Optimal Coordination of G2V and V2G to Support Power Grids With High Penetration of Renewable Energy

Electric vehicles (EVs) have recently gained much popularity as a green alternative to fossil-fuel cars and a feasible solution to reduce air pollution in big cities. The use of EVs can also be extended as a demand response tool to support high penetration of renewable energy (RE) sources in future smart grid. Based on the certainty equivalent adaptive control (CECA) principle and a customer participation program, this paper presents a novel control strategy using optimization technique to coordinate not only the charging but also the discharging of EV batteries to deal with the intermittency in RE production. In addition, customer charging requirements and schedules are incorporated into the optimization algorithm to ensure customer satisfaction, and further improve the control performance. The merits of this scheme are its simplicity, efficiency, robustness and readiness for practical applications. The effectiveness of the proposed control algorithm is demonstrated by computer simulations of a power system with high level of wind energy integration.

[1]  Bruce H. Krogh,et al.  Wind Integration in Power Systems: Operational Challenges and Possible Solutions , 2011, Proceedings of the IEEE.

[2]  Prasanta Ghosh,et al.  Optimizing Electric Vehicle Charging: A Customer's Perspective , 2013, IEEE Transactions on Vehicular Technology.

[3]  Cishen Zhang,et al.  Smart Charging and Discharging of Electric Vehicles to Support Grid with High Penetration of Renewable Energy , 2014 .

[4]  Shyh-Jier Huang,et al.  Short-term load forecasting via ARMA model identification including non-Gaussian process considerations , 2003 .

[5]  Paras Mandal,et al.  A review of wind power and wind speed forecasting methods with different time horizons , 2010, North American Power Symposium 2010.

[6]  Tony Markel Plug-In Hybrid Electric Vehicles , 2006 .

[7]  Wencong Su,et al.  Stochastic Energy Scheduling in Microgrids With Intermittent Renewable Energy Resources , 2014, IEEE Transactions on Smart Grid.

[8]  Phil Taylor,et al.  Evaluating the benefits of an electrical energy storage system in a future smart grid , 2010 .

[9]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[10]  Chris Mi,et al.  Hybrid Electric Vehicles: Principles and Applications with Practical Perspectives , 2011 .

[11]  Ahmed Yousuf Saber,et al.  Resource Scheduling Under Uncertainty in a Smart Grid With Renewables and Plug-in Vehicles , 2012, IEEE Systems Journal.

[12]  Ahmed Yousuf Saber,et al.  Efficient Utilization of Renewable Energy Sources by Gridable Vehicles in Cyber-Physical Energy Systems , 2010, IEEE Systems Journal.

[13]  Chengke Zhou,et al.  Modeling of the Cost of EV Battery Wear Due to V2G Application in Power Systems , 2011, IEEE Transactions on Energy Conversion.

[14]  Benjamin K. Sovacool,et al.  Beyond Batteries: An Examination of the Benefits and Barriers to Plug-In Hybrid Electric Vehicles (PHEVs) and a Vehicle-to-Grid (V2G) Transition , 2009 .

[15]  Leon M. Tolbert,et al.  Single-Phase On-Board Bidirectional PEV Charger for V2G Reactive Power Operation , 2015, IEEE Transactions on Smart Grid.

[16]  Kai Ding,et al.  Battery-Management System (BMS) and SOC Development for Electrical Vehicles , 2011, IEEE Transactions on Vehicular Technology.

[17]  Ali Marjan Wind farm performance , 2016 .

[18]  Chris Mi,et al.  5. Plug-in Hybrid Electric Vehicles , 2011 .

[19]  Local Infrastructure Creating a market: Victorian electric vehicle trial mid-term report , 2013 .

[20]  Ahmed Yousuf Saber,et al.  Plug-in Vehicles and Renewable Energy Sources for Cost and Emission Reductions , 2011, IEEE Transactions on Industrial Electronics.

[21]  Mohammad Shahidehpour,et al.  Hourly Coordination of Electric Vehicle Operation and Volatile Wind Power Generation in SCUC , 2012, IEEE Transactions on Smart Grid.