worst equals dual best[J].Operations Research Letters,2009,37(1):1-6.
[21]李秀磊,耿光飞.主动配电网中储能和需求侧响应的联合优化规划[J].电网技术,2016,40(12):3803-3810.
[2]桑静静,赵庆生,何志方.光伏并网对配电网电压及网损的影响[J].可再生能源,2013,31(4):11-14,19.
[3]汪文达,崔雪,马兴,等.考虑多个风电机组接入配电网的多目标无功优化[J].电网技术,2015,39(7):1860-1865.
[4]丁明,石雪梅.新能源接入对主动配电网的影响[J].电力建设,2015,36(1):76-84.
[5]王成山,陈恺,谢莹华,等.配电网扩展规划中分布式电源的选址和定容[J].电力系统自动化,2006,30(3):38-43.
[6]王再闯,袁铁江,李永东,等.基于储能电站提高风电消纳能力的电源规划研究[J].可再生能源,2014,32(7):954-960.
[7]贾龙,胡泽春,宋永华,等.储能和电动汽车充电站与配电网的联合规划研究[J].中国电机工程学报,2017,37(1):73-84.
[8]杨毅,韦钢,周冰,等.含分布式电源的配电网模糊优化规划[J].电力系统自动化,2010,34(13):19-23.
[9]曾鸣,杜楠,张鲲,等.基于多目标静态模糊模型的分布式电源规划[J].电网技术,2013,37(4):954-959.
[10]白牧可,唐巍,张璐,等.基于机会约束规划的DG与配电网架多目标协调规划[J].电工技术学报,2013,28(10):346-354.
[11]丛鹏伟,唐巍,张璐,等.基于机会约束规划考虑DG与负荷多状态的配电网重构[J].电网技术,2013,37(9):2573-2579.
[12]张沈习,程浩忠,邢海军,等.配电网中考虑不确定性的分布式电源规划研究综述[J].电力自动化设备,2016,36(8):1-9.
[13] Dutta S,Sharma R.Optimal storage sizing for integrating wind and load forecast uncertainties[A].2012 IEEE PES Innovative Smart Grid Technologies(ISGT)[C].Washington DC:IEEE,2012.1-7.
[14]梅生伟,郭文涛,王莹莹,等.一类电力系统鲁棒优化问题的博弈模型及应用实例[J].中国电机工程学报,2013,33(19):47-56,20.
[15]高红均,刘俊勇,魏震波.主动配电网分层鲁棒规划模型及其求解方法[J].中国电机工程学报,2017,37(5):1389-1400.
[16]温俊强,曾博,张建华.配电网中分布式风电可调鲁棒优化规划[J].电网技术,2016,40(1):227-233.
[17]李洪美,崔翰韬,万秋兰.考虑电动汽车充电策略的配网重构二阶锥规划模型[J].中国电机工程学报,2015,35(18):4674-4681.
[18] Ra Jabr.Radial distribution load flow using conic programming[J].IEEE Transactions on Power Systems,2006,21(3):1458-1459.
[19]郭小璇,龚仁喜,鲍海波,等.含新能源电力系统机会约束经济调度的二阶锥规划方法[J].电力系统保护与控制,2015,43(22):85-91.
[20] Beck A,Ben Tal A.Duality in robust optimization:primal worst equals dual best[J].Operations Research Letters,2009,37(1):1-6.
[21]李秀磊,耿光飞.主动配电网中储能和需求侧响应的联合优化规划[J].电网技术,2016,40(12):3803-3810.