Distributed optimization of energy storage units in non-ideal communication network
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- 英文论文题名：Distributed optimization of energy storage units in non-ideal communication network
- 论文作者：Shang Ding ; Xifeng Zhou ; Qiangang Guo
- 英文论文作者：Shang Ding ; Xifeng Zhou ; Qiangang Guo ; institute of automation ; Nanjing university of posts and telecommunications ; Tong Da institute ; Nanjing university of posts and telecommunications
- 年：2017
- 作者机构：institute of automation,Nanjing university of posts and telecommunications;Tong Da institute,Nanjing university of posts and telecommunications;
- 英文论文关键词：energy storage unit ; distributed gradient algorithm ; time-varying topology ; suppress channel noise
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TM73
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：5
- 文件大小：322k
- 原文格式：D
- 会议级别：全国
摘要
Energy storage systems(ESSs) usually are used to keep active power and frequency stable in the microgrid, especially in the autonomous microgrid. Some factors often happen just like time-varying topology and channel noise in actual communication network. This paper uses multi-agent system and every agent represents an energy storage unit. This paper chooses the battery energy storage system(BESS). Distributed gradient algorithm is used to control the active powers of ESSs. In this paper, simulation is carried out in non-ideal communication network and simulation results before and after suppressing noise are compared. The simulation results show that distributed gradient algorithm can suppress the noise obviously.
Energy storage systems(ESSs) usually are used to keep active power and frequency stable in the microgrid, especially in the autonomous microgrid. Some factors often happen just like time-varying topology and channel noise in actual communication network. This paper uses multi-agent system and every agent represents an energy storage unit. This paper chooses the battery energy storage system(BESS). Distributed gradient algorithm is used to control the active powers of ESSs. In this paper, simulation is carried out in non-ideal communication network and simulation results before and after suppressing noise are compared. The simulation results show that distributed gradient algorithm can suppress the noise obviously.
Energy storage systems(ESSs) usually are used to keep active power and frequency stable in the microgrid, especially in the autonomous microgrid. Some factors often happen just like time-varying topology and channel noise in actual communication network. This paper uses multi-agent system and every agent represents an energy storage unit. This paper chooses the battery energy storage system(BESS). Distributed gradient algorithm is used to control the active powers of ESSs. In this paper, simulation is carried out in non-ideal communication network and simulation results before and after suppressing noise are compared. The simulation results show that distributed gradient algorithm can suppress the noise obviously.
引文
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[3]A.G.A.Khalil and D.C.Lee,MPPT control of wind generation systems based on estimated wind speed using SVR,IEEETransactions Industrial Electronics,55(3),1489-1490,2008.
[4]L.Zhang,W.G.Hurleyand W.H.Wolfe,A new approach to achieve maximum power point tracking for PV system with a variable inductor,IEEE Transaction on Power Electronics,26(4):1031-1037,2011.
[5]Yun Cong Jiang,Jable A.Abu Qahouq and Tim A,Haskew,Adaptive step size with adaptive-perturbation-frequency digital MPPT controller for a single-sensor photovoltaic solar system,IEEE Transaction on Power Electronics,28(7):3195-3205,2013.
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[7]Gangui Yan,Xiaodong Feng,Junhui Li,et al.,Optimization of Energy Storage System Capacity for Relaxing Peak Load Regulation Bottlenecks,Proceedings of the CSEE,32(28):27-35,2012.
[8]Fan Yu,Wei Zhou,Hui Sun,etal,Hybrid Energy Storage System and Control System Design for Wind Power Balancing,Proceedings of the CSEE,31(17):127-133,2011.
[9]Yang T C,Initial study of using rechargeable batteries in wind power generation with variable speed induction generators,IETRenewable Power Generation,2(2):89-101,2008.
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[13]Wei Zhang,Wenxin Liu,Xin Wang,Online Optimal Generation Control Based on Constrained Distributed Gradient Algorithm,IEEE Transactions on Power System,30(1):35-45,2015.
[14]X.Lu,K.Sun,J.M.Guerrero,J.C.Vasquez,and L.Huang,State-of-charge balance using adaptive droop control for distributed energy storage systems in DC microgrid applications,IEEE Transactions on Industrial Electronics,61(6):2804-2815,2014.
[15]W.H.Zhu,Y.Zhu,and B.J.Tatarchuk,A simplified equivalent circuit model for simulation of Pb Cacid batteries at load for energy storage application,Energy Conversion and Management,52(8C9):2794-2799,2011.
[16]K.M.Tsang,L.Sunand W.L,Chan,Identification and modelling of lithium ion battery,Energy Conversion and Management,52(12):2857-2862,2010.
[17]F.A.Amoroso and G,Cappuccino,Impact of charging efficiency variations on the effectiveness of variable-ratebased charging strategies for electric vehicles,Power Sources,196(22):9574-9578,2011.
[18]F.A.Amoroso and G.Cappuccino,Advantages of efficiencyaware smart charging strategies for PEVs,Energy Conversion and Management,54(1):1-6,2012.
[19]Yinliang Xu,Wei Zhang,G.Hug,Cooperative Control of Distributed Energy Storage Systems in a Microgrid,IEEE Transaction on Smart Grid,6(1):238-248,2015.
[20]L.Xiao and S.Boyd,Optimal scaling of a gradient method for distributed resource allocation,Optimization Theory and Applications,29(3):469-488,2016.
[21]I.Lobel and A.Ozdaglar,Distributed subgradient methods for convex optimization over random networks,IEEE Transaction on Automatic Control,56(6):1291-1306,2011.
[22]A.Nedic and A.Ozdaglar,Distributed subgradient methods for multiagent optimization,IEEE Transaction on Automatic Control,54(1):48-61,2009.
[23]K.Srivastava and A.Nedic,Distributed asynchronous constrained stochastic optimization,IEEE Journal of Selected Topics in Signal Processing,5(4):772-790,2011.
[24]M.Zhu and S.Martinez,On distributed convex optimization under inequality and equality constraints,IEEE Transaction on Automatic Control,57(1):151-164,2012.
[25]R.Olfati-Saber,J.A.Faxand R.M.Murray,Consensus and cooperation in networked multi-agent systems,Proceeding of the IEEE,95(1):215-233,2007.
[26]J.A.Bondy and U.S.R.Murty,Graph Theory With Applications,IEEE Journals and Magazines,63(10):1533-1534,1976.
[27]Hao Xu,Xiaoshun Zhang and Tao Yu,Robust collaborative consistency algorithm of economic dispatch under nonideal communication network conditions,Automation of Electric Power Systems,40(14),2016.
[2]Lassetter R,Akhil A,Marnay,et al.,The CERTS microgrid concept,Electrical Engineering Department University if Wisconsin-Madison Madison,6(3):54-65,2007.
[3]A.G.A.Khalil and D.C.Lee,MPPT control of wind generation systems based on estimated wind speed using SVR,IEEETransactions Industrial Electronics,55(3),1489-1490,2008.
[4]L.Zhang,W.G.Hurleyand W.H.Wolfe,A new approach to achieve maximum power point tracking for PV system with a variable inductor,IEEE Transaction on Power Electronics,26(4):1031-1037,2011.
[5]Yun Cong Jiang,Jable A.Abu Qahouq and Tim A,Haskew,Adaptive step size with adaptive-perturbation-frequency digital MPPT controller for a single-sensor photovoltaic solar system,IEEE Transaction on Power Electronics,28(7):3195-3205,2013.
[6]Jong-Yul Kim,Jin-Hong Jeon,Seal-Ki Kin,et al.,Cooperative control strategy of energy storage system and microsources for stabilizing the microgrid during islanded operation,IEEETransaction on Power Electronics,25(12):3037-3048,2010.
[7]Gangui Yan,Xiaodong Feng,Junhui Li,et al.,Optimization of Energy Storage System Capacity for Relaxing Peak Load Regulation Bottlenecks,Proceedings of the CSEE,32(28):27-35,2012.
[8]Fan Yu,Wei Zhou,Hui Sun,etal,Hybrid Energy Storage System and Control System Design for Wind Power Balancing,Proceedings of the CSEE,31(17):127-133,2011.
[9]Yang T C,Initial study of using rechargeable batteries in wind power generation with variable speed induction generators,IETRenewable Power Generation,2(2):89-101,2008.
[10]R.Mudumbai,S.Dasgupta and B.Cho,Distributed control for optimal economic dispatch of power generators,Control Conference,2008:89-101.
[11]R.Mudumbai,S.Dasgupta and B.Cho,Distributed control for optimal economic dispatch of a network of heterogeneous power generators,Control Conference,2008:89-101.
[12]Z.Zhang,X.Yingand M.Chow,Decentralizing the economic dispatch problem using a two-level incremental cost consensus algorithm in a smart grid environment,in Proc.North American Power Symposium,2012:1750-1760.
[13]Wei Zhang,Wenxin Liu,Xin Wang,Online Optimal Generation Control Based on Constrained Distributed Gradient Algorithm,IEEE Transactions on Power System,30(1):35-45,2015.
[14]X.Lu,K.Sun,J.M.Guerrero,J.C.Vasquez,and L.Huang,State-of-charge balance using adaptive droop control for distributed energy storage systems in DC microgrid applications,IEEE Transactions on Industrial Electronics,61(6):2804-2815,2014.
[15]W.H.Zhu,Y.Zhu,and B.J.Tatarchuk,A simplified equivalent circuit model for simulation of Pb Cacid batteries at load for energy storage application,Energy Conversion and Management,52(8C9):2794-2799,2011.
[16]K.M.Tsang,L.Sunand W.L,Chan,Identification and modelling of lithium ion battery,Energy Conversion and Management,52(12):2857-2862,2010.
[17]F.A.Amoroso and G,Cappuccino,Impact of charging efficiency variations on the effectiveness of variable-ratebased charging strategies for electric vehicles,Power Sources,196(22):9574-9578,2011.
[18]F.A.Amoroso and G.Cappuccino,Advantages of efficiencyaware smart charging strategies for PEVs,Energy Conversion and Management,54(1):1-6,2012.
[19]Yinliang Xu,Wei Zhang,G.Hug,Cooperative Control of Distributed Energy Storage Systems in a Microgrid,IEEE Transaction on Smart Grid,6(1):238-248,2015.
[20]L.Xiao and S.Boyd,Optimal scaling of a gradient method for distributed resource allocation,Optimization Theory and Applications,29(3):469-488,2016.
[21]I.Lobel and A.Ozdaglar,Distributed subgradient methods for convex optimization over random networks,IEEE Transaction on Automatic Control,56(6):1291-1306,2011.
[22]A.Nedic and A.Ozdaglar,Distributed subgradient methods for multiagent optimization,IEEE Transaction on Automatic Control,54(1):48-61,2009.
[23]K.Srivastava and A.Nedic,Distributed asynchronous constrained stochastic optimization,IEEE Journal of Selected Topics in Signal Processing,5(4):772-790,2011.
[24]M.Zhu and S.Martinez,On distributed convex optimization under inequality and equality constraints,IEEE Transaction on Automatic Control,57(1):151-164,2012.
[25]R.Olfati-Saber,J.A.Faxand R.M.Murray,Consensus and cooperation in networked multi-agent systems,Proceeding of the IEEE,95(1):215-233,2007.
[26]J.A.Bondy and U.S.R.Murty,Graph Theory With Applications,IEEE Journals and Magazines,63(10):1533-1534,1976.
[27]Hao Xu,Xiaoshun Zhang and Tao Yu,Robust collaborative consistency algorithm of economic dispatch under nonideal communication network conditions,Automation of Electric Power Systems,40(14),2016.