A Novel Resource Reservation Scheme for Mobile PHEVs in V2G Environment Using Game Theoretical Approach

With the widespread penetration of plug-in hybrid electric vehicles (PHEVs), the overall demand on microgrids (MGs) may increase manifold in the near future. Unregulated power demands from PHEVs may increase the demand-supply gap at MGs. Thus, to keep MGs stabilize and cater the ever-growing energy demands, there is a requirement of an intelligent solution to regulate and manage PHEVs in vehicle-to-grid (V2G) environment. Keeping in view the given issues, this paper proposes a novel scheme that aims to regulate PHEVs' charging and discharging activities based on MGs' day-ahead load curves. These load curves are obtained by utilizing the existing load forecasting techniques such as fuzzy logic (FL) and artificial neural networks (ANNs). Efficient utilization of PHEVs according to these curves may play a vital role in flattening MG's load profile. Thus, the proposed scheme works by reserving resources such as time slots and charging points (CPs) for PHEVs during peak shaving and valley filling. Different algorithms pertaining to resource reservation for PHEVs have also been designed. These algorithms employ the concepts of game theory and the 0/1 knapsack problem for supporting peak shaving and valley filling, respectively. Moreover, PHEVs are also utilized when there are transitions from valley filling to peak shaving areas in the load curves and vice versa. PHEVs involved in this process have both charging and discharging capabilities and are referred to as dual-mode PHEVs. The proposed scheme has been tested with respect to various parameters, and its performance was found satisfactory.

[1]  Issarachai Ngamroo,et al.  PHEVs Bidirectional Charging/Discharging and SoC Control for Microgrid Frequency Stabilization Using Multiple MPC , 2015, IEEE Transactions on Smart Grid.

[2]  Alexander Brodsky,et al.  Towards Optimal Decision Guidance for Smart Grids with Integrated Renewable Generation and Water Desalination , 2014, 2014 IEEE 26th International Conference on Tools with Artificial Intelligence.

[3]  Sudip Misra,et al.  Cloud Computing Applications for Smart Grid: A Survey , 2015, IEEE Transactions on Parallel and Distributed Systems.

[4]  Wenxin Liu,et al.  Distributed Dynamic Programming-Based Approach for Economic Dispatch in Smart Grids , 2015, IEEE Transactions on Industrial Informatics.

[5]  Yu-Hsiu Lin,et al.  Development of an Improved Time–Frequency Analysis-Based Nonintrusive Load Monitor for Load Demand Identification , 2014, IEEE Transactions on Instrumentation and Measurement.

[6]  Chao Yang,et al.  Correctional DP-Based Energy Management Strategy of Plug-In Hybrid Electric Bus for City-Bus Route , 2015, IEEE Transactions on Vehicular Technology.

[7]  T. Funabashi,et al.  Next day load curve forecasting using hybrid correction method , 2005, IEEE Transactions on Power Systems.

[8]  Neeraj Kumar,et al.  Providing healthcare services on-the-fly using multi-player cooperation game theory in Internet of Vehicles (IoV) environment , 2015, Digit. Commun. Networks.

[9]  Omid Ameri Sianaki,et al.  A Knapsack problem approach for achieving efficient energy consumption in smart grid for endusers' life style , 2010, 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply.

[10]  Willett Kempton,et al.  Using fleets of electric-drive vehicles for grid support , 2007 .

[11]  Shengli Xie,et al.  PHEV Charging and Discharging Cooperation in V2G Networks: A Coalition Game Approach , 2014, IEEE Internet of Things Journal.

[12]  Xinghuo Yu,et al.  The New Frontier of Smart Grids , 2011, IEEE Industrial Electronics Magazine.

[13]  Nirwan Ansari,et al.  Alleviating Solar Energy Congestion in the Distribution Grid via Smart Metering Communications , 2012, IEEE Transactions on Parallel and Distributed Systems.

[14]  Sudip Misra,et al.  D2P: Distributed Dynamic Pricing Policyin Smart Grid for PHEVs Management , 2015, IEEE Transactions on Parallel and Distributed Systems.

[15]  P. L. So,et al.  V2G Capacity Estimation Using Dynamic EV Scheduling , 2014, IEEE Transactions on Smart Grid.

[16]  Kan Zhou,et al.  Randomized PHEV Charging Under Distribution Grid Constraints , 2014, IEEE Transactions on Smart Grid.

[17]  Seema Bawa,et al.  An Intelligent Context-aware Congestion Resolution Protocol for Data Dissemination in Vehicular Ad Hoc Networks , 2015, Mob. Networks Appl..

[18]  Rajib Das,et al.  Mathematical Modeling for Economic Evaluation of Electric Vehicle to Smart Grid Interaction , 2014, IEEE Transactions on Smart Grid.

[19]  Chao Yang,et al.  Hybrid genetic algorithm-based optimization of powertrain and control parameters of plug-in hybrid electric bus , 2015, J. Frankl. Inst..

[20]  Naveen K. Chilamkurti,et al.  Bayesian Coalition Negotiation Game as a Utility for Secure Energy Management in a Vehicles-to-Grid Environment , 2016, IEEE Transactions on Dependable and Secure Computing.

[21]  Ju Bin Song,et al.  Optimal charging and discharging for multiple PHEVs with demand side management in vehicle-to-building , 2012, Journal of Communications and Networks.

[22]  Nei Kato,et al.  GT-CFS: A Game Theoretic Coalition Formulation Strategy for Reducing Power Loss in Micro Grids , 2014, IEEE Transactions on Parallel and Distributed Systems.

[23]  Shi-Jaw Chen,et al.  Nontechnical Loss and Outage Detection Using Fractional-Order Self-Synchronization Error-Based Fuzzy Petri Nets in Micro-Distribution Systems , 2015, IEEE Transactions on Smart Grid.

[24]  Praveen Kumar,et al.  A Multi Charging Station for Electric Vehicles and Its Utilization for Load Management and the Grid Support , 2013, IEEE Transactions on Smart Grid.

[25]  Naveen K. Chilamkurti,et al.  Bayesian coalition game for the internet of things: an ambient intelligence-based evaluation , 2015, IEEE Communications Magazine.

[26]  Sukumar Mishra,et al.  Biogeography based optimal state feedback controller for frequency regulation of a smart microgrid , 2014 .

[27]  Xin Wang,et al.  Energy Management Strategy for Plug-In Hybrid Electric Vehicles via Bidirectional Vehicle-to-Grid , 2017, IEEE Systems Journal.

[28]  Wenxin Liu,et al.  Novel Multiagent Based Load Restoration Algorithm for Microgrids , 2011, IEEE Transactions on Smart Grid.

[29]  Fang Zhuo,et al.  System Operation and Energy Management of a Renewable Energy-Based DC Micro-Grid for High Penetration Depth Application , 2015, IEEE Transactions on Smart Grid.

[30]  Subhas C. Misra,et al.  An intelligent RFID-enabled authentication scheme for healthcare applications in vehicular mobile cloud , 2016, Peer-to-Peer Netw. Appl..

[31]  Arye Nehorai,et al.  Joint Optimization of Hybrid Energy Storage and Generation Capacity With Renewable Energy , 2013, IEEE Transactions on Smart Grid.

[32]  Nirwan Ansari,et al.  Decentralized Controls and Communications for Autonomous Distribution Networks in Smart Grid , 2013, IEEE Transactions on Smart Grid.

[33]  Mo-Yuen Chow,et al.  A Survey on the Electrification of Transportation in a Smart Grid Environment , 2012, IEEE Transactions on Industrial Informatics.

[34]  Lingfeng Wang,et al.  A particle swarm optimization based control strategy for plug-in hybrid electric vechicles at residential networks level , 2014, 2014 IEEE PES T&D Conference and Exposition.

[35]  Yong Cheol Kang,et al.  Short-term load forecasting for special days in anomalous load conditions using neural networks and fuzzy inference method , 2000 .

[36]  Ivan Stojmenovic,et al.  GTES: An Optimized Game-Theoretic Demand-Side Management Scheme for Smart Grid , 2014, IEEE Systems Journal.

[37]  M. Ouyang,et al.  Approximate Pontryagin’s minimum principle applied to the energy management of plug-in hybrid electric vehicles , 2014 .

[38]  Guoqing Xu,et al.  Regulated Charging of Plug-in Hybrid Electric Vehicles for Minimizing Load Variance in Household Smart Microgrid , 2013, IEEE Transactions on Industrial Electronics.