EV Scheduling for Distribution Peak Load and Grid Congestion Management

By Claude Ziad El-Bayeh

Over the last decade, Electric Vehicles (EVs) have drawn attention of researchers for many reasons. First, EVs require electric energy to supply their traction motors. Second, EVs can be used as battery storage systems, in which they can store or supply energy from/to the grid. Third, thanks to advanced technology of the converters, EVs can provide ancillary services for electric distribution networks (DN) through many applications such as, voltage and frequency regulations, active and reactive power flow compensation, harmonic distortion reduction, energy supply/demand management and integration of renewable energy sources. In response to the evolving needs of the system operators, new businesses were emerged such as EV parking lots, EV charging stations, where the fleet operators use EVs to provide different services and support the grid.

Statement of the Challenge and Opportunity: Gaps, Opportunities, and Drivers

Despite advantages of the EVs in reducing pollution and providing ancillary services to the grid, they can introduce many problems if they are not integrated with grid in an intelligent way. Since EVs have large batteries, they require considerable energy demand to be fully recharged. One of the major problems arises when many of EVs are charged at the same time increasing the risk on the network to challenge a sudden increase in the power demand. Thus, EVs can introduce severe problems such as voltage drop, excess of power demands and peak loads, which may cause a partial or a complete blackout on the network. Furthermore, these severe problems can cause damaged elements of the infrastructure (such as transformers, protection devices, cables, etc.). All these problems lead researchers to new research opportunities and motivate them to propose and develop new solutions to mitigate the impact of EVs on the “distribution network” (DN).

Technological Innovation and Advances

Fortunately, current technology allows researchers to develop new tools and methods to mitigate integration of EVs on the DN. Some of them can be articulated as follows:

  • Different control strategies (e.g., Centralized, Decentralized, Hierarchical, Distributed (Cooperative)) were developed to schedule the charging and discharging of the EVs in an efficient way
  • Different converter topologies were developed to control active and reactive power flow of the EV’s batteries. e.g., Grid to Vehicle (G2V) and Vehicle to Grid (V2G)
  • Different optimization algorithms were developed or used to optimize the charging of EVs by reducing the total electricity cost at the end-user level
  • Different battery technologies were developed to increase the battery’s lifetime and its capacity and reduce its weight
  • Different “Demand Response Programs” (DRP) were developed to create an interaction between the end-users and electricity retailer to control total load on the network and reduce the peak demand in certain periods. The main goal of DRP is to change the electricity price in order to incite users to shift their loads to the periods when the price is low. This results in reduction of network congestion and protection of its elements

All these technological innovations are of great benefit to mitigate the burdens of integration of EVs. For example, control strategies and optimization algorithms are not only used to control and schedule the power flow of the EVs on the grid but also to shave the peak demand, manage the energy and reduce the congestion. It works by finding the optimal power value of the charging or discharging processes of each EV in time “t” in a way that the sum of the total power demand of all loads (including EVs) respects the grid limits and constraints. Hence, either EVs may be charged in certain periods when the electricity price and/or the power demand are low, or they can supply the grid with electricity when there are heavy electric burdens.

Deployment of Electric Vehicles

EVs can be deployed over the entire network including homes, residential buildings, commercial buildings, institutions, parking lots, charging stations and many others. Consequently, each type of these places has its own strategy to control the charging process of its own EVs and electric loads. Ancillary services are not exclusive only for EV parking lots or EV charging stations, but also individual users such as in homes and residential buildings can participate in supporting the grid and reduce the congestion in an efficient manner. To attain this objective, many complex control strategies were developed to coordinate the charging of a fleet of EVs in a parking lot. The main goal was to satisfy both EV owners (by respecting their energy needs) and the distribution system operator (by respecting the network limits). These complex algorithms increase the penetration level of EVs without affecting negatively the distribution system.

To implement the control strategies, the scheduling and the optimization of EVs should be associated with demand response and incentive programs. The electricity retailer (or distribution system operator, or power utility) can benefit from the programs to incite the end-users to schedule their loads. On the one hand, end-users reduce their electricity bill; therefore, their satisfaction is increased. On the other hand, operators will reduce the congestion on the network, which will increase their revenue and protect the system from excess of power and voltage deviation.

Benefits of Controlling and Optimizing the Charging of EVs

The advantages for the operators are numerous including, but not limited to:

  • Reduce the peak demand and protect transformers and cables from overheating and reduce in their lifetime
  • Shift the loads to off-peak time, when the demand is low
  • Increase the efficiency and the reliability of the network
  • Increase the utilization factor of the network
  • Reduce the power and energy losses on the network
  • Increase the revenue of the system operator and the electricity retailer
  • Maintain the voltage and the frequency within the recommended limits
  • No additional generators are turned on to supply the excess of power. Therefore, the operating cost is reduced
  • Protection systems such as relays and fuses will not be activated, which will guarantee a good functioning of the system and a continuation in the power supply
  • Reduce the risk of a power outage
  • Smart charging maximize the penetration level of EVs without exceeding the grid constraints

Current Situation and Barriers

Currently, conventional distribution network is still used in many countries and regions, which is based on a unidirectional power flow from the power generator to the end-users. Thus, it will not be suitable for a high penetration level of bidirectional elements such as EVs; renewable energy sources (RES), and distributed generations (DGs). Therefore, supplying power to the grid (which is not equipped with bidirectional elements such as protective devices and transformers) may induce problems and an excess of energy can perturb the stability of the grid. For this reason, it is always recommended to shift as soon as possible to a smarter grid, which allows a bidirectional power flow, has a rigorous communication infrastructure to manage and control the electrical loads on the network and fill the gap between the supplied and the consumed energy.


In conclusion, EVs will play a major role in reducing the congestion and managing the power flow in future smart grids. Thus, it is better to shift to this new emerging technology early and to find solutions for their integration in order to avoid their negative impacts on the network. Consequently, if the EVs and RES are widely deployed, their integration should be associated with intelligent algorithms and infrastructure to guarantee a sustainable smart grid.

For a downloadable copy of the March 2019 eNewsletterwhich includes this article, please visit the IEEE Smart Grid Resource Center  
Claude Ziad El-Bayeh

Claude Ziad El-Bayeh (S’16, M’18) received the B.Sc. degree in electrical and electronic engineering from the Lebanese University Faculty of Engineering II, Lebanon, in 2008. M.Sc. degree in Organizational Management from the University of Quebec in Chicoutimi, Canada, in 2012, and the Master of Research degree in Renewable Energy from Saint Joseph University, Beirut, Lebanon, in 2014. He is currently pursuing the Ph.D. degree in Electrical Engineering at the University of Quebec - Engineering School (École de Technologie Supérieure), Montreal, Canada. His research interests include Smart Grid, Energy Management, Renewable Energy, Power and Distribution Systems, Optimization and Operations Research.

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