居民用户参与电网调峰激励机制及优化用电策略研究
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摘要
随着居民用电占比的不断提升,以及智能电表和智能家电在居民用户中的普及,开发居民用户的需求响应潜力对提高电网灵活调节能力是非常必要的。该文以居民负荷参与电网调峰为切入点,首先建立兼顾用户用电舒适度的居民用户各类电器的负荷模型;其次,基于现有分时电价机制不足以调动居民用户参与电网调峰的积极性及可能形成新的负荷高峰的情况,从居民负荷与系统负荷的相关性出发,提出了反映居民用电对电网调峰贡献度的调峰激励机制,并进行了合理性证明;最后综合考虑用电成本、舒适度和调峰激励建立了居民用户用电优化策略。仿真分析表明,所提出的调峰激励机制能够兼顾居民用户和电网的利益,是一种对现有固定/分时电价有效补充的激励机制,能进一步减少居民用户用电成本,降低其负荷峰值,响应电网削峰填谷的需要,实现居民用户与电网的友好互动。
With increasing ratio of residential load and popularization of smart meters and smart appliances in residential users, it is necessary to develop demand response potential of residential users to improve flexibility of power grid operation. This paper focuses on participation of residential load in peak shaving of power grid. Firstly, load models of various appliances considering user's comfort are established. Then, based on the situation that current time-of-use electricity price is not enough to arouse enthusiasm of residential users to participate in peak shaving of power grid and may create new load peaks, starting from the correlation between residential load and system load, a peak shaving incentive mechanism is put forward, reflecting the contribution of residential power consumption to peak shaving, and then its rationality is proved. Finally, electricity cost, comfort degree and the incentive are synthesized to form an optimal power consumption strategy for residential users. Simulation results show that the proposed incentive mechanism, taking account of the interests of both residents and power grid, is an effective supplementary incentive for fixed or time-of-use electricity price mechanism. It can reduce electricity cost and the peak load of residential users, conform to need of peak load shifting, and therefore realize friendly interaction between residential users and power grid.
With increasing ratio of residential load and popularization of smart meters and smart appliances in residential users, it is necessary to develop demand response potential of residential users to improve flexibility of power grid operation. This paper focuses on participation of residential load in peak shaving of power grid. Firstly, load models of various appliances considering user's comfort are established. Then, based on the situation that current time-of-use electricity price is not enough to arouse enthusiasm of residential users to participate in peak shaving of power grid and may create new load peaks, starting from the correlation between residential load and system load, a peak shaving incentive mechanism is put forward, reflecting the contribution of residential power consumption to peak shaving, and then its rationality is proved. Finally, electricity cost, comfort degree and the incentive are synthesized to form an optimal power consumption strategy for residential users. Simulation results show that the proposed incentive mechanism, taking account of the interests of both residents and power grid, is an effective supplementary incentive for fixed or time-of-use electricity price mechanism. It can reduce electricity cost and the peak load of residential users, conform to need of peak load shifting, and therefore realize friendly interaction between residential users and power grid.
引文
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[21]纪姝彦.面向智能用电的家庭能量管理研究[D].合肥:合肥工业大学,2017.
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[23]曾雪婷,刘天琪,李茜,等.基于虚拟电源配置策略的风光水火多源互补短期优化调度[J].电网技术,2016,40(5):1379-1386.Zeng Xueting,Liu Tianqi,Li Qian,et al.Short-term complementary optimal dispatch model of multi-source hybrid power system based on virtual power configuration strategy[J].Power System Technology,2016,40(5):1379-1386(in Chinese).
[24]罗洪飞.基于非合作博弈及多目标优化的居民用户智能用电策略研究[D].重庆:重庆大学,2016.
[25]梅坚,杨立兵,李晓刚,等.调峰市场效用分析与低谷调峰市场设计[J].电力系统自动化,2013,37(21):134-138.Mei Jian,Yang Libin,Li Xiaogang,et al.Utility analysis for peak regulation market and trading market design for peak regulation capacity in valley time[J].Automation of Electric Power Systems,2013,37(21):134-138(in Chinese).
[2]杨旭英,周明,李庚银.智能电网下需求响应机理分析与建模综述[J].电网技术,2016,40(1):220-226.Yang Xuying,Zhou Ming,Li Gengyin.Survey on demand response mechanism and modeling in smart grid[J].Power System Technology,2016,40(1):220-226(in Chinese).
[3]李斌,顾国栋.江苏电力负荷管理的创新及实践[J].电力需求侧管理,2015,17(5):1-4.Li Bin,Gu Guodong.Innovation and practice of Jiangsu’s power demand side[J].Power Demand Side Management,2015,17(5):1-4(in Chinese).
[4]Rodriguez Diaz E,Palacios Garcia E J,Savaghebi M,et al.Development and integration of a HEMS with an advanced smart metering infrastructure[C]//IEEE International Conference on Consumer Electronics.Las Vegas,the United States:IEEE,2016:544-545.
[5]张延宇,曾鹏,李忠文,等.智能电网环境下空调系统多目标优化控制算法[J].电网技术,2014,38(7):1819-1826.Zhang Yanyu,Zeng Peng,Li Zhongwen,et al.A multi-objective optimal control algorithm for air conditioning system in smart grid[J].Power System Technology,2014,38(7):1819-1826(in Chinese).
[6]杨永标,颜庆国,王冬,等.居民用户智能用电建模及优化仿真分析[J].电力系统自动化,2016,40(3):46-51.Yang Yongbiao,Yan Qingguo,Wang Dong,et al.Intelligent electricity consumption modeling and optimal simulations for residential users[J].Automation of Electric Power Systems,2016,40(3):46-51(in Chinese).
[7]Roh H T,Lee J W.Residential demand response scheduling with multiclass appliances in the smart grid[J].IEEE Transactions on Smart Grid,2016,7(1):94-104.
[8]徐建军,王保娥,闫丽梅,等.混合能源协同控制的智能家庭能源优化控制策略[J].电工技术学报,2017,32(12):214-223.Xu Jianjun,Wang Bao E,Yan Limei,et al.The strategy of the smart home energy optimization control of the hybrid energy coordinated control[J].Transactions of China Electrotechnical Society,2017,32(12):214-223(in Chinese).
[9]樊玮,刘念,张建华.事件驱动的智能家庭在线能量管理算法[J].电工技术学报,2016,31(13):130-140.Fan Wei,Liu Nian,Zhang Jianhua.An online algorithm based on event triggering for energy management of smart home[J].Transactions of China Electrotechnical Society,2016,31(13):130-140(in Chinese).
[10]Althaher S,Mancarella P,Mutale J.Automated demand response from home energy management system under dynamic pricing and power and comfort constraints[J].IEEE Transactions on Smart Grid,2015,6(4):1874-1883.
[11]陆俊,彭文昊,朱炎平,等.基于粒子校正优化的智能小区需求响应调度策略[J].电网技术,2017,41(7):2370-2377.Lu Jun,Peng Wenhao,Zhu Yanping,et al.A scheduling strategy based on particle correction for intelligent power demand response[J].Power System Technology,2017,41(7):2370-2377(in Chinese).
[12]Yu Y,Liu G,Zhu W,et al.Good consumer or bad consumer:economic information revealed from demand profiles[J].IEEETransactions on Smart Grid,2018,9(3):2347-2358.
[13]Gu Chenghong,Yan Xiaohe,Yan Zhang,et al.Dynamic pricing for responsive demand to increase distribution network efficiency[J].Applied Energy,2017(205):236-243.
[14]张良,严正,冯冬涵,等.采用两阶段优化模型的电动汽车充电站内有序充电策略[J].电网技术,2014,38(4):967-973.Zhang Liang,Yan Zheng,Feng Donghan,et al.Two-stage optimization model based coordinated charging for EV charging station[J].Power System Technology,2014,38(4):967-973(in Chinese).
[15]Chen Z,Wu L,Fu Y.Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization[J].IEEE Transactions on Smart Grid,2012,3(4):1822-1831.
[16]Zhao Z,Lee W C,Shin Y,et al.An optimal power scheduling method for demand response in home energy management system[J].IEEETransactions on Smart Grid,2013,4(3):1391-1400.
[17]唐佳,王丹,贾宏杰,等.基于迟滞模型的集群电动汽车参与实时需求响应V2G控制策略研究[J].电网技术,2017,41(7):2155-2165.Tang Jia,Wang Dan,Jia Hongjie,et al.A study of V2G control strategies of aggregated electric vehicles for real-time demand response based on hysteresis model[J].Power System Technology,2017,41(7):2155-2165(in Chinese).
[18]Deng R,Yang Z,Chow M Y,et al.A survey on demand response in smart grids:Mathematical models and approaches[J].IEEETransactions on Industrial Informatics,2015,11(3):570-582.
[19]Lu N.An evaluation of the HVAC load potential for providing load balancing service[J].IEEE Transactions on Smart Grid,2012,3(3):1263-1270.
[20]Wang Z,Paranjape R.Optimal residential demand response for multiple heterogeneous homes with real-time price prediction in a multiagent framework[J].IEEE Transactions on Smart Grid,2017,8(3):1173-1184.
[21]纪姝彦.面向智能用电的家庭能量管理研究[D].合肥:合肥工业大学,2017.
[22]胡建军,胡飞雄.节能发电调度模式下有偿调峰补偿新机制[J].电力系统自动化,2009,33(10):16-18.Hu Jianjun,Hu Feixiong.A novel compensation mechanism of remunerative peak load regulation under energy-saving dispatch framework[J].Automation of Electric Power Systems,2009,33(10):16-18(in Chinese).
[23]曾雪婷,刘天琪,李茜,等.基于虚拟电源配置策略的风光水火多源互补短期优化调度[J].电网技术,2016,40(5):1379-1386.Zeng Xueting,Liu Tianqi,Li Qian,et al.Short-term complementary optimal dispatch model of multi-source hybrid power system based on virtual power configuration strategy[J].Power System Technology,2016,40(5):1379-1386(in Chinese).
[24]罗洪飞.基于非合作博弈及多目标优化的居民用户智能用电策略研究[D].重庆:重庆大学,2016.
[25]梅坚,杨立兵,李晓刚,等.调峰市场效用分析与低谷调峰市场设计[J].电力系统自动化,2013,37(21):134-138.Mei Jian,Yang Libin,Li Xiaogang,et al.Utility analysis for peak regulation market and trading market design for peak regulation capacity in valley time[J].Automation of Electric Power Systems,2013,37(21):134-138(in Chinese).