Wind Power Dispatch based on Wind Forecasting,Electricity Price and Battery Lifetime Estimation
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- 英文论文题名：Wind Power Dispatch based on Wind Forecasting,Electricity Price and Battery Lifetime Estimation
- 论文作者：Wenhao Zhuo ; Andrey V.Savkin
- 英文论文作者：Wenhao Zhuo ; Andrey V.Savkin ; School of Electrical Engineering and Telecommunications ; The University of New South Wales
- 年：2017
- 作者机构：School of Electrical Engineering and Telecommunications,The University of New South Wales;
- 英文论文关键词：Wind power control ; battery energy storage system ; battery lifetime estimation ; dynamic programming
- 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：TM614
- 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：6
- 文件大小：400k
- 原文格式：D
- 会议级别：全国
摘要
Battery energy storage systems(BESS) are widely used in wind power systems to improve the dispatchability of wind power. In this paper, a wind power trading strategy using controllable BESS is presented to maximize the profit of wind power plants. A dynamic programming algorithm is produced to control the operation of BESS based on forecasted wind power, electricity price and battery lifetime estimation. The aim is to charge/discharge the BESS over different electricity price periods to generate higher income, and the use of battery lifetime estimation in the algorithm is to solve suitable discharge currents and depth of discharges that minimize the battery lifetime consumption, therefore reducing the cost of BESS. The algorithm is flexible and can be implemented to batteries with different specifications. It is tested with commercial battery data available online and real wind energy data from wind farms.
Battery energy storage systems(BESS) are widely used in wind power systems to improve the dispatchability of wind power. In this paper, a wind power trading strategy using controllable BESS is presented to maximize the profit of wind power plants. A dynamic programming algorithm is produced to control the operation of BESS based on forecasted wind power, electricity price and battery lifetime estimation. The aim is to charge/discharge the BESS over different electricity price periods to generate higher income, and the use of battery lifetime estimation in the algorithm is to solve suitable discharge currents and depth of discharges that minimize the battery lifetime consumption, therefore reducing the cost of BESS. The algorithm is flexible and can be implemented to batteries with different specifications. It is tested with commercial battery data available online and real wind energy data from wind farms.
Battery energy storage systems(BESS) are widely used in wind power systems to improve the dispatchability of wind power. In this paper, a wind power trading strategy using controllable BESS is presented to maximize the profit of wind power plants. A dynamic programming algorithm is produced to control the operation of BESS based on forecasted wind power, electricity price and battery lifetime estimation. The aim is to charge/discharge the BESS over different electricity price periods to generate higher income, and the use of battery lifetime estimation in the algorithm is to solve suitable discharge currents and depth of discharges that minimize the battery lifetime consumption, therefore reducing the cost of BESS. The algorithm is flexible and can be implemented to batteries with different specifications. It is tested with commercial battery data available online and real wind energy data from wind farms.
引文
[1]B.-M.Hodge,D.Lew,M.Milligan,H.Holttinen,S.Sillanp??,E.Gómez-Lázaro,et al.,"Wind power forecasting error distributions:An international comparison,"in 11th Annual International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants Conference,2012.
[2]Global Wind Energy Council.Global Wind Report 2015.Available:http://www.gwec.net/wp-content/uploads/vip/GWECGlobal-Wind-2015-Report_April-2016_22_04.pdf
[3]P.L.Joskow,"Comparing the costs of intermittent and dispatchable electricity generating technologies,"The American Economic Review,vol.101,pp.238-241,2011.
[4]A.Savkin,M.Khalid,and V.Agelidis,"A Constrained Monotonic Charging/Discharging Strategy for Optimal Capacity of Battery Energy Storage Supporting Wind Farms,"IEEE Transactions on Sustainable Energy,vol.7,pp.1224-1231,2016.
[5]M.Khalid and A.V.Savkin,"A model predictive control approach to the problem of wind power smoothing with controlled battery storage,"Renewable Energy,vol.35,pp.1520-1526,2010.
[6]M.Khalid,A.V.Savkin,and V.G.Agelidis,"An adaptive control algorithm for wind power dispatch using a battery energy storage system,"in 2015 IEEE Conference on Control Applications(CCA),2015,pp.936-940.
[7]M.Khalid,A.V.Savkin,and V.G.Agelidis,"Maximizing the income for wind power plant integrated with a battery energy storage system using dynamic programming,"in 201510th Control Conference(ASCC),2015,pp.1-5.
[8]A.Khatamianfar,M.Khalid,A.V.Savkin,and V.G.Agelidis,"Improving wind farm dispatch in the Australian electricity market with battery energy storage using model predictive control,"IEEE Transactions on Sustainable Energy,vol.4,pp.745-755,2013.
[9]Y.Zheng,D.J.Hill,K.Meng,F.J.Luo,and Z.Y.Dong,"Optimal Short-term Power Dispatch Scheduling for a Wind Farm with Battery Energy Storage System,"IFACPapers On Line,vol.48,pp.518-523,2015.
[10]M.Khalid and A.V.Savkin,“A method for short-term wind power prediction with multiple observation points,”IEEE Transactions on Power Systems,27(2),pp.579-586,2012.
[11]M.Khalid and A.V.Savkin,“Minimization and Control of Battery Energy Storage for Wind Power Smoothing:Aggregated,Distributed and Semi-distributed Storage,”Renewable Energy,vol.64,pp.105-112,2014.
[12]M.Khalid,A.Ahmadi,A.V.Savkin and V.G.Agelidis,“Minimizing the Energy Cost for Microgrids Integrated With Renewable Energy Resources and Conventional Generation Using Controlled Battery Energy Storage,”Renewable Energy,vol.97,pp.646–655,November 2016.
[13]Australian Energy Market Operator.Participant categories in the National Electricity Market.Available:http://www.aemo.com.au/-/media/Files/PDF/ParticipantCategories-in-the-National-Electricity-Market.ashxs
[14]D.I.Stroe,M,?wierczyński,A.I.Stan,et al.,"Accelerated Lifetime Testing Methodology for Lifetime Estimation of Lithium-Ion Batteries Used in Augmented Wind Power Plants,"IEEE Transactions on Industry Applications,vol.50,pp.4006-4017,2014.
[15]D.U.Sauer and H.Wenzl,"Comparison of different approaches for lifetime prediction of electrochemical systems—Using lead-acid batteries as example,"Journal of Power Sources,vol.176,pp.534-546,2008.
[16]S.Drouilhet and B.Johnson,"A Battery Life Prediction Method for Hybrid Power Applications Preprint,"in The 35th AIAA Aerospace Seienees Meeting and Exhibit,Reno,Nevada,USA,1997.
[17]B.-M.Hodge and M.Milligan,"Wind power forecasting error distributions over multiple timescales,"in Power and Energy Society General Meeting,2011 IEEE,2011,pp.1-8.
[18]D.P.Bertsekas,Dynamic Programming and Optimal Control:Athena Scientific,2000.
[19]S.A.Pourmousavi,R.K.Sharma,and B.Asghari,"A framework for real-time power management of a grid-tied microgrid to extend battery lifetime and reduce cost of energy,"in 2012 IEEE PES Innovative Smart Grid Technologies(ISGT),2012,pp.1-8.
[20]A.Keeli and R.K.Sharma,"Optimal use of second life battery for peak load management and improving the life of the battery,"in Electric Vehicle Conference(IEVC),2012IEEE International,2012,pp.1-6.
[21]Rolls Battery.8CS25P Flooded Deep Cycle Battery Datasheet.Available:http://www.rollsbattery.com/wpcontent/uploads/batteries/8CS25P.pdf
[22]Rolls Battery.Rolls Battery User Manual.Available:http://rollsbattery.com/wpcontent/plugins/rollsbatteries/pdfs/Rolls_Battery_Manual.pdf
[23]Math Works.Curve Fitting Toolbox.Available:https://au.mathworks.com/products/curvefitting/
[24]K.Takeda,C.Takahashi,H.Arita,N.Kusumi,M.Amano,and A.Emori,"Design of hybrid energy storage system using dual batteries for renewable applications,"in 2014 IEEE PES General Meeting|Conference&Exposition,2014,pp.1-5.
[25]G.Sideratos and N.D.Hatziargyriou,"An Advanced Statistical Method for Wind Power Forecasting,"IEEE Transactions on Power Systems,vol.22,pp.258-265,2007
[2]Global Wind Energy Council.Global Wind Report 2015.Available:http://www.gwec.net/wp-content/uploads/vip/GWECGlobal-Wind-2015-Report_April-2016_22_04.pdf
[3]P.L.Joskow,"Comparing the costs of intermittent and dispatchable electricity generating technologies,"The American Economic Review,vol.101,pp.238-241,2011.
[4]A.Savkin,M.Khalid,and V.Agelidis,"A Constrained Monotonic Charging/Discharging Strategy for Optimal Capacity of Battery Energy Storage Supporting Wind Farms,"IEEE Transactions on Sustainable Energy,vol.7,pp.1224-1231,2016.
[5]M.Khalid and A.V.Savkin,"A model predictive control approach to the problem of wind power smoothing with controlled battery storage,"Renewable Energy,vol.35,pp.1520-1526,2010.
[6]M.Khalid,A.V.Savkin,and V.G.Agelidis,"An adaptive control algorithm for wind power dispatch using a battery energy storage system,"in 2015 IEEE Conference on Control Applications(CCA),2015,pp.936-940.
[7]M.Khalid,A.V.Savkin,and V.G.Agelidis,"Maximizing the income for wind power plant integrated with a battery energy storage system using dynamic programming,"in 201510th Control Conference(ASCC),2015,pp.1-5.
[8]A.Khatamianfar,M.Khalid,A.V.Savkin,and V.G.Agelidis,"Improving wind farm dispatch in the Australian electricity market with battery energy storage using model predictive control,"IEEE Transactions on Sustainable Energy,vol.4,pp.745-755,2013.
[9]Y.Zheng,D.J.Hill,K.Meng,F.J.Luo,and Z.Y.Dong,"Optimal Short-term Power Dispatch Scheduling for a Wind Farm with Battery Energy Storage System,"IFACPapers On Line,vol.48,pp.518-523,2015.
[10]M.Khalid and A.V.Savkin,“A method for short-term wind power prediction with multiple observation points,”IEEE Transactions on Power Systems,27(2),pp.579-586,2012.
[11]M.Khalid and A.V.Savkin,“Minimization and Control of Battery Energy Storage for Wind Power Smoothing:Aggregated,Distributed and Semi-distributed Storage,”Renewable Energy,vol.64,pp.105-112,2014.
[12]M.Khalid,A.Ahmadi,A.V.Savkin and V.G.Agelidis,“Minimizing the Energy Cost for Microgrids Integrated With Renewable Energy Resources and Conventional Generation Using Controlled Battery Energy Storage,”Renewable Energy,vol.97,pp.646–655,November 2016.
[13]Australian Energy Market Operator.Participant categories in the National Electricity Market.Available:http://www.aemo.com.au/-/media/Files/PDF/ParticipantCategories-in-the-National-Electricity-Market.ashxs
[14]D.I.Stroe,M,?wierczyński,A.I.Stan,et al.,"Accelerated Lifetime Testing Methodology for Lifetime Estimation of Lithium-Ion Batteries Used in Augmented Wind Power Plants,"IEEE Transactions on Industry Applications,vol.50,pp.4006-4017,2014.
[15]D.U.Sauer and H.Wenzl,"Comparison of different approaches for lifetime prediction of electrochemical systems—Using lead-acid batteries as example,"Journal of Power Sources,vol.176,pp.534-546,2008.
[16]S.Drouilhet and B.Johnson,"A Battery Life Prediction Method for Hybrid Power Applications Preprint,"in The 35th AIAA Aerospace Seienees Meeting and Exhibit,Reno,Nevada,USA,1997.
[17]B.-M.Hodge and M.Milligan,"Wind power forecasting error distributions over multiple timescales,"in Power and Energy Society General Meeting,2011 IEEE,2011,pp.1-8.
[18]D.P.Bertsekas,Dynamic Programming and Optimal Control:Athena Scientific,2000.
[19]S.A.Pourmousavi,R.K.Sharma,and B.Asghari,"A framework for real-time power management of a grid-tied microgrid to extend battery lifetime and reduce cost of energy,"in 2012 IEEE PES Innovative Smart Grid Technologies(ISGT),2012,pp.1-8.
[20]A.Keeli and R.K.Sharma,"Optimal use of second life battery for peak load management and improving the life of the battery,"in Electric Vehicle Conference(IEVC),2012IEEE International,2012,pp.1-6.
[21]Rolls Battery.8CS25P Flooded Deep Cycle Battery Datasheet.Available:http://www.rollsbattery.com/wpcontent/uploads/batteries/8CS25P.pdf
[22]Rolls Battery.Rolls Battery User Manual.Available:http://rollsbattery.com/wpcontent/plugins/rollsbatteries/pdfs/Rolls_Battery_Manual.pdf
[23]Math Works.Curve Fitting Toolbox.Available:https://au.mathworks.com/products/curvefitting/
[24]K.Takeda,C.Takahashi,H.Arita,N.Kusumi,M.Amano,and A.Emori,"Design of hybrid energy storage system using dual batteries for renewable applications,"in 2014 IEEE PES General Meeting|Conference&Exposition,2014,pp.1-5.
[25]G.Sideratos and N.D.Hatziargyriou,"An Advanced Statistical Method for Wind Power Forecasting,"IEEE Transactions on Power Systems,vol.22,pp.258-265,2007