Adaptive Blockchain-Based Electric Vehicle Participation Scheme in Smart Grid Platform

The electric vehicle (EV) charging scheme can reduce the power generation costs and improve the smart grid resilience. However, the huge penetrations of EVs can impact the voltage stability and operating costs. In this paper, a novel EV participation charging scheme is proposed for a decentralized blockchain-enabled smart grid system. Our objectives are to minimize the power fluctuation level in the grid network and the overall charging cost for EV users. We first formulate the power fluctuation level problem of the smart grid system that take into accounts of EV battery capacities, charging rates, and EV users charging behavior. And then, we propose a novel adaptive blockchain-based electric vehicle participation (AdBEV) scheme that uses the Iceberg order execution algorithm to obtain an improved EV charging and discharging schedule. The simulation results show the proposed scheme outperforms the scheme that applying genetic algorithm approach in term of lowering the power fluctuation level and overall charging costs.

[1]  Arshdeep Bahga,et al.  Blockchain Platform for Industrial Internet of Things , 2016 .

[2]  Hortensia Amaris,et al.  Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms , 2014 .

[3]  Jianhui Wang,et al.  Resilient Distribution System by Microgrids Formation After Natural Disasters , 2016, IEEE Transactions on Smart Grid.

[4]  Michael Devetsikiotis,et al.  Blockchains and Smart Contracts for the Internet of Things , 2016, IEEE Access.

[5]  Thitinan Tantidham,et al.  Review of Ethereum: Smart home case study , 2017, 2017 2nd International Conference on Information Technology (INCIT).

[6]  Yue Chen,et al.  Optimised electric vehicles charging scheme with uncertain user-behaviours in smart grids , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[7]  Gaetano Zizzo,et al.  The Blockchain in Microgrids for Transacting Energy and Attributing Losses , 2017, 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[8]  Angelika Esser,et al.  The navigation of an iceberg: The optimal use of hidden orders , 2007 .

[9]  Jonathan Mather,et al.  Blockchains for decentralized optimization of energy resources in microgrid networks , 2017, 2017 IEEE Conference on Control Technology and Applications (CCTA).

[10]  Hamed Mohsenian Rad,et al.  Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments , 2010, IEEE Transactions on Smart Grid.

[11]  Prateek Saxena,et al.  Making Smart Contracts Smarter , 2016, IACR Cryptol. ePrint Arch..

[12]  Muhammad Anan,et al.  Smart grid opportunities and challenges of integrating renewable sources: A survey , 2014, 2014 International Wireless Communications and Mobile Computing Conference (IWCMC).

[13]  Xiang Cheng,et al.  Energy Management Framework for Electric Vehicles in the Smart Grid: A Three-Party Game , 2016, IEEE Communications Magazine.

[14]  Vincent W. S. Wong,et al.  Robust Frequency Regulation Capacity Scheduling Algorithm for Electric Vehicles , 2017, IEEE Transactions on Smart Grid.

[15]  Xiaoyu Wang,et al.  Aggregation Model-Based Optimization for Electric Vehicle Charging Strategy , 2013, IEEE Transactions on Smart Grid.

[16]  Sijie CHEN,et al.  From demand response to transactive energy: state of the art , 2017 .

[17]  Ying Jun Zhang,et al.  Online Charging Scheduling Algorithms of Electric Vehicles in Smart Grid: An Overview , 2016, IEEE Communications Magazine.

[18]  Xiapu Luo,et al.  Under-optimized smart contracts devour your money , 2017, 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER).

[19]  Mohamed A. El-Sharkawi,et al.  Optimal Combined Bidding of Vehicle-to-Grid Ancillary Services , 2012, IEEE Transactions on Smart Grid.

[20]  Christof Weinhardt,et al.  A blockchain-based smart grid: towards sustainable local energy markets , 2017, Computer Science - Research and Development.

[21]  Yousef Mahmoud,et al.  Probabilistic Modeling of Electric Vehicle Charging Pattern Associated with Residential Load for Voltage Unbalance Assessment , 2017 .

[22]  Ann Nowé,et al.  NRG-X-Change - A Novel Mechanism for Trading of Renewable Energy in Smart Grids , 2014, SMARTGREENS.

[23]  E. Sortomme,et al.  Intelligent dispatch of Electric Vehicles performing vehicle-to-grid regulation , 2012, 2012 IEEE International Electric Vehicle Conference.