基于双层MPC的多源孤岛微网经济运行控制策略
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摘要
含有柴油发电机、光伏发电单元和储能单元的孤岛微网为偏远地区的能源供给提供了有效的解决途径,但是由于光伏出力与负荷需求的双重不确定性,目前尚缺乏行之有效的能量控制策略以同时保证孤岛微网的供电可靠性与经济性。如何在不间断供电的基础上,实现多源孤岛微网的经济运行已是电网公司亟待解决的新问题。为此,提出了一种基于双层模型预测控制(Model Predictive Control, MPC)的多源孤岛微网经济运行控制策略,以实现运行成本最小化,同时减小负荷和光伏功率波动带来的不利影响。通过仿真分析中国西北某村的经济运行成本验证了所提控制策略的有效性。
The island microgrids containing diesel generators, photovoltaic cells and energy storage units provide an effective solution to the energy supply in remote areas. However, due to the double uncertainty of renewable energy output and island microgrid load, there is still a lack of effective energy control strategies to ensure the reliability and economy of power supply of isolated island microgrids. Based on uninterrupted power supply, how to realize the economic operation of multi-source island microgrids is a new problem that the grid company needs to solve urgently. In this paper, a multi-source island micro-network economic operation control strategy based on the Model Predictive Control(MPC) is proposed to minimize the cost operation and reduce the adverse influence of load and the fluctuation of PV power fluctuation. The effectiveness of the control strategy is verified by analyzing the economic operation cost of a village in northwest China.
The island microgrids containing diesel generators, photovoltaic cells and energy storage units provide an effective solution to the energy supply in remote areas. However, due to the double uncertainty of renewable energy output and island microgrid load, there is still a lack of effective energy control strategies to ensure the reliability and economy of power supply of isolated island microgrids. Based on uninterrupted power supply, how to realize the economic operation of multi-source island microgrids is a new problem that the grid company needs to solve urgently. In this paper, a multi-source island micro-network economic operation control strategy based on the Model Predictive Control(MPC) is proposed to minimize the cost operation and reduce the adverse influence of load and the fluctuation of PV power fluctuation. The effectiveness of the control strategy is verified by analyzing the economic operation cost of a village in northwest China.
引文
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[3]ZHANG L,GARI N,HMURCIK L V.Energy management in a microgrid with distributed energy resources[J].Energy Conversion Management,2014,78:297-305.
[4]屈克庆,李文旗,赵晋斌,等.孤岛微网不平衡负荷下控制策略[J].电力系统保护与控制,2017,45(11):8-14.QU Keqing,LI Wenqi,ZHAO Jinbin,et al.Islanded microgrid control strategy under unbalanced loads[J].Power System Protection and Control,2017,45(11):8-14.
[5]王先齐,吕智林,汤泽琦.基于分时电价机制的并网型微网多目标动态优化调度[J].电力系统保护与控制,2017,45(4):9-18.WANG Xianqi,LüZhilin,TANG Zeqi.Multi-objective dynamic dispatching of grid-connected microgrid based on TOU power price mechanism[J].Power System Protection and Control,2017,45(4):9-18.
[6]祖其武,牛玉刚,陈蓓.基于改进粒子群算法的微网多目标经济运行策略研究[J].电力系统保护与控制,2017,45(17):57-63.ZU Qiwu,NIU Yugang,CHEN Bei.Study on multi objective economic operating strategy of microgrid based on improved particle swarm optimization algorithm[J].Power System Protection and Control,2017,45(17):57-63.
[7]DHARMAPANDIT O,PATNAIK R K,DASH P K.Afast time-frequency response based differential spectral energy protection of AC microgrids including fault location[J].Protection and Control of Modern Power Systems,2017,2(2):331-358.DOI:10.1186/s41601-017-0062-0.
[8]MALYSZ P,SIROUSPOUR S,EMADI A.An optimal energy storage control strategy for grid-connected microgrids[J].IEEE Transactions on Smart Grid,2014,5(4):1785-1796.
[9]BRUNO S,DASSISTI M,LA SCALA M,et al.Predictive dispatch across time of hybrid isolated power systems[J].IEEE Transactions on Sustainable Energy,2014,5(3):738-746.
[10]PARISIO A,RIKOS E,TZAMALIS G,et al.Use of model predictive control for experimental microgrid optimization[J].Applied Energy,2014,115:37-46.
[11]田慧雯,李咸善,陈铁,等.基于混合储能的光伏微网孤网运行的综合控制策略[J].电力系统保护与控制,2014,42(19):122-128.TIAN Huiwen,LI Xianshan,CHEN Tie,et al.Comprehensive control strategy of hybrid energy storagebased photovoltaic island microgrid[J].Power System Protection and Control,2014,42(19):122-128.
[12]李武华,徐驰,禹红斌,等.直流微网系统中混合储能分频协调控制策略[J].电工技术学报,2016,31(14):84-92.LI Wuhua,XU Chi,YU Hongbin,et al.Frequency dividing coordinated control strategy for hybrid energy storage system of DC micro-grid[J].Transactions of China Electrotechnical Society,2016,31(14):84-92.
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[15]SHEPHERD C M.Design of primary and secondary cells II:an equation describing battery discharge[J].Journal of the Electrochemical Society,1965,112(7).
[16]SU W,WANG J,ROH J.Stochastic energy scheduling in microgrids with intermittent renewable energy resources[J].IEEE Transactions on Smart Grid,2014,5(4):1876-1883.
[17]REHMAN S,AL-HADHRAMI L M.Study of a solar PV-diesel-battery hybrid power system for a remotely located population near Rafha,Saudi Arabia[J].Energy,2010,35(12):4986-4995.
[18]LEE C M,KO C N.Short-term load forecasting using lifting scheme and Arima models[J].Expert System Application,2011,38(5):5902-5911.
[19]PAOLETTI S,GARULLI A,VICINO A.Electric load forecasting in the presence of active demand[C]//2012IEEE 51st IEEE Conference on Decision and Control(CDC),December 10-13,2012,Maui,HI,USA:2395-2400.
[20]LAMBERT T,GILMAN P,LILIENTHAL P.Micropower system modeling with homer[M]//Integration of Alternative Sources of Energy,Wiley-IEEE Press,2006,1:381-385.