基于改进状态空间模型的空调负荷控制策略
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摘要
空调负荷因其可中断特性可以实现系统控制信号的快速响应与调节。提出了一种基于改进状态空间模型的空调负荷控制策略。首先扩展状态空间长度,建立了更为精确的改进状态空间模型,实现无控条件下空调负荷聚合特性的跟踪。在此基础上,建立了空调聚合控制模型,实现温控信号下空调负荷动态聚合特性的跟踪。最后,对空调群进行温度优化控制,实现空调群的负荷调节。仿真结果验证了空调负荷的改进状态空间模型、聚合控制模型和温度优化控制策略的有效性。
Air conditioning load, as an important interruptible load, can respond to system control signals quickly. An aggregated control strategy of air conditioning load based on improved state-space model is proposed. By extending the state-space length, the improved state-space model with high-accuracy is established to track the aggregated characteristics of uncontrolled air conditioning load. Then, an aggregated control model that takes into account temperature control signals is proposed to track the dynamic collective behavior of the air conditioning load. Finally, an optimal temperature control strategy is proposed to implement the power adjustment of air conditioning load. Simulation results are demonstrated to verify the improved state space model, the aggregated control model and the optimal temperature control strategy.
Air conditioning load, as an important interruptible load, can respond to system control signals quickly. An aggregated control strategy of air conditioning load based on improved state-space model is proposed. By extending the state-space length, the improved state-space model with high-accuracy is established to track the aggregated characteristics of uncontrolled air conditioning load. Then, an aggregated control model that takes into account temperature control signals is proposed to track the dynamic collective behavior of the air conditioning load. Finally, an optimal temperature control strategy is proposed to implement the power adjustment of air conditioning load. Simulation results are demonstrated to verify the improved state space model, the aggregated control model and the optimal temperature control strategy.
引文
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[4] SALEH S A, PIJNENBURG P, CASTILLO G E. Load aggregation from generation-follows-load to load-follows-generation residential loads[J]. IEEE Transactions on Industry Applications, 2017, 53(2): 833-842.
[5] 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.
[6] LU N, ZHANG Y. Design considerations of a centralized load controller using thermostatically controlled appliances for continuous regulation reserves[J]. IEEE Transactions on Smart Grid, 2013, 4(2): 914-921.
[7] 宋梦,高赐威,苏卫华.面向需求响应应用的空调负荷建模及控制[J].电力系统自动化,2016,40(14):158-167.SONG Meng, GAO Ciwei, SU Weihua. Modeling and controlling of air-conditioning load for demand response applications[J]. Automation of Electric Power Systems, 2016, 40(14): 158-167.
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[16] BASHASH S, FATHY H K. Modeling and control of aggregate air conditioning loads for robust renewable power management[J]. IEEE Transactions on Control Systems Technology, 2013, 21(4): 1318-1327.
[17] SONG Meng, GAO Ciwei, YANG Jianlin, et al. Novel aggregate control model of air conditioning loads for fast regulation service[J]. IET Generation, Transmission & Distribution, 2017, 11(17): 4391-4401.
[18] 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.DOI:10.7500/AEPS20170614023.TANG Zao, LIU Junyong, LIU Youbo, et al. Load control and distribution network reconfiguration with participation of air-conditioning load aggregator[J]. Automation of Electric Power Systems, 2018, 42(2): 42-49. DOI: 10.7500/AEPS20170614023.
[19] 孙宇军,王岩,王蓓蓓,等.考虑需求响应不确定性的多时间尺度源荷互动决策方法[J].电力系统自动化,2018,42(2):106-114.DOI:10.7500/AEPS20170416004.SUN Yujun, WANG Yan, WANG Beibei, et al. Multi-time scale decision method for source-load interaction considering demand response uncertainty[J]. Automation of Electric Power Systems, 2018,42(2):106-114. DOI: 10.7500/AEPS20170416004.
[20] 孙成龙.考虑需求响应不确定性的系统备用优化调度研究[D].南京:东南大学,2015:28-35.SUN Chenglong. Research on optimal scheduling considering demand-side participating as reserves with response uncertainties[D]. Nanjing: Southeast University, 2015: 28-35.
[21] 徐青山,吴枭,杨斌.考虑状态差异性聚类的空调负荷直接负荷控制动态优化方法[J].电力系统自动化,2016,40(14):33-41.XU Qingshan, WU Xiao, YANG Bin. Dynamic optimization method of direct load control for air-conditioning load considering status diversity clustering[J]. Automation of Electric Power Systems, 2016, 40(14): 33-41.
[2] HUI H, DING Y, LIU W, et al. Operating reserve evaluation of aggregated air conditioners[J]. Applied Energy, 2017, 196: 218-228.
[3] ZHANG Wei, LIAN Jianming, CHANG C Y, et al. Aggregated modeling and control of air conditioning loads for demand response[J]. IEEE Transactions on Power Systems, 2013, 28(4): 4655-4664.
[4] SALEH S A, PIJNENBURG P, CASTILLO G E. Load aggregation from generation-follows-load to load-follows-generation residential loads[J]. IEEE Transactions on Industry Applications, 2017, 53(2): 833-842.
[5] 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.
[6] LU N, ZHANG Y. Design considerations of a centralized load controller using thermostatically controlled appliances for continuous regulation reserves[J]. IEEE Transactions on Smart Grid, 2013, 4(2): 914-921.
[7] 宋梦,高赐威,苏卫华.面向需求响应应用的空调负荷建模及控制[J].电力系统自动化,2016,40(14):158-167.SONG Meng, GAO Ciwei, SU Weihua. Modeling and controlling of air-conditioning load for demand response applications[J]. Automation of Electric Power Systems, 2016, 40(14): 158-167.
[8] 辛洁晴,吴亮.商务楼中央空调周期性暂停分档控制策略[J].电力系统自动化,2013,37(5):49-54.XIN Jieqing, WU Liang. Hierarchical strategies for duty cycling control of air conditioners in business buildings[J]. Automation of Electric Power Systems, 2013, 37(5): 49-54.
[9] LU N, CHASSIN D P. A state-queueing model of thermostatically controlled appliances[J]. IEEE Transactions on Power Systems, 2004, 19(3): 1666-1673.
[10] LU N, CHASSIN D P, WIDERGREN S E. Modelling uncertainties in aggregated thermostatically controlled loads using a state queuing model[J]. IEEE Transactions on Power Systems, 2005, 20(2): 725-733.
[11] SANANDAJI B M, VINCENT T L, POOLLA K. Ramping rate flexibility of residential HVAC loads[J]. IEEE Transactions on Sustainable Energy, 2016, 7(2): 865-874.
[12] TROVATO V, TINDEMANS S H, STRBAC G. Leaky storage model for optimal multi-service allocation of thermostatic loads[J]. IET Generation, Transmission & Distribution, 2016, 10(3): 585-593.
[13] MATHIEU J L, KAMGARPOUR M, LYGEROS J, et al. Arbitraging intraday wholesale energy market prices with aggregations of thermostatic loads[J]. IEEE Transactions on Power Systems, 2015, 30(2): 763-772.
[14] LIU M, SHI Y. Model predictive control of aggregated heterogeneous second-order thermostatically controlled loads for ancillary services[J]. IEEE Transactions on Power Systems, 2016, 31(3): 1963-1971.
[15] SANANDAJI B M, HAO H, POOLLA K. Fast regulation service provision via aggregation of thermostatically controlled loads[C]// Proceedings of the 47th Hawaii International Conference on System Science, January 1-6, 2014, Waikoloa, USA: 2388-2397.
[16] BASHASH S, FATHY H K. Modeling and control of aggregate air conditioning loads for robust renewable power management[J]. IEEE Transactions on Control Systems Technology, 2013, 21(4): 1318-1327.
[17] SONG Meng, GAO Ciwei, YANG Jianlin, et al. Novel aggregate control model of air conditioning loads for fast regulation service[J]. IET Generation, Transmission & Distribution, 2017, 11(17): 4391-4401.
[18] 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.DOI:10.7500/AEPS20170614023.TANG Zao, LIU Junyong, LIU Youbo, et al. Load control and distribution network reconfiguration with participation of air-conditioning load aggregator[J]. Automation of Electric Power Systems, 2018, 42(2): 42-49. DOI: 10.7500/AEPS20170614023.
[19] 孙宇军,王岩,王蓓蓓,等.考虑需求响应不确定性的多时间尺度源荷互动决策方法[J].电力系统自动化,2018,42(2):106-114.DOI:10.7500/AEPS20170416004.SUN Yujun, WANG Yan, WANG Beibei, et al. Multi-time scale decision method for source-load interaction considering demand response uncertainty[J]. Automation of Electric Power Systems, 2018,42(2):106-114. DOI: 10.7500/AEPS20170416004.
[20] 孙成龙.考虑需求响应不确定性的系统备用优化调度研究[D].南京:东南大学,2015:28-35.SUN Chenglong. Research on optimal scheduling considering demand-side participating as reserves with response uncertainties[D]. Nanjing: Southeast University, 2015: 28-35.
[21] 徐青山,吴枭,杨斌.考虑状态差异性聚类的空调负荷直接负荷控制动态优化方法[J].电力系统自动化,2016,40(14):33-41.XU Qingshan, WU Xiao, YANG Bin. Dynamic optimization method of direct load control for air-conditioning load considering status diversity clustering[J]. Automation of Electric Power Systems, 2016, 40(14): 33-41.