Impact of demand response management on chargeability of electric vehicles

AbstractLarge-scale penetration of electric vehicles (EVs) would significantly increase the load requirements of buildings in highly urbanized cities. EVs exhibit higher degree of charging flexibility when compared to other interruptible loads in buildings. Hence, EVs can be assigned lower priority and interrupted before interrupting any other loads. Any temporary interruption will have minimum impact on EV owner's satisfaction/comfort. However, it should be ensured that the EVs could be charged to the owner's required state of charge (SOC) by the time of departure. The scheduling algorithms that are used to manage the EV charging process ensure that the charging requirements are fulfilled even when there are temporary interruptions. The capability of the scheduling algorithms to manage mismatches decreases with the decrease in time available for charging. In this paper, the impact of demand response management (DRM) on the chargeability of the EVs while using different priority criteria is examined. Subsequently, the proportion of interruption for each EV with different priority criteria and the need for determining the chargeability of EVs before shedding them are studied. A scheduling driven algorithm is proposed which can be used for determining the chargeability of EVs and can be used in combination with DRM

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

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

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

EV specific time-of-use rates analysis for workplace charging.

EV specific time-of-use rate plans have been recently introduced by several utilities to overcome the demand charge issue that is the main barrier impeding EV growth in the commercial and industrial sector. This study analyses two EV specific TOU rates in place from a customer and the grid perspectives. The analysis relies on a developed optimal cost model with coordinated charging strategies that minimizes the total cost of a workplace charging station over its lifetime. From a customer perspective, it is shown that the cost benefits are not always achievable and depends on the rates provided. From the grid perspective, the peak demand is found to be increased. Thus, the EV specific rates may not always provide an efficient use of the grid assets

Online Coordinated Charging of Plug-In Electric Vehicles in Smart Grid to Minimize Cost of Generating Energy and Improve Voltage Profile

This Ph.D. research highlights the negative impacts of random vehicle charging on power grid and proposes four practical PEV coordinated charging strategies that reduce network and generation costs by integrating renewable energy resources and real-time pricing while considering utility constraints and consumer concerns

Batteries charging systems for electric and plug-in hybrid electric vehicles

Many countries have a large dependence on imported fossil fuels whose prices increase almost every day. Knowing that much of this consumption is for transportation systems, it becomes essential to seek for alternatives. The natural bet is the electric mobility, namely through Electric Vehicles (EVs) and Plug-in Hybrid Electric Vehicles (PHEVs). However, the wide spread utilization of these vehicles has consequences on the electrical power grid, mainly in terms of load management and electric power quality, which are associated to the batteries charging systems. In this scenario, this chapter assesses the electric mobility integration in Smart Grid context, focusing different approaches to the operation of EVs and PHEVs charging processes and the specifications of the chargers, as well as different topologies of charging systems and their features, modes of operation, typical waveforms, and impact in the electrical power grid in terms of power quality. It is also presented a laboratory prototype of a bidirectional EV charger and shown some experimental results. This prototype was developed to charge the batteries aiming to preserve their lifespan, and to contribute to mitigate the degradation of the power quality. The experimental results show the operation of this prototype during the batteries charging process (G2V – Grid-to-Vehicle operation), and during the delivering of stored energy back to the electrical power grid (V2G – Vehicle-to-Grid operation).FEDER Funds - Operational Program for Competitiveness Factors – COMPETEFundação para a Ciência e a Tecnologia (FCT) - FCOMP-01-0124-FEDER-022674, MITPT/ EDAM-SMS/0030/200

Accommodating a High Penetration of Plug-in Electric Vehicles in Distribution Networks

The last few decades have seen growing concern about climate change caused by global warming, and it now seems that the very future of humanity depends on saving the environment. With recognition of CO2 emissions as the primary cause of global warming, their reduction has become critically important. An effective method of achieving this goal is to focus on the sectors that represent the greatest contribution to these emissions: electricity generation and transportation. For these reasons, the goal of the work presented in this thesis was to address the challenges associated with the accommodation of a high penetration of plug-in electric vehicles (PEVs) in combination with renewable energy sources. Every utility must consider how to manage the challenges created by PEVs. The current structure of distribution systems is capable of accommodating low PEV penetration; however, high penetration (20 % to 60 %) is expected over the next decades due to the accelerated growth in both the PEV market and emission reduction plans. The energy consumed by such a high penetration of PEVs is expected to add considerable loading on distribution networks, with consequences such as thermal overloading, higher losses, and equipment degradation. A further consideration is that renewable energy resources, which are neither exhaustible nor polluting, currently offer the only clean-energy option and should thus be utilized in place of conventional sources in order to supply the additional transportation-related demand. Otherwise, PEV technology would merely transfer emissions from the transportation sector to the electricity generation sector. As a means of facilitating the accommodation of high PEV penetration, this thesis proposes methodologies focused on two main themes: uncontrolled and coordinated charging. For uncontrolled charging, which represents current grid conditions, the proposal is to utilize dispatchable and renewable distributed generation (DG) units to address the high PEV penetration in a way that would not be counterproductive. This objective is achieved through three main steps. First, the benefits of allocating renewable DG in distribution systems are investigated, with different methodologies developed for their evaluation. The benefits are defined as the deferral of system upgrade investments, the reduction in the energy losses, and the reliability improvement. The research also includes a proposal for applying the developed methodologies for an assessment of the benefits of renewable DG in a planning approach for the optimal allocation of the DG units. The second step involves the development of a novel probabilistic energy consumption model for uncontrolled PEV charging, which includes consideration of the drivers’ behaviors and ambient temperature effect associated with vehicle usage. The final step integrates the approaches and models developed in the previous two steps, where a long-term dynamic planning approach is developed for the optimal allocation of renewable and dispatchable DG units in order to accommodate the rising penetration of PEV uncontrolled charging. The proposed planning approach is multi-objective and includes consideration of system emissions and costs. The second theme addressed in this thesis is coordinated PEV charging, which is dependent on the ongoing development of a smart grid communication infrastructure, in which vehicle-grid communication is feasible via appropriate communication pathways. This part of the work led to the development of a proposed coordinated charging architecture that can efficiently improve the performance of the real-time coordinating PEV charging in the smart grid. The architecture is comprised of two novel units: a prediction unit and an optimization unit. The prediction unit provides an accurate forecast of future PEV power demand, and the optimization unit generates optimal coordinated charging/discharging decisions that maximize service reliability, minimize operating costs, and satisfy system constraints

A fast and efficient coordinated vehicle-to-grid discharging control scheme for peak shaving in power distribution system.

This study focuses on the potential role of plug-in electric vehicles (PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid (V2G) power and currently available information transfer technology enables utility companies to use this stored energy. The V2G process is first formulated as an optimal control problem. Then, a two-stage V2G discharging control scheme is proposed. In the first stage, a desired level for peak shaving and duration for V2G service are determined off-line based on forecasted loading profile and PEV mobility model. In the second stage, the discharging rates of PEVs are dynamically adjusted in real time by considering the actual grid load and the characteristics of PEVs connected to the grid. The optimal and proposed V2G algorithms are tested using a real residential distribution transformer and PEV mobility data collected from field with different battery and charger ratings for heuristic user case scenarios. The peak shaving performance is assessed in terms of peak shaving index and peak load reduction. Proposed solution is shown to be competitive with the optimal solution while avoiding high computational loads. The impact of the V2G management strategy on the system loading at night is also analyzed by implementing an off-line charging scheduling algorithm

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