基于需求侧响应的家庭电热水器优化调度
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摘要
电热水器是家庭中极为重要的负荷,对实时电价机制下家庭电热水器的优化调度问题进行分析是非常有意义的。首先,将电热水器热力学模型归纳为一阶显式方程,并以此为基础,利用线性整数规划对电热水器的优化调度问题进行求解。然后,对不同程度的舒适区间无选择性调整方案的经济性进行了讨论。最后,探讨了基于多维度信息的综合权重排序法在有选择性舒适区间调整方案中的应用,并对两者进行了比较。仿真结果表明,调整舒适区间上下限能够明显降低调度计划的用电费用。而且,基于多维度信息的综合权重排序法能够有效选择舒适区间调整节点,在很短的调整时长内获得较好的经济效益。
Household Electric Water Heater(HEWH) is one of the most important services in a home. It is significant to study the household electric water heater load scheduling based on demand response in real time pricing tariffs. At first, a type of first-order explicit equation is utilized to describe the thermal dynamic modes of the HEWH. Under such a background, the HEWH load scheduling is addressed using linear integer programming. Then, the energy costs of different indistinctive adjusting schemes of comfort zone are discussed. For comparison's sake, the selective adjusting schemes with synthetic weight ranking method based on multi-dimensional information are also analyzed. Simulation results indicate that adjusting the upper and lower bounds of comfort zone is useful to reduce the energy cost. Moreover, the proposed synthetic weight ranking method based on multi-dimensional information is able to obtain well economic benefit through adjusting just a small part of comfort zone.
Household Electric Water Heater(HEWH) is one of the most important services in a home. It is significant to study the household electric water heater load scheduling based on demand response in real time pricing tariffs. At first, a type of first-order explicit equation is utilized to describe the thermal dynamic modes of the HEWH. Under such a background, the HEWH load scheduling is addressed using linear integer programming. Then, the energy costs of different indistinctive adjusting schemes of comfort zone are discussed. For comparison's sake, the selective adjusting schemes with synthetic weight ranking method based on multi-dimensional information are also analyzed. Simulation results indicate that adjusting the upper and lower bounds of comfort zone is useful to reduce the energy cost. Moreover, the proposed synthetic weight ranking method based on multi-dimensional information is able to obtain well economic benefit through adjusting just a small part of comfort zone.
引文
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[3]YIN Xianggen,ZHANG Zhe,LI Zhenxing,et al.The research and the development of the wide area relaying protection based on fault element identification[J].Protection and Control of Modern Power Systems,2016,1(1):95-107.DOI:10.1186/s41601-016-0023-z.
[4]WANG J,LI Y,ZHOU Y.Interval number optimization for household load scheduling with uncertainty[J].Energy Build,2016,130:613-624.
[5]郝文斌,李银奇.不同电价机制下含光伏发电的家庭负荷调度经济性研究[J].电力系统保护与控制,2017,45(17):34-42.HAO Wenbin,LI Yinqi.Economic study of household load scheduling of a smart home with photovoltaic system under different pricing mechanisms[J].Power System Protection and Control,2017,45(17):34-42.
[6]佟晶晶,温俊强,王丹,等.基于分时电价的电动汽车多目标优化充电策略[J].电力系统保护与控制,2016,44(1):17-23.TONG Jingjing,WEN Junqiang,WANG Dan,et al.Multi-objective optimization charging strategy for plug-in electric vehicles based on time-of-use price[J].Power System Protection and Control,2016,44(1):17-23.
[7]PEDRASA M A,SPOONER T D,MACGILL I F.The value of accurate forecasts and a probabilistic method for robust scheduling of residential distributed energy resources[C]//2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems,June 14-17,2010,Singapore,Singapore:587-592.
[8]WANG C,ZHOU Y,WU J,et al.Robust-index method for household load scheduling considering uncertainties of customer behavior[J].IEEE Transactions on Smart Grid,2015,6(4):1806-1818.
[9]WANG C,ZHOU Y,JIAO B,et al.Robust optimization for load scheduling of a smart home with photovoltaic system[J].Energy Conversion and Management,2015,102:247-257.
[10]ARABALI A,GHOFRANI M,ETEZADI-AMOLI M,et al.Genetic-algorithm-based optimization approach for energy management[J].IEEE Transactions on Power Delivery,2013,28(1):162-170.
[11]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[J].电网技术,2014,38(7):1819-1826.ZHANG Yanyu,ZENG Peng,LI Zhongwen,et al.Amulti-objective optimal control algorithm for air conditioning system in smart grid[J].Power System Technology,2014,38(7):1819-1826.
[12]DU P,LU N.Appliance commitment for household load scheduling[J].IEEE Transactions on Smart Grid,2011,2(2):411-419.
[13]WANG C,ZHOU Y,WANG J,et al.A novel traversaland-pruning algorithm for household load scheduling[J].Applied Energy,2013,102:1430-1438.
[14]IWAFUNE Y,YAGITA Y.High-resolution determinant analysis of Japanese residential electricity consumption using home energy management system data[J].Energy and Buildings,2016,116:274-284.
[15]PRATT R G,TAYLOR Z T.Development and testing of an equivalent thermal parameter model of commercial buildings from time-series end-use data[M].Richland,WA,USA:Pac.Northwest Lab,1994.
[16]TAYLOR Z T,PRATT R G.The effects of model simplifications on equivalent thermal parameters calculated from hourly building performance data[C]//Proc ACEEE Sum Study Energy Efficiency Build,1988,10:268-285.
[17]CALLAWAY D S.Tapping the energy storage potential in electric loads to deliver load following and regulation,with application to wind energy[J].Energy Conversion Management,2009,50(9):1389-1400.
[18]HONG Y Y,LIN J K,WU C P,et al.Multi-objective air-conditioning control considering fuzzy parameters using immune clonal selection programming[J].IEEETransactions on Smart Grid,2012,3(4):1603-1610.
[19]AGNETIS A,DE PASCALE G,DETTI P,et al.Load scheduling for household energy consumption optimization[J].IEEE Transactions on Smart Grid,2013,4(4):2364-2373.
[20]2012 ASHRAE Handbook-HVAC Systems and Equipment.Amer.Soc.Heating,Refrigerating and Air-Conditioning Eng.,Inc.,2012[EB/OL].https://app.knovel.com/web/search.v?q=2012%20ASHRAE%20Han dbook&my_subscription=FALSE&search_type=tech-ref erence.