Integration of Massive Plug-in Hybrid Electric Vehicles into Power Distribution Systems: Modeling, Optimization, and Impact Analysis

With the development of vehicle-to-grid (V2G) technology, it is highly promising to use plug-in hybrid electric vehicles (PHEVs) as a new form of distributed energy resources. However, the uncertainties in the power market and the conflicts among different stakeholders make the integration of PHEVs a highly challenging task. Moreover, the integration of PHEVs may lead to negative effects on the power grid performance if the PHEV fleets are not properly managed. This dissertation studies various aspects of the integration of PHEVs into power distribution systems, including the PHEV load demand modeling, smart charging algorithms, frequency regulation, reliability-differentiated service, charging navigation, and adequacy assessment of power distribution systems. This dissertation presents a comprehensive methodology for modeling the load demand of PHEVs. Based on this stochastic model of PHEV, a two-layer evolution strategy particle swarm optimization (ESPSO) algorithm is proposed to integrate PHEVs into a residential distribution grid. This dissertation also develops an innovative load frequency control system, and proposes a hierarchical game framework for PHEVs to optimize their charging process and participate in frequency regulation simultaneously. The potential of using PHEVs to enable reliability-differentiated service in residential distribution grids has been investigated in this dissertation. Further, an integrated electric vehicle (EV) charging navigation framework has been proposed in this dissertation which takes into consideration the impacts from both the power system and transportation system. Finally, this dissertation proposes a comprehensive framework for adequacy evaluation of power distribution networks with PHEVs penetration. This dissertation provides innovative, viable business models for enabling the integration of massive PHEVs into the power grid. It helps evolve the current power grid into a more reliable and efficient system

Control Strategies for Smart Charging and Discharging of Plug- In Electric Vehicles

This chapter aims to provide an overview of the plug-in electric vehicle (PEV) charging and discharging strategies in the electric power system and the smart cities, as well as an application benefiting both consumers and power utility. The electric vehicle technology will be introduced. Then, the main impacts, benefits and challenges related to this technology will be discussed. Following, the role of the vehicles in smart cities will be presented. Next, the major methods and strategies for charging and discharging of plug-in electric vehicles available in the literature will be described. Finally, a new strategy for the intelligent charging and discharging of electric vehicles will be presented, which aims to benefit the consumer and the power utility

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits

Estimating the grid payments necessary to compensate additional costs to prospective electric vehicle owners who provide vehicle-to-grid ancillary services

The provision of ancillary services in the smart grid by electric vehicles is attractive to grid operators. Vehicles must be aggregated to meet the minimum power requirements of providing ancillary services to the grid. Likely aggregator revenues are insufficient to cover the additional battery degradation costs which would be borne by an existing electric vehicle owner. Moreover, aggregator revenues are insufficient to make electric vehicles competitive with conventional vehicles and encourage uptake by prospective consumers. Net annual costs and hourly compensation payments to electric vehicle owners were most sensitive to battery cost. The fleet provided firm fast reserve from 1900 h for 0.42 h, up to 2.7 h in the best cases. At best, likely aggregator revenue was 20 times less than the compensation required, up to 27,500 times at worst. The electric vehicle fleet may not be large enough to meet the firm fast reserve power and duration requirements until 2020. However, it may not be until 2030 that enough vehicles have been sold to provide this service cost-effectively. Even then, many more electric vehicles will be needed to meet the power level and duration requirements, both more often and for longer to enable participation in an all-day, everyday ancillary services market.The authors acknowledge the funding provided for this work by the Oxford Martin School

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

A Comprehensive Assessment of Vehicle-to-Grid Systems and Their Impact to the Sustainability of Current Energy and Water Nexus

This dissertation aims to explore the feasibility of incorporating electric vehicles into the electric power grid and develop a comprehensive assessment framework to predict and evaluate the life cycle environmental, economic and social impact of the integration of Vehicle-to-Grid systems and the transportation-water-energy nexus. Based on the fact that electric vehicles of different classes have been widely adopted by both fleet operators and individual car owners, the following questions are investigated: 1. Will the life cycle environmental impacts due to vehicle operation be reduced? 2. Will the implementation of Vehicle-to-Grid systems bring environmental and economic benefits? 3. Will there be any form of air emission impact if large amounts of electric vehicles are adopted in a short time? 4. What is the role of the Vehicle-to-Grid system in the transportation-water-energy nexus? To answer these questions: First, the life cycle environmental impacts of medium-duty trucks in commercial delivery fleets are analyzed. Second, the operation mechanism of Vehicle-to-Grid technologies in association with charging and discharging of electric vehicles is researched. Third, the feasible Vehicle-to-Grid system is further studied taking into consideration the spatial and temporal variance as well as other uncertainties within the system. Then, a comparison of greenhouse gas emission mitigation of the Vehicle-to-Grid system and the additional emissions caused by electric vehicle charging through marginal electricity is analyzed. Finally, the impact of the Vehicle-to-Grid system in the transportation-water-energy nexus, and the underlying environmental, economic and social relationships are simulated through system dynamic modeling. The results provide holistic evaluations and spatial and temporal projections of electric vehicles, Vehicle-to-Grid systems, wind power integration, and the transportation-water-energy nexus

State-of-the-Art Assessment of Smart Charging and Vehicle 2 Grid services

Electro-mobility – especially when coupled smartly with a decarbonised grid and also renewable distributed local energy generation, has an imperative role to play in reducing CO2 emissions and mitigating the effects of climate change. In parallel, the regulatory framework continues to set new and challenging targets for greenhouse gas emissions and urban air pollution. • EVs can help to achieve environmental targets because they are beneficial in terms of reduced GHG emissions although the magnitude of emission reduction really depends on the carbon intensity of the national energy mix, zero air pollution, reduced noise, higher energy efficiency and capable of integration with the electric grid, as discussed in Chapter 1. • Scenarios to limit global warming have been developed based on the Paris Agreement on Climate Change, and these set the EV deployment targets or ambitions mentioned in Chapter 2. • Currently there is a considerable surge in electric cars purchasing with countries such as China, the USA, Norway, The Netherlands, France, the UK and Sweden leading the way with an EV market share over 1%. • To enable the achievement of these targets, charging infrastructures need to be deployed in parallel: there are four modes according to IEC 61851, as presented in Chapter 2.1.4. • The targets for SEEV4City project are as follow: o Increase energy autonomy in SEEV4-City sites by 25%, as compared to the baseline case. o Reduce greenhouse gas emissions by 150 Tonnes annually and change to zero emission kilometres in the SEEV4-City Operational Pilots. o Avoid grid related investments (100 million Euros in 10 years) by introducing large scale adoption of smart charging and storage services and make existing electrical grids compatible with an increase in electro mobility and local renewable energy production. • The afore-mentioned objectives are achieved by applying Smart Charging (SC) and Vehicle to Grid (V2G) technologies within Operational Pilots at different levels: o Household. o Street. o Neighbourhood. o City. • SEEV4City aims to develop the concept of 'Vehicle4Energy Services' into a number of sustainable business models to integrate electric vehicles and renewable energy within a Sustainable Urban Mobility and Energy Plan (SUMEP), as introduced in Chapter 1. With this aim in mind, this project fills the gaps left by previous or currently running projects, as reviewed in Chapter 6. • The business models will be developed according to the boundaries of the six Operational Pilots, which involve a disparate number of stakeholders which will be considered within them. • Within every scale, the relevant project objectives need to be satisfied and a study is made on the Public, Social and Private Economics of Smart Charging and V2G. • In order to accomplish this work, a variety of aspects need to be investigated: o Chapter 3 provides details about revenue streams and costs for business models and Economics of Smart Charging and V2G. o Chapter 4 focuses on the definition of Energy Autonomy, the variables and the economy behind it; o Chapter 5 talks about the impacts of EV charging on the grid, how to mitigate them and offers solutions to defer grid investments; o Chapter 7 introduces a number of relevant business models and considers the Economics of Smart Charging and V2G; o Chapter 8 discusses policy frameworks, and gives insight into CO2 emissions and air pollution; o Chapter 9 defines the Data Collection approach that will be interfaced with the models; o Chapter 10 discusses the Energy model and the simulation platforms that may be used for project implementation