Demand Side Management of Electric Vehicles in Smart Grids: A survey on strategies, challenges, modeling, and optimization

The shift of transportation technology from internal combustion engine (ICE) based vehicles to electricvehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater efficiency hasbrought EV technology to the forefront of the electric power distribution systems due to theirability to interact with the grid through vehicle-to-grid (V2G) infrastructure. The greater adoptionof EVs presents an ideal use-case scenario of EVs acting as power dispatch, storage, and ancillaryservice-providing units. This EV aspect can be utilized more in the current smart grid (SG) scenarioby incorporating demand-side management (DSM) through EV integration. The integration of EVswith DSM techniques is hurdled with various issues and challenges addressed throughout thisliterature review. The various research conducted on EV-DSM programs has been surveyed. This reviewarticle focuses on the issues, solutions, and challenges, with suggestions on modeling the charginginfrastructure to suit DSM applications, and optimization aspects of EV-DSM are addressed separatelyto enhance the EV-DSM operation. Gaps in current research and possible research directions have beendiscussed extensively to present a comprehensive insight into the current status of DSM programsemployed with EV integration. This extensive review of EV-DSM will facilitate all the researchersto initiate research for superior and efficient energy management and EV scheduling strategies andmitigate the issues faced by system uncertainty modeling, variations, and constraints

Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach

© 2019 Elsevier Ltd As the number of electric vehicles (EVs) is steadily increasing, their aggregation can offer significant storage to improve the electric system operation in many aspects. To this end, a comprehensive stochastic optimization framework is proposed in this paper for the joint operation of a fleet of EVs with a wind power producer (WPP) in a three-settlement pool-based market. An aggregator procures enough energy for the EVs based on their daily driving patterns, and schedules the stored energy to counterbalance WPP fluctuations. Different sources of uncertainty including the market prices and WPP generation are modeled through proper scenarios, and the risk is hedged by adding a risk measure to the formulation. To obtain more accurate results, the battery degradation costs are also included in the problem formulation. A detailed case study is presented based on the Iberian electricity market data as well as the technical information of three different types of EVs. The proposed approach is benchmarked against the disjoint operation of EVs and WPP. Numerical simulations demonstrate that the proposed strategy can effectively benefit EV owners and WPP by reducing the energy costs and increasing the profits

Dispatch of vehicle-to-grid battery storage using an analytic hierarchy process

The number of electric vehicles (EVs) is expected to increase significantly in the future to combat air pollution and reduce reliance on fossil fuels. This will impact on the power system. However, appropriate charging and discharging of EVs through vehicle-to-grid operations could also provide support for the power system and benefits for the EV owners. This raises the questions of when and how EV battery storage should be dispatched, taking into account both vehicle users’ and power system’s requirements and priorities, as well as the constraints of the battery system. This paper proposes a novel decentralized dispatch strategy based on the Analytic Hierarchy Process (AHP) taking into account the relative importance of the different criteria including cost, battery state of charge, power system contingency and load levelling. The proposed AHP-based dispatch strategy was tested on an IEEE Reliability Test System with different EV numbers and capacities to investigate the efficacy of such an approach. The simulation results demonstrate the feasibility and benefits of this dispatch strategy

Integrating plug-in electric vehicles into the electric power system

This dissertation contributes to our understanding of how plug-in hybrid electric vehicles (PHEVs) and plug-in battery-only electric vehicles (EVs)—collectively termed plug-in electric vehicles (PEVs)—could be successfully integrated with the electric power system. The research addresses issues at a diverse range of levels pertaining to light-duty vehicles, which account for the majority of highway vehicle miles traveled, energy consumed by highway travel modes, and carbon dioxide emissions from on-road sources. Specifically, the following topics are investigated: (i) On-board power electronics topologies for bidirectional vehicle-to-grid and grid-to-vehicle power transfer; (ii) The estimation of the electric energy and power consumption by fleets of light-duty PEVs; (iii) An operating framework for the scheduling and dispatch of electric power by PEV aggregators; (iv) The pricing of electricity by PHEV aggregators and how it affects the decision-making process of a cost-conscious PHEV owner; (v) The impacts on distribution systems from PEVs under aggregator control; (vi) The modeling of light-duty PEVs for long-term energy and transportation planning at a national scale

Optimal Management of an Integrated Electric Vehicle Charging Station under Weather Impacts

The focus of this Dissertation is on developing an optimal management of what is called the “Integrated Electric Vehicle Charging Station” (IEVCS) comprising the charging stations for the Plug-in Electric Vehicles (PEVs), renewable (solar) power generation resources, and fixed battery energy storage in the buildings. The reliability and availability of the electricity supply caused by severe weather elements are affecting utility customers with such integrated facilities. The proposed management approach allows such a facility to be coordinated to mitigate the potential impact of weather condition on customers electricity supply, and to provide warnings for the customers and utilities to prepare for the potential electricity supply loss. The risk assessment framework can be used to estimate and mitigate such impacts. With proper control of photovoltaic (PV) generation, PEVs with mobile battery storage and fixed energy storage, customers’ electricity demand could be potentially more flexible, since they can choose to charge the vehicles when the grid load demand is light, and stop charging or even supply energy back to the grid or buildings when the grid load demand is high. The PV generation capacity can be used to charge the PEVs, fixed battery energy storage system (BESS) or supply power to the grid. Such increased demand flexibility can enable the demand response providers with more options to respond to electricity price changes. The charging stations integration and interfacing can be optimized to minimize the operational cost or support several utility applications