An IoT- Based Decision Support Tool for Improving the Performance of Smart Grids Connected With Distributed Energy Sources and Electric Vehicles

The growing penetration of distributed energy sources (DES), such as photovoltaic (PV) solar power, battery energy systems and electric vehicles (EVs) into low voltage distribution networks is creating serious challenges for distribution network operators. Uncertain nature of these DES and EV charging is a key factor to cause unbalance, which degrade network performance in terms of energy loss, voltage unbalance, and voltage profile of the distribution network, etc. Some methods were proposed to mitigate such negative impact of these uncertain DES and EV charging from both centralized and decentralized approaches by controlling charging or discharging power of EVs. However, these methods involve all active EVs to participate in coordination and this causes significant inconvenience to EV owners along with requirements of complex communication infrastructure and huge data processing overhead. This article proposes an Internet of Things -based centralized control strategy to coordinate EV and DES distribution by using the differential evolution (DE) optimization algorithm. The obtained results show that the proposed control strategy can improve network performance (voltage imbalance, neutral current, energy loss, and node voltage) significantly. In addition, the control strategy is less demanding on communication infrastructure and convenient for EV owners as well as having a lighter data processing overhead.

[1]  Marcos J. Rider,et al.  A Mixed-Integer Linear Programming Model for the Electric Vehicle Charging Coordination Problem in Unbalanced Electrical Distribution Systems , 2015, IEEE Transactions on Smart Grid.

[2]  A. Keane,et al.  Optimal Charging of Electric Vehicles in Low-Voltage Distribution Systems , 2012, IEEE Transactions on Power Systems.

[3]  Linni Jian,et al.  High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles , 2017 .

[4]  Rachid Cherkaoui,et al.  Identification of control and management strategies for LV unbalanced microgrids with plugged-in electric vehicles , 2010 .

[5]  Shuangxia Niu,et al.  A scenario of vehicle-to-grid implementation and its double-layer optimal charging strategy for minimizing load variance within regional smart grids , 2014 .

[6]  Johan Driesen,et al.  Multiagent Charging of Electric Vehicles Respecting Distribution Transformer Loading and Voltage Limits , 2014, IEEE Transactions on Smart Grid.

[7]  Federico Milano,et al.  Optimal Load Management With Inclusion of Electric Vehicles and Distributed Energy Resources , 2014, IEEE Transactions on Smart Grid.

[8]  Rafael Cossent,et al.  Integration of PV and EVs in unbalanced residential LV networks and implications for the smart grid and advanced metering infrastructure deployment , 2017 .

[9]  Pangan Ting,et al.  Decentralized Plug-in Electric Vehicle Charging Selection Algorithm in Power Systems , 2012, IEEE Transactions on Smart Grid.

[10]  Gengfa Fang,et al.  Optimal Dispatch of Electrical Vehicle and PV Power to Improve the Power Quality of an Unbalanced Distribution Grid , 2019, 2019 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS).

[11]  Junwei Lu,et al.  Improved Neutral Current Compensation With a Four-Leg PV Smart VSI in a LV Residential Network , 2017, IEEE Transactions on Power Delivery.

[12]  Ahmed A. Zaki Diab,et al.  Optimal sitting and sizing of renewable distributed generations in distribution networks using a hybrid PSOGSA optimization algorithm , 2017, 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe).

[13]  John Edisson Cardona,et al.  Decentralized electric vehicles charging coordination using only local voltage magnitude measurements , 2018 .

[14]  Luis F. Ochoa,et al.  Control of EV Charging Points for Thermal and Voltage Management of LV Networks , 2016, IEEE Transactions on Power Systems.

[15]  Tansu Alpcan,et al.  Electric vehicle charging and grid constraints: Comparing distributed and centralized approaches , 2013, 2013 IEEE Power & Energy Society General Meeting.

[16]  C. Y. Chung,et al.  Uncertainties of EV Charging and Effects on Well-Being Analysis of Generating Systems , 2015, IEEE Transactions on Power Systems.

[17]  Dheeraj Kumar Khatod,et al.  Techno-economic and environmental approach for optimal placement and sizing of renewable DGs in distribution system , 2017 .

[18]  Hassan Feshki Farahani,et al.  Improving voltage unbalance of low-voltage distribution networks using plug-in electric vehicles , 2017 .

[19]  Saifur Rahman,et al.  Grid Integration of Electric Vehicles and Demand Response With Customer Choice , 2012, IEEE Transactions on Smart Grid.

[20]  Ruben Romero,et al.  Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation , 2017 .

[21]  Pramod Agarwal,et al.  Neutral current compensation in three-phase, four-wire systems: A review , 2012 .

[22]  Masoud Esmaili,et al.  Multi-objective optimal charging of plug-in electric vehicles in unbalanced distribution networks , 2015 .

[23]  Damian Flynn,et al.  Local Versus Centralized Charging Strategies for Electric Vehicles in Low Voltage Distribution Systems , 2012, IEEE Transactions on Smart Grid.

[24]  Masoud Rashidinejad,et al.  Dynamic phase balancing in the smart distribution networks , 2017 .

[25]  Arindam Ghosh,et al.  Power capacity management of dynamic voltage restorers used for voltage sag and unbalance compensation , 2017, 2017 Australasian Universities Power Engineering Conference (AUPEC).