BATTPOWER Application: Large-Scale Integration of EVs in an Active Distribution Grid -- A Norwegian Case Study

With the considerable increase of Distributed Energy Resources (DER), the reliable and cost-effective operation of distribution grids becomes challenging. The efficient operation relies on computationally dependable and tractable optimisation solvers, which may handle: 1) non-linear AC power flow constraints, and 2) timelinking variables and constraints and objectives of DER, over the operational horizon. In this paper, we introduce an application of a high-performance MultiPeriod AC Optimal Power Flow (MPOPF) solver, called “BATTPOWER”, to simulate active distribution grids for a near-future scenario. A large-scale Norwegian distribution grid along with a large population of Electric Vehicles (EV) are here taken as the case-study. We suggest and analyse three operational strategies (in terms of control of charge scheduling fleet of EV) for the Distribution System Operator (DSO): (a) uncoordinated/dumb charge scheduling, (b) coordinated charge scheduling with the objective of energy cost-minimisation without operational constraints of the grid, and (c) coordinated charge scheduling with the objective of energy cost-minimisation along with the operational constraints of the grid. The results demonstrate that the uncoordinated charging would lead to: 1) overloading of lines and transformers when the share of EVs is above 20%, and 2) higher operational costs than the proposed control strategies of (b) and (c). In strategy (b) operational line/transformer limits are violated when the populations of EVs are growing above 36%. This implies that current market design must be altered to allow active control of a large proportion of DERs within grid operational limits to achieve cost minimization at system level. To our knowledge, the work presented in this paper is the first ever attempt to do a comprehensive analysis of the impact of EV charging demand on a real Norwegian distribution grid. Moreover, the inference of the analysis says that the Norwegian distribution networks are more prone to congestion problems than the voltage problems for the EV demand which includes a smart charging scheme accounting for grid conditions.

[1]  Dr. Timur Gül Global EV Outlook 2019 , 2019 .

[2]  Olaf Schenk,et al.  Toward the Next Generation of Multiperiod Optimal Power Flow Solvers , 2018, IEEE Transactions on Power Systems.

[3]  R.J. Thomas,et al.  On Computational Issues of Market-Based Optimal Power Flow , 2007, IEEE Transactions on Power Systems.

[4]  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.

[5]  Thorkild Bretteville-Jensen The Norwegian electric car controversy: The arguments and some empirical illustrations , 2016 .

[6]  S. Sojoudi,et al.  Optimal charging of plug-in hybrid electric vehicles in smart grids , 2011, 2011 IEEE Power and Energy Society General Meeting.

[7]  Sandra Vogel,et al.  Working time in the European Union , 2010 .

[8]  Hossein Farahmand,et al.  BATTPOWER Toolbox: Memory-Efficient and High-Performance Multi-Period AC Optimal Power Flow Solver , 2020, IEEE Transactions on Power Systems.

[9]  Maurizio Delfanti,et al.  Real-Time Modeling and Control of Electric Vehicles Charging Processes , 2015, IEEE Transactions on Smart Grid.

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

[11]  Antonio Zecchino,et al.  Impact of large‐scale EV integration and fast chargers in a Norwegian LV grid , 2019, The Journal of Engineering.

[12]  Jorge Nocedal,et al.  Knitro: An Integrated Package for Nonlinear Optimization , 2006 .

[13]  Mingjian Cui,et al.  Fast Solving Method Based on Linearized Equations of Branch Power Flow for Coordinated Charging of EVs (EVCC) , 2019, IEEE Transactions on Vehicular Technology.

[14]  L. Wehenkel,et al.  Experiments with the interior-point method for solving large scale optimal power flow problems , 2013 .

[15]  Håkon Marthinsen,et al.  Optimal power flow methods and their application to distribution systems with energy storage : a survey of available tools and methods , 2016 .

[16]  Sukumar Kamalasadan,et al.  Optimal Fast Control and Scheduling of Power Distribution System Using Integrated Receding Horizon Control and Convex Conic Programming , 2016, IEEE Transactions on Industry Applications.

[17]  Jing Yang,et al.  Smart Charging Strategies for Optimal Integration of Plug-In Electric Vehicles Within Existing Distribution System Infrastructure , 2018, IEEE Transactions on Smart Grid.

[18]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[19]  Paul Cuffe,et al.  Visualizing the Electrical Structure of Power Systems , 2017, IEEE Systems Journal.

[20]  Tony Q. S. Quek,et al.  Optimal charging of electric vehicles in smart grid: Characterization and valley-filling algorithms , 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

[21]  Chau Yuen,et al.  Electric Vehicle Charge Scheduling Mechanism to Maximize Cost Efficiency and User Convenience , 2018, IEEE Transactions on Smart Grid.

[22]  Jiang Wu,et al.  Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles , 2016, IEEE Transactions on Smart Grid.

[23]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[24]  Magnus Korpås,et al.  Integration of PEV and PV in Norway using multi-period ACOPF — Case study , 2017, 2017 IEEE Manchester PowerTech.

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

[26]  Nuno Silva,et al.  A Horizon Optimization Control Framework for the Coordinated Operation of Multiple Distributed Energy Resources in Low Voltage Distribution Networks , 2019, Energies.

[27]  Marika Kolbenstvedt,et al.  Learning from Norwegian Battery Electric and Plug-in Hybrid Vehicle users: Results from a survey of vehicle owners , 2016 .

[28]  Tansu Alpcan,et al.  Optimal Charging of Electric Vehicles Taking Distribution Network Constraints Into Account , 2015, IEEE Transactions on Power Systems.

[29]  Iver Bakken Sperstad,et al.  Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties , 2019, Energies.

[30]  Ufuk Topcu,et al.  A simple optimal power flow model with energy storage , 2010, 49th IEEE Conference on Decision and Control (CDC).

[31]  Gerard Ledwich,et al.  A Hierarchical Decomposition Approach for Coordinated Dispatch of Plug-in Electric Vehicles , 2013, IEEE Transactions on Power Systems.

[32]  Chao Du,et al.  Layered and Distributed Charge Load Dispatch of Considerable Electric Vehicles , 2015, IEEE Transactions on Power Systems.

[33]  H. Vincent Poor,et al.  Model Predictive Control for Smart Grids With Multiple Electric-Vehicle Charging Stations , 2017, IEEE Transactions on Smart Grid.

[34]  Mohamed A. El-Sharkawi,et al.  Optimal Charging Strategies for Unidirectional Vehicle-to-Grid , 2011, IEEE Transactions on Smart Grid.

[35]  Paul S. Moses,et al.  Smart load management of plug-in electric vehicles in distribution and residential networks with charging stations for peak shaving and loss minimisation considering voltage regulation , 2011 .

[36]  Francois Bouffard,et al.  Electric Vehicle Aggregator/System Operator Coordination for Charging Scheduling and Services Procurement , 2013, IEEE Transactions on Power Systems.

[37]  Martin Lillebo Impact of EV Integration and Fast Chargers in a Norwegian LV Grid - An analysis based on data from a residential grid in Steinkjer , 2018 .