CVaR risk-based optimization framework for renewable energy management in distribution systems with DGs and EVs

Abstract A method based on chance constrained second-order cone programming (CCSOCP) is presented for the optimal risk value control of power loss in distribution systems with the distributed generation (DG) of renewable energy systems and electric vehicles (EVs). The charging power of the EV is seen as a random variable, and the risk value of the power loss – due to the uncertainties in the power output of distributed generation of renewable energy systems and charging power of electric vehicles – is studied. Moreover, a second-order cone programming based method is also presented to constrain the potential risk of power loss to an acceptable range by optimally coordinating the power output of DG and the EV charging power in a distribution system. A conditional value at risk (CVaR) model for the power loss of distribution systems is presented and CVaR is taken as a constraint to control the risk value of power loss due to uncertainties in DG and EV charging. The results of a test on a 69-node system are used to verify the validity of the risk control method proposed in this paper.

[1]  R. Jabr.  Optimal Power Flow Using an Extended Conic Quadratic Formulation , 2008, IEEE Transactions on Power Systems.

[2]  V. Vittal,et al.  Online Risk-Based Security Assessment , 2002, IEEE Power Engineering Review.

[3]  Roy Billinton,et al.  Operating Risk Analysis of Wind-integrated Power Systems , 2012 .

[4]  Michael Negnevitsky,et al.  Risk Assessment for Power System Operation Planning With High Wind Power Penetration , 2015, IEEE Transactions on Power Systems.

[5]  Shokri Z. Selim,et al.  Risk-averse multi-product selective newsvendor problem with different market entry scenarios under CVaR criterion , 2017, Comput. Ind. Eng..

[6]  R. Billinton,et al.  Considering load-carrying capability and wind speed correlation of WECS in generation adequacy assessment , 2006, IEEE Transactions on Energy Conversion.

[7]  Jiang Wu,et al.  Maximizing renewable energy penetration through distribution network reconfiguration using mixed-integer conic programming , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[8]  R. Jabr,et al.  Minimum Loss Network Reconfiguration Using Mixed-Integer Convex Programming , 2012, IEEE Transactions on Power Systems.

[9]  Akbar Ebrahimi,et al.  Short-Term Impacts of DR Programs on Reliability of Wind Integrated Power Systems Considering Demand-Side Uncertainties , 2016, IEEE Transactions on Power Systems.

[10]  Badrul Chowdhury,et al.  Further development of the Overload Risk Index, an indicator of system vulnerability , 2009, 41st North American Power Symposium.

[11]  Liu Bin.  A new risk measure and its application in portfolio optimization: The SPP–CVaR approach , 2015 .

[12]  Z. Tan,et al.  Application of CVaR risk aversion approach in the dynamical scheduling optimization model for virtual power plant connected with wind-photovoltaic-energy storage system with uncertainties and demand response , 2017 .

[13]  Dirk Van Hertem,et al.  Risk-Based Management of Overloads Caused by Power Injection Uncertainties Using Power Flow Controlling Devices , 2015, IEEE Transactions on Power Systems.

[14]  James D. McCalley,et al.  Risk based voltage security assessment , 2000 .

[15]  Alireza Maheri,et al.  A critical evaluation of deterministic methods in size optimisation of reliable and cost effective standalone hybrid renewable energy systems , 2014, Reliab. Eng. Syst. Saf..

[16]  Antoine Lejay,et al.  Approximation of CVaR minimization for hedging under exponential-Lévy models , 2017, J. Comput. Appl. Math..

[17]  Pierre Pinson,et al.  On‐line assessment of prediction risk for wind power production forecasts , 2003 .

[18]  Pierluigi Mancarella,et al.  Benefits of Advanced Smart Metering for Demand Response based Control of Distribution Networks , 2010 .

[19]  Liang Han,et al.  Uncertainty Tracing of Distributed Generations via Complex Affine Arithmetic Based Unbalanced Three-Phase Power Flow , 2015, IEEE Transactions on Power Systems.

[20]  Zhen Wang,et al.  A Distributionally Robust Co-Ordinated Reserve Scheduling Model Considering CVaR-Based Wind Power Reserve Requirements , 2016, IEEE Transactions on Sustainable Energy.

[21]  P. Luh,et al.  Risk Analysis for Distribution Systems in the Northeast U.S. Under Wind Storms , 2014, IEEE Transactions on Power Systems.

[22]  D. Jayaweera,et al.  Comparison of risk-based and deterministic security assessments , 2007 .

[23]  L. Bertling,et al.  Probabilistic security assessment for power system operations , 2004, IEEE Power Engineering Society General Meeting, 2004..

[24]  Mohammad A. S. Masoum,et al.  Real-Time Coordination of Plug-In Electric Vehicle Charging in Smart Grids to Minimize Power Losses and Improve Voltage Profile , 2011, IEEE Transactions on Smart Grid.

[25]  Roy Billinton,et al.  Unit Commitment Risk Analysis of Wind Integrated Power Systems , 2009 .

[26]  Javier Contreras,et al.  Stochastic Unit Commitment in Isolated Systems With Renewable Penetration Under CVaR Assessment , 2016, IEEE Transactions on Smart Grid.

[27]  Jinyu Wen,et al.  Transient stability risk assessment of power systems incorporating wind farms , 2013 .

[28]  Esteban Gil,et al.  Generation Capacity Expansion Planning Under Hydro Uncertainty Using Stochastic Mixed Integer Programming and Scenario Reduction , 2015, IEEE Transactions on Power Systems.

[29]  R. Jabr.  Radial distribution load flow using conic programming , 2006, IEEE Transactions on Power Systems.

[30]  Ping Guo,et al.  An inexact CVaR two-stage mixed-integer linear programming approach for agricultural water management under uncertainty considering ecological water requirement , 2017, Ecological Indicators.

[31]  F. Y. Ettoumi,et al.  Statistical analysis of solar measurements in Algeria using beta distributions , 2002 .

[32]  Ali Elkamel,et al.  Optimal Transition to Plug-In Hybrid Electric Vehicles in Ontario, Canada, Considering the Electricity-Grid Limitations , 2010, IEEE Transactions on Industrial Electronics.

[33]  Zhifeng Liu,et al.  Fireworks algorithm for mean-VaR/CVaR models , 2017 .

[34]  Stanton W. Hadley,et al.  Potential Impacts of Plug-in Hybrid Electric Vehicles on Regional Power Generation , 2009 .

[35]  S. S. Venkata,et al.  Coordinated Charging of Plug-In Hybrid Electric Vehicles to Minimize Distribution System Losses , 2011, IEEE Transactions on Smart Grid.

[36]  V. Vittal,et al.  Annual Risk Assessment for Overload Security , 2001, IEEE Power Engineering Review.

[37]  Raquel Balbás,et al.  VaR as the CVaR sensitivity: Applications in risk optimization , 2017, J. Comput. Appl. Math..

[38]  Zeng Yuan.  A PRACTICAL DIRECT METHOD FOR DETERMINING DYNAMIC SECURITY REGIONS OF ELECTRIC POWER SYSTEMS , 2003 .

[39]  J. Cidras,et al.  Wind speed simulation in wind farms for steady-state security assessment of electrical power systems , 1999 .

[40]  Yue Yuan,et al.  Modeling of Load Demand Due to EV Battery Charging in Distribution Systems , 2011, IEEE Transactions on Power Systems.

[41]  James D. McCalley,et al.  Risk-Based Locational Marginal Pricing and Congestion Management , 2014, IEEE Transactions on Power Systems.

[42]  C. A. Canizares,et al.  A Robust Optimization Approach for Planning the Transition to Plug-in Hybrid Electric Vehicles , 2011, IEEE Transactions on Power Systems.

[43]  Tao Xu,et al.  Hierarchical Risk Assessment of Transmission System Considering the Influence of Active Distribution Network , 2015, IEEE Transactions on Power Systems.

[44]  Baha Alzalg.  Decomposition-based interior point methods for stochastic quadratic second-order cone programming , 2014, Appl. Math. Comput..

[45]  James D. McCalley,et al.  A Computational Strategy to Solve Preventive Risk-Based Security-Constrained OPF , 2013, IEEE Transactions on Power Systems.

[46]  Li Si.  Security Economic Dispatch in Wind Power Integrated Systems Using a Conditional Risk Method , 2012 .

[47]  Peng Li,et al.  Application of conic programming for optimal distributed generation allocation in distribution network , 2014, 2014 China International Conference on Electricity Distribution (CICED).

[48]  J.D. McCalley,et al.  Power System Risk Assessment and Control in a Multiobjective Framework , 2009, IEEE Transactions on Power Systems.

[49]  J. C. Gomez,et al.  Impact of EV battery chargers on the power quality of distribution systems , 2002 .

[50]  Dilan JAYAWEERA,et al.  Steady-state security in distribution networks with large wind farms , 2014, ENERGYO.