考虑资源相关性和不确定性的负荷需求响应决策研究
|
摘要
需求响应(demand response,DR)具有一定的不确定性,为了真实地反映各不确定性用户的响应情况,文章考虑了以空调为代表的不确定性用户资源之间在空间和时间上响应度的相关性。首先采用拉丁超立方采样法对响应度进行规模采样和相关性控制,得到反映响应相关性的样本。其次引入确定性资源,建立负荷聚合商(load aggregator,LA)的最优决策模型,并通过随机模拟和智能算法求解利润最高时的决策方案。最后通过算例分析了确定性资源、相关性及响应度的分布参数对决策方案和利润的影响,验证了订购确定性资源,签约负相关的不确定性用户,提高响应度的均值,降低响应度的方差均对利润有着显著的提高。
The demand response (DR) has certain uncertainty. In order to truly reflect the response of each uncertain user,this paper considers the correlation between spatial and temporal responsiveness of uncertain user resources represented by air conditioning. Firstly,the improved Latin hypercube sampling method is used to scale and correlate the responsivity,and the samples reflecting the response correlation are obtained. Secondly,the deterministic resources are introduced to establish the optimal decision model of the load aggregator (LA),and the decision-making scheme is solved by the algorithm when the profit is the highest through random simulation and intelligence. Finally,an example is given to analyze the influence of the distribution parameters of deterministic resources, correlation and responsiveness on decision-making schemes and profits. Measures that can increase the profit include ordering deterministic resources,signing negative related uncertain users,increasing the average of responsiveness,reducing the variance of responsiveness.
The demand response (DR) has certain uncertainty. In order to truly reflect the response of each uncertain user,this paper considers the correlation between spatial and temporal responsiveness of uncertain user resources represented by air conditioning. Firstly,the improved Latin hypercube sampling method is used to scale and correlate the responsivity,and the samples reflecting the response correlation are obtained. Secondly,the deterministic resources are introduced to establish the optimal decision model of the load aggregator (LA),and the decision-making scheme is solved by the algorithm when the profit is the highest through random simulation and intelligence. Finally,an example is given to analyze the influence of the distribution parameters of deterministic resources, correlation and responsiveness on decision-making schemes and profits. Measures that can increase the profit include ordering deterministic resources,signing negative related uncertain users,increasing the average of responsiveness,reducing the variance of responsiveness.
引文
[1]段翩,朱建全,刘明波,等.基于双层模糊机会约束规划的虚拟电厂优化调度[J].电工技术学报,2016,31(9):58-67.DUAN Pian,ZHU Jianquan,LIU M ingbo,et al.Optimal dispatch of virtual pow er plant based on bi-level fuzzy chance constrained programming[J].Transactions of China Electrotechnical Society,2016,31(9):58-67.
[2]俞敏,倪琳娜,方鹏,等.计及分布式发电出力与电价不确定性的负荷聚合商电能获取策略[J].电力建设,2018,39(1):10-18.YU M in,NI Linna,FANG Peng,et al.Electrical energy acquisition strategy for load aggregators considering combined uncertainties of distributed generation outputs and electricity market prices[J].Electric Pow er Construction,2018,39(1):10-18.
[3]彭文昊,陆俊,冯勇军,等.计及用户参与不确定性的需求响应策略优化方法[J].电网技术,2018,42(5):1588-1594.PENG Wenhao,LU Jun,FENG Yongjun,et al.A demand response strategy optimization considering user participation uncertainty[J].Pow er System Technology,2018,42(5):1588-1594.
[4]赵冬梅,殷加玞.考虑源荷双侧不确定性的模糊随机机会约束优先目标规划调度模型[J].电工技术学报,2018,33(5):1076-1085.ZHAO Dongmei,YIN Jiafu.Fuzzy random chance constrained preemptive goal programming scheduling model considering sourceside and load-side uncertainty[J].Transactions of China Electrotechnical Society,2018,33(5):1076-1085.
[5]ZHAO C Y,WANG J H,WATSON J P,et al.Multi-stage robust unit commitment considering w ind and demand response uncertainties[J].IEEE Transactions on Power Systems,2013,28(3):2708-2717.
[6]孙博宇,喻洁,梅军,等.考虑可调负荷集群响应不确定性的联合调度模型[J].电力系统保护与控制,2016,44(23):61-67.SUN Boyu,YU Jie,M EI Jun,et al.Combined dispatch model of adjustable load clusters considering response uncertainty[J].Pow er System Protection and Control,2016,44(23):61-67.
[7]王蓓蓓,孙宇军,李扬,等.不确定性需求响应建模在电力积分激励决策中的应用[J].电力系统自动化,2015,39(10):93-99,150.WANG Beibei,SUN Yujun,LI Yang,et al.Application of uncertain demand response modeling in pow er-score incentive decision[J].Automation of Electric Pow er Systems,2015,39(10):93-99,150.
[8]曾丹,姚建国,杨胜春,等.计及价格型负荷响应不确定性的概率潮流计算[J].电力系统自动化,2015,39(20):66-71,97.ZENG Dan,YAO Jianguo,YANG Shengchun,et al.Probabilistic load flow calculation considering price-elasticity load uncertainties[J].Automation of Electric Power Systems,2015,39(20):66-71,97.
[9]司小庆,曹卫国,任善荣,等.空调负荷实现电网有序削峰的实证研究[J].电气技术,2014(1):47-51.SI Xiaoqing,CAO Weiguo,REN Shanrong,et al.Demonstration research on air conditioning load shaving pow er grid peak orderly[J].Electrical Engineering,2014(1):47-51.
[10]蒋程,王硕,王宝庆,等.基于拉丁超立方采样的含风电电力系统的概率可靠性评估[J].电工技术学报,2016,31(10):193-206.JIANG Cheng,WANG Shuo,WANG Baoqing,et al.Probabilistic reliability assessment of pow er system containing w ind pow er based on latin hypercube sampling[J].Transactions of China Electrotechnical Society,2016,31(10):193-206.
[11]孙腾飞,程浩忠,张立波,等.基于改进混合抽样与最小切负荷计算的电力系统可靠性评估方法[J].电力系统保护与控制,2016,44(13):96-103.SUN Tengfei,CHENG Haozhong,ZHANG Libo,et al.Reliability evaluation based on modified mixed sampling and minimum loadcutting method[J].Pow er System Protection and Control,2016,44(13):96-103.
[12]CHEN Y,WEN J Y,CHENG S J.Probabilistic load flow method based on nataf transformation and latin hypercube sampling[J].IEEE Transactions on Sustainable Energy,2013,4(2):294-301.
[13]缪鹏彬,余娟,史乐峰,等.基于改进非参数核密度估计和拉丁超立方抽样的电动公共客车负荷模型[J].电工技术学报,2016,31(4):187-193.M IAO Pengbin,YU Juan,SHI Lefeng,et al.Electric public bus load model based on improved kernel density estimation and latin hypercube sampling[J].Transactions of China Electrotechnical Society,2016,31(4):187-193.
[14]李俊芳,张步涵.基于进化算法改进拉丁超立方抽样的概率潮流计算[J].中国电机工程学报,2011,31(25):90-96.LI Junfang,ZHANG Buhan.Probabilistic load flow based on improved latin hypercube sampling w ith evolutionary algorithm[J].Proceedings of the CSEE,2011,31(25):90-96.
[15]高赐威,李倩玉,李慧星,等.基于负荷聚合商业务的需求响应资源整合方法与运营机制[J].电力系统自动化,2013,37(17):78-86.GAO Ciw ei,LI Qianyu,LI Huixing,et al.M ethodology and operation mechanism of demand response resources integration based on load aggregator[J].Automation of Electric Pow er Systems,2013,37(17):78-86.
[16]VRETTOS E,OLDEWURTEL F,VASIRANI M,et al.Centralized and decentralized balance group optimization in electricity markets w ith demand response[C]//2013 IEEEGrenoble Conference.Grenoble,France:IEEE,2013:1-6.
[17]唐早,刘俊勇,刘友波,等.空调聚合商参与下的负荷控制与配电网重构[J].电力系统自动化,2018,42(2):42-49.TANG Zao,LIU Junyong,LIU Youbo,et al.Load control and distribution netw ork reconfiguration w ith participation of airconditioning load aggregators[J].Automation of Electric Pow er Systems,2018,42(2):42-49.
[18]张开宇,宋依群,严正,等.考虑用户违约可能的负荷聚合商储能配置策略[J].电力系统自动化,2015,39(17):127-133.ZHANG Kaiyu,SONG Yiqun,YAN Zheng,et al.Energy storage capacity optimization for load aggregators considering probability of demand response resources'breach[J].Automation of Electric Pow er Systems,2015,39(17):127-133.
[19]XU Y X,XIE L,SINGH C.Optimal scheduling and operation of load aggregator w ith electric energy storage in pow er markets[C]//North American Pow er Symposium 2010.Arlington,TX,USA:IEEE,2010:1-7.
[20]高赐威,李倩玉,李扬,等.基于DLC的空调负荷双层优化调度和控制策略[J].中国电机工程学报,2014,34(10):1546-1555.GAO Ciw ei,LI Qianyu,LI Yang,et al.Bi-level optimal dispatch and control strategy for air-conditioning load based on direct load control[J].Proceedings of the CSEE,2014,34(10):1546-1555.
[21]韩笑,周明,李庚银,等.计及储能和空调负荷的主动配电网多目标优化调度[J].电力系统保护与控制,2018,46(7):14-23.HAN Xiao,ZHOU M ing,LI Gengyin,et al.M ulti-objective optimal dispatching of active distribution netw orks considering energy storage systems and air-conditioning loads[J].Pow er System Protection and Control,2018,46(7):14-23.
[2]俞敏,倪琳娜,方鹏,等.计及分布式发电出力与电价不确定性的负荷聚合商电能获取策略[J].电力建设,2018,39(1):10-18.YU M in,NI Linna,FANG Peng,et al.Electrical energy acquisition strategy for load aggregators considering combined uncertainties of distributed generation outputs and electricity market prices[J].Electric Pow er Construction,2018,39(1):10-18.
[3]彭文昊,陆俊,冯勇军,等.计及用户参与不确定性的需求响应策略优化方法[J].电网技术,2018,42(5):1588-1594.PENG Wenhao,LU Jun,FENG Yongjun,et al.A demand response strategy optimization considering user participation uncertainty[J].Pow er System Technology,2018,42(5):1588-1594.
[4]赵冬梅,殷加玞.考虑源荷双侧不确定性的模糊随机机会约束优先目标规划调度模型[J].电工技术学报,2018,33(5):1076-1085.ZHAO Dongmei,YIN Jiafu.Fuzzy random chance constrained preemptive goal programming scheduling model considering sourceside and load-side uncertainty[J].Transactions of China Electrotechnical Society,2018,33(5):1076-1085.
[5]ZHAO C Y,WANG J H,WATSON J P,et al.Multi-stage robust unit commitment considering w ind and demand response uncertainties[J].IEEE Transactions on Power Systems,2013,28(3):2708-2717.
[6]孙博宇,喻洁,梅军,等.考虑可调负荷集群响应不确定性的联合调度模型[J].电力系统保护与控制,2016,44(23):61-67.SUN Boyu,YU Jie,M EI Jun,et al.Combined dispatch model of adjustable load clusters considering response uncertainty[J].Pow er System Protection and Control,2016,44(23):61-67.
[7]王蓓蓓,孙宇军,李扬,等.不确定性需求响应建模在电力积分激励决策中的应用[J].电力系统自动化,2015,39(10):93-99,150.WANG Beibei,SUN Yujun,LI Yang,et al.Application of uncertain demand response modeling in pow er-score incentive decision[J].Automation of Electric Pow er Systems,2015,39(10):93-99,150.
[8]曾丹,姚建国,杨胜春,等.计及价格型负荷响应不确定性的概率潮流计算[J].电力系统自动化,2015,39(20):66-71,97.ZENG Dan,YAO Jianguo,YANG Shengchun,et al.Probabilistic load flow calculation considering price-elasticity load uncertainties[J].Automation of Electric Power Systems,2015,39(20):66-71,97.
[9]司小庆,曹卫国,任善荣,等.空调负荷实现电网有序削峰的实证研究[J].电气技术,2014(1):47-51.SI Xiaoqing,CAO Weiguo,REN Shanrong,et al.Demonstration research on air conditioning load shaving pow er grid peak orderly[J].Electrical Engineering,2014(1):47-51.
[10]蒋程,王硕,王宝庆,等.基于拉丁超立方采样的含风电电力系统的概率可靠性评估[J].电工技术学报,2016,31(10):193-206.JIANG Cheng,WANG Shuo,WANG Baoqing,et al.Probabilistic reliability assessment of pow er system containing w ind pow er based on latin hypercube sampling[J].Transactions of China Electrotechnical Society,2016,31(10):193-206.
[11]孙腾飞,程浩忠,张立波,等.基于改进混合抽样与最小切负荷计算的电力系统可靠性评估方法[J].电力系统保护与控制,2016,44(13):96-103.SUN Tengfei,CHENG Haozhong,ZHANG Libo,et al.Reliability evaluation based on modified mixed sampling and minimum loadcutting method[J].Pow er System Protection and Control,2016,44(13):96-103.
[12]CHEN Y,WEN J Y,CHENG S J.Probabilistic load flow method based on nataf transformation and latin hypercube sampling[J].IEEE Transactions on Sustainable Energy,2013,4(2):294-301.
[13]缪鹏彬,余娟,史乐峰,等.基于改进非参数核密度估计和拉丁超立方抽样的电动公共客车负荷模型[J].电工技术学报,2016,31(4):187-193.M IAO Pengbin,YU Juan,SHI Lefeng,et al.Electric public bus load model based on improved kernel density estimation and latin hypercube sampling[J].Transactions of China Electrotechnical Society,2016,31(4):187-193.
[14]李俊芳,张步涵.基于进化算法改进拉丁超立方抽样的概率潮流计算[J].中国电机工程学报,2011,31(25):90-96.LI Junfang,ZHANG Buhan.Probabilistic load flow based on improved latin hypercube sampling w ith evolutionary algorithm[J].Proceedings of the CSEE,2011,31(25):90-96.
[15]高赐威,李倩玉,李慧星,等.基于负荷聚合商业务的需求响应资源整合方法与运营机制[J].电力系统自动化,2013,37(17):78-86.GAO Ciw ei,LI Qianyu,LI Huixing,et al.M ethodology and operation mechanism of demand response resources integration based on load aggregator[J].Automation of Electric Pow er Systems,2013,37(17):78-86.
[16]VRETTOS E,OLDEWURTEL F,VASIRANI M,et al.Centralized and decentralized balance group optimization in electricity markets w ith demand response[C]//2013 IEEEGrenoble Conference.Grenoble,France:IEEE,2013:1-6.
[17]唐早,刘俊勇,刘友波,等.空调聚合商参与下的负荷控制与配电网重构[J].电力系统自动化,2018,42(2):42-49.TANG Zao,LIU Junyong,LIU Youbo,et al.Load control and distribution netw ork reconfiguration w ith participation of airconditioning load aggregators[J].Automation of Electric Pow er Systems,2018,42(2):42-49.
[18]张开宇,宋依群,严正,等.考虑用户违约可能的负荷聚合商储能配置策略[J].电力系统自动化,2015,39(17):127-133.ZHANG Kaiyu,SONG Yiqun,YAN Zheng,et al.Energy storage capacity optimization for load aggregators considering probability of demand response resources'breach[J].Automation of Electric Pow er Systems,2015,39(17):127-133.
[19]XU Y X,XIE L,SINGH C.Optimal scheduling and operation of load aggregator w ith electric energy storage in pow er markets[C]//North American Pow er Symposium 2010.Arlington,TX,USA:IEEE,2010:1-7.
[20]高赐威,李倩玉,李扬,等.基于DLC的空调负荷双层优化调度和控制策略[J].中国电机工程学报,2014,34(10):1546-1555.GAO Ciw ei,LI Qianyu,LI Yang,et al.Bi-level optimal dispatch and control strategy for air-conditioning load based on direct load control[J].Proceedings of the CSEE,2014,34(10):1546-1555.
[21]韩笑,周明,李庚银,等.计及储能和空调负荷的主动配电网多目标优化调度[J].电力系统保护与控制,2018,46(7):14-23.HAN Xiao,ZHOU M ing,LI Gengyin,et al.M ulti-objective optimal dispatching of active distribution netw orks considering energy storage systems and air-conditioning loads[J].Pow er System Protection and Control,2018,46(7):14-23.