含分布式电源和储能装置的配电网分散式动态最优潮流
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摘要
随着大量分布式能源接入配电网,配电网的可调度性大大增强,逐渐呈现多主体特性。因此在对分布式能源进行优化调度的同时,还应保护不同主体间的隐私,这对传统的优化调度方式带来了很大的挑战。首先建立了含分布式电源和储能装置的配电网动态最优潮流模型,并借助正负旋转备用应对光伏出力的不确定性。通过对交流潮流方程进行线性近似,同时验证了在一定条件下描述储能装置运行状态的互补约束可自动满足,从而将原始的非线性规划模型转化为二次规划模型。然后将配电网、分布式电源和储能装置分别作为独立主体,将动态最优潮流模型转化为分散式优化模型。再采用辅助问题原理法求解,将分散式动态最优潮流模型的求解分解为各个独立主体的二次规划子模型的求解,既保护各个利益主体间的隐私,又能通过在各主体之间交换边界变量信息,实现各个独立主体之间的协调优化,从而实现全局最优。最后,通过对IEEE 33节点和一个实际265节点配电网进行测试,验证文中所提方法的正确性和有效性。
With a large number of distributed generators integrated to distribution network, the distribution network is greatly enhanced in dispatchability and gradually presents multi-agent characteristics. Therefore, while performing optimal dispatch of distributed generators, the privacy between different agents should be protected as well, thus bringing a great challenge to traditional optimal dispatch mode. In this paper, firstly, a dynamic optimal power flow(DOPF) model of distribution network with distributed generators and energy storage devices is established with positive and negative spinning reserve used to deal with uncertainty of photovoltaic outputs. By linearly approximating the AC power flow equation in the model, and proving that the complementary constraints on outputs of energy storage devices can be automatically satisfied under certain conditions, the original nonlinear programming model is transformed into a quadratic programming problem. Next, treating the distribution network, distributed power and energy storage devices as independent agents,the DOPF model is transformed into a decentralized optimization model.Then, the auxiliary problem principle is used to solve this model by decomposing the distributed DOPF model into several independent sub-models. They are all quadratic problems and belong to different agents. This method can protect the privacy among different agents and exchange boundary information between them. It also realizes coordination and optimization among the independent agents so as to achieve global optimum. Finally, IEEE 33-bus and anactual 265-bus distribution system are used to verify correctness and effectiveness of the proposed method.
With a large number of distributed generators integrated to distribution network, the distribution network is greatly enhanced in dispatchability and gradually presents multi-agent characteristics. Therefore, while performing optimal dispatch of distributed generators, the privacy between different agents should be protected as well, thus bringing a great challenge to traditional optimal dispatch mode. In this paper, firstly, a dynamic optimal power flow(DOPF) model of distribution network with distributed generators and energy storage devices is established with positive and negative spinning reserve used to deal with uncertainty of photovoltaic outputs. By linearly approximating the AC power flow equation in the model, and proving that the complementary constraints on outputs of energy storage devices can be automatically satisfied under certain conditions, the original nonlinear programming model is transformed into a quadratic programming problem. Next, treating the distribution network, distributed power and energy storage devices as independent agents,the DOPF model is transformed into a decentralized optimization model.Then, the auxiliary problem principle is used to solve this model by decomposing the distributed DOPF model into several independent sub-models. They are all quadratic problems and belong to different agents. This method can protect the privacy among different agents and exchange boundary information between them. It also realizes coordination and optimization among the independent agents so as to achieve global optimum. Finally, IEEE 33-bus and anactual 265-bus distribution system are used to verify correctness and effectiveness of the proposed method.
引文
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[13]Zheng W Y,Wu W C,Zhang B M,et al.Fully distributed multi-area economic dispatch method for active distribution networks[J].IETGeneration Transmission&Distribution,2015,9(12):1341-1351.
[14]Dall'Anese E,Zhu H,Giannakis G B.Distributed optimal power flow for smart microgrids[J].IEEE Transactions on Smart Grid,2013,4(3):1464-1475.
[15]韩禹歆,陈来军,王召健,等.基于自适应步长ADMM的直流配电网分布式最优潮流[J].电工技术学报,2017,32(11):26-37.Han Yuxin,Chen Laijun,Wang Zhaojian,et al.Distributed optimal power flow in direct current distribution network based on alternative direction method of multipliers with dynamic step size[J].Transactions of China Electrotechnical Society,2017,32(11):26-37(in Chinese).
[16]蒲天骄,刘威,陈乃仕,等.基于一致性算法的主动配电网分布式优化调度[J].中国电机工程学报,2017,37(6):1579-1589.Pu Tianjiao,Liu Wei,Chen Naishi,et al.Distributed optimal dispatching of active distribution network based on consensus algorithm[J].Proceedings of the CSEE,2017,37(6):1579-1589(in Chinese).
[17]Ahmadi-Khatir A,Conejo A J,Cherkaoui R.Multi-area unit scheduling and reserve allocation under wind power uncertainty[J].IEEE Transactions on Power Systems,2014,29(4):1701-1710.
[18]Guggilam S S,Dall’Anese E,Chen Y C,et al.Scalable optimization methods for distribution networks with high PV integration[J].IEEETransactions on Smart Grid,2016,7(4):2061-2070.
[19]Bolognani S,Zampieri S.On the existence and linear approximation of the power flow solution in power distribution networks[J].IEEETransactions on Power Systems,2016,31(1):163-172.
[20]Dall’Anese E,Kyri Baker,Tyler Summers.Chance-constrained ACoptimal power flow for distribution systems with renewables[J].IEEETransactions on Power Systems,2017,32(5):3427-3438.
[21]Yang P,Nehorai A.Joint optimization of hybrid energy storage and generation capacity with renewable energy[J].IEEE Transactions on Smart Grid,2014,5(4):1566-1574.
[2]尤毅,刘东,钟清,等.多时间尺度下基于主动配电网的分布式电源协调控制[J].电力系统自动化,2014,38(9):192-198,203.You Yi,Liu Dong,Zhong Qing,et al.Multi-time scale coordinated control of distributed generators based on active distribution network[J].Automation of Electric Power Systems,2014,38(9):192-198,203(in Chinese).
[3]蒲天骄,陈乃仕,王晓辉,等.主动配电网多源协同优化调度架构分析及应用设计[J].电力系统自动化,2016,40(1):17-23.Pu Tianjiao,Chen Naishi,Wang Xiaohui,et al.Application and architecture of multi-source coordinated optimal dispatch for active distribution network[J].Automation of Electric Power Systems,2016,40(1):17-23(in Chinese).
[4]王甜婧,许阔,朱永强.主动配电网的源-网-荷多层博弈经济调度策略[J].电力系统保护与控制,2018,46(4):10-19.Wang Tianjing,Xu Kuo,Zhu Yongqiang.Economic dispatch strategy of active distribution network based on source-network-load multilayer game[J].Power System Protection and Control,2018,46(4):10-19(in Chinese).
[5]刘一兵,吴文传,张伯明,等.基于混合整数二阶锥规划的主动配电网有功-无功协调多时段优化运行[J].中国电机工程学报,2014,34(16):2575-2583.Liu Yibing,Wu Wenchuan,Zhang Boming,et al.A mixed integer second-order cone programming based active and reactive power coordinated multi-period optimization for active distribution network[J].Proceedings of the CSEE,2014,34(16):2575-2583(in Chinese).
[6]刘斌,刘锋,梅生伟,等.基于二阶锥优化的含有载调压变压器主动配电网最优潮流[J].电力系统自动化,2015,39(19):40-47.Liu Bin,Liu Feng,Mei Shengwei,et al.Optimal power flow in active distribution networks with on-load tap changer based on second-order cone programming[J].Automation of Electric Power Systems,2015,39(19):40-47(in Chinese).
[7]高红均,刘俊勇,沈晓东,等.主动配电网最优潮流研究及其应用实例[J].中国电机工程学报,2017,37(6):1634-1644.Gao Hongjun,Liu Junyong,Shen Xiaodong,et al.Optimal power flow research in active distribution network and its application examples[J].Proceedings of the CSEE,2017,37(6):1634-1644(in Chinese).
[8]Gan Lingwen,Li Na,Topcu U,et al.Exact convex relaxation of optimal power flow in radial networks[J].IEEE Transactions on Automatic Control,2015,60(1):72-87.
[9]常垚,程林,李洪涛,等.基于半正定松弛最优潮流的主动配电网多源协调优化控制[J].电网技术,2016,40(8):2416-2422.Chang Yao,Cheng Lin,Li Hongtao,et al.Distribution system optimal power flow with various controllable sources based on semi-definite relaxation[J].Power System Technology,2016,40(8):2416-2422(in Chinese).
[10]Xie M,Ji X,Ke S,Liu M.Autonomous optimized economic dispatch of active distribution system with multi-microgrids[J].Energy,2018(153):479-489.
[11]齐琛,汪可友,李国杰,等.交直流混合主动配电网的分层分布式优化调度[J].中国电机工程学报,2017,37(7):1909-1917.Qi Chen,Wangle Keyou,Li Guojie,et al.Hierarchical and distributed optimal scheduling of AC/DC hybrid active distribution network[J].Proceedings of the CSEE,2017,37(7):1909-1917(in Chinese).
[12]欧阳聪,刘明波,林舜江,等.采用同步型交替方向乘子法的微电网分散式动态经济调度算法[J].电工技术学报,2017,32(5):134-142.Ou Yangcong,Liu Mingbo,Lin Shunjiang,et al.Decentralized dynamic economic dispatch algorithm of microgrids using synchronous alternating direction method of multipliers[J].Transactions of China Electrotechnical Society,2017,32(5):134-142(in Chinese).
[13]Zheng W Y,Wu W C,Zhang B M,et al.Fully distributed multi-area economic dispatch method for active distribution networks[J].IETGeneration Transmission&Distribution,2015,9(12):1341-1351.
[14]Dall'Anese E,Zhu H,Giannakis G B.Distributed optimal power flow for smart microgrids[J].IEEE Transactions on Smart Grid,2013,4(3):1464-1475.
[15]韩禹歆,陈来军,王召健,等.基于自适应步长ADMM的直流配电网分布式最优潮流[J].电工技术学报,2017,32(11):26-37.Han Yuxin,Chen Laijun,Wang Zhaojian,et al.Distributed optimal power flow in direct current distribution network based on alternative direction method of multipliers with dynamic step size[J].Transactions of China Electrotechnical Society,2017,32(11):26-37(in Chinese).
[16]蒲天骄,刘威,陈乃仕,等.基于一致性算法的主动配电网分布式优化调度[J].中国电机工程学报,2017,37(6):1579-1589.Pu Tianjiao,Liu Wei,Chen Naishi,et al.Distributed optimal dispatching of active distribution network based on consensus algorithm[J].Proceedings of the CSEE,2017,37(6):1579-1589(in Chinese).
[17]Ahmadi-Khatir A,Conejo A J,Cherkaoui R.Multi-area unit scheduling and reserve allocation under wind power uncertainty[J].IEEE Transactions on Power Systems,2014,29(4):1701-1710.
[18]Guggilam S S,Dall’Anese E,Chen Y C,et al.Scalable optimization methods for distribution networks with high PV integration[J].IEEETransactions on Smart Grid,2016,7(4):2061-2070.
[19]Bolognani S,Zampieri S.On the existence and linear approximation of the power flow solution in power distribution networks[J].IEEETransactions on Power Systems,2016,31(1):163-172.
[20]Dall’Anese E,Kyri Baker,Tyler Summers.Chance-constrained ACoptimal power flow for distribution systems with renewables[J].IEEETransactions on Power Systems,2017,32(5):3427-3438.
[21]Yang P,Nehorai A.Joint optimization of hybrid energy storage and generation capacity with renewable energy[J].IEEE Transactions on Smart Grid,2014,5(4):1566-1574.