Integrating Electric Vehicles into Power System Operation Production Cost Models (original) (raw)
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Modelling Electric Vehicle Charge Demand: Implementation for the Greek Power System
World Electric Vehicle Journal
The emerging popularity of Plug-in Electric Vehicles (PEVs) is creating new connections between the transportation and electric sectors, and PEV charging will bring new opportunities and challenges to a system of growing complexity. The electrification of transport will increase energy security, reduce carbon emissions, and improve local air quality. The actual expansion of electric vehicles (EVs) will depend on several factors: the evolution of autonomy, the acquisition price, the charging process and infrastructure, etc. This paper provides a guide for simulating the accumulative load profile for EV charging on a national level. The importance of all the parameters and variables involved (deterministic or stochastic) is investigated. Detailed tables and references concerning the distribution of values and the composition of the EV fleet are provided. A multivariate probabilistic model is developed considering the EV classes, weekly and seasonal driving patterns, charging strategie...
Power System Impacts of Electric Vehicle Charging Strategies
Electricity
This article explores the potential impacts of integrating electric vehicles (EVs) and variable renewable energy (VRE) on power system operation. EVs and VRE are integrated in a production cost model with a 5 min time resolution and multiple planning horizons to deduce the effects of variable generation and EV charging on system operating costs, EV charging costs, dispatch stacks, reserves and VRE curtailment. EV penetration scenarios of the light-duty vehicle fleet of 10%, 20%, and 30% are considered in the RTS-GMLC test system, and VRE penetration is 34% of annual energy consumption. The impacts of EVs are investigated during the annual peak in the summer and during the four weeks of the year in which high VRE and low loads lead to overgeneration. Uncoordinated and coordinated EV charging scenarios are considered. In the uncoordinated scenario, charging is undertaken at the convenience of the EV owners, modeled using data from the Idaho National Laboratory’s EV Project. Coordinate...
Predicting and Managing EV Charging Demand on Electrical Grids: A Simulation-Based Approach
Energies
Electric vehicles (EVs) are becoming increasingly popular, and it is important for utilities to understand their charging characteristics to accurately estimate the demand on the electrical grid. In this work, we developed simulation models for different EV charging scenarios in the home sector. We used them to predict maximum demand based on the increasing penetration of EV consumers. We comprehensively reviewed the literature on EV charging technologies, battery capacity, charging situations, and the impact of EV loads. Our results suggest a method for visualizing the impact of EV charging loads by considering factors such as state of charge, arrival time, charging duration, rate of charge, maximum charging power, and involvement rate. This method can be used to model load profiles and determine the number of chargers needed to meet EV user demand. We also explored the use of a time-of-use (TOU) tariff as a demand response strategy, which encourages EV owners to charge their vehic...
International Multidisciplinary Research Journal, 2022
Dispatching of generating resources at Power Stations is a complex task based on the balance of economics, contractual agreement, regulations, and environmental consciousness in terms of emissions produced in the course of electricity generation. The complexity of the task could be exacerbated with the integration of a large percentage of Electric Vehicles (EVs) in the quest to reduce CO 2 emissions in the transportation sector. In this paper, a dispatch model, which is suitable for analysing the impacts of charging patterns of EVs on grid emissions intensity and emissions abatement costs, is described and developed for dispatching generating resources/technologies. The dispatch model is based on the correlation between historical system load and capacity factors of generating units. The dispatch model is tested on data from the UK power system on a typical winter day in December 2015 with an assumed 50% integration of EVs on the system. Results show amongst others that charging of EVs in the off-peak period may affect the optimal deployment of generating technologies/resources with storage capacity and could produce a higher average grid emissions intensity.
IEEE Access, 2021
Electric vehicles (EVs) can have massive benefits in energy sector especially for a small island country like the Maldives that imports oil with high transportation costs while power could have been generated from abundantly available local renewable resources. However, EV charging may also impose significant investment requirement for the power system that needs to be analyzed carefully including the capacity of the existing distribution network system, investments needed in solar PV together with battery storage and additional diesel capacity to meet the incremental demand from EVs. We explore an EV adoption scenario for Maldives for 2030 with 30% of all vehicles including two-wheelers that dominate the transport on the island under two different charging regimes: uncoordinated and optimized coordinated mode. The latter is achieved through a system wide optimization using a modified version of the World Bank Electricity Planning Model (EPM) that optimizes charging load subject to a range of constraints on allowable timing for different categories of vehicles. If charging from the fleet is uncoordinated, a relatively small increase in energy requirement of 3.1% due to EV may lead to a 26.1% increase in generation capacity requirement and hence 15.7% additional investment. While the optimized charging regime helps to drastically cut down on generation capacity requirements to just 1.8% increase and also considerably eases feeder loading, it may also lead to higher emissions as more EV load during off-peak hours lead to an increase in diesel-based generation. We have therefore explored an additional scenario wherein the annual emissions from the power sector are constrained to the baseline (''No EV'') scenario. The analysis shows the importance of focused modeling analysis to understand the ramifications of EV load impact on the power system including significant increase in generation capacity and potential increase in power sector emissions in a fossil-fuel dominated system. INDEX TERMS Electric vehicles, power system optimization, least-cost planning, distribution network. I. INTRODUCTION A. CONTEXT
Modelling of large-scale electric vehicles charging demand: A New Zealand case study
Electric Power Systems Research
Due to increasing electric vehicles (EVs) uptakes, power system distribution network will have to accommodate the increased load level for charging EVs. Thus, the importance of a robust power system especially in the distribution network level is indisputable. During the planning or reinforcement stage of distribution networks, it is paramount to have some estimations and analyses done on system-wide EV charging loads that will be placed in the network. Thus, this paper systematically investigates the EV fleet composition, market shares, and charging patterns within New Zealand (NZ) area. A multivariate probabilistic modelling of dependent random variables and cumulative distribution functions is adopted for the accurate estimation of aggregated EV charging demands. Several vehicle travel survey data sets are utilised to quantitatively determine charging behaviours and driving patterns of EVs. The developed methodology based on Monte-Carlo simulation (MCS) is utilised to generate results close to the real use-cases daily power demand, which can be further utilised in the analysis of EV charging strategies. In addition, non-smart and smart EV charging strategies are introduced to mitigate impacts of the large-scale EV deployment and to guarantee the charging completion for each EV.
This paper aims to develop a management method considering load demand for electric vehicle charging. The method developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes have proposed to determine optimal demand shifting so that charging costs and demands can possibly be managed. The time of use electricity rate has been put into practice to change the tendencies of charging time. Nevertheless, since it focuses only minimizing costs of charging from vehicle owners, loads would be concentrated at a certain time and form a new peak load. The purpose of this paper is to suggest a scenario of load leveling. Therefore charging costs and demands can be managed suitably considering the discordance between electrical prices and system load fluctuations. In case study results, charging patterns and daily demands in the areas are investigated. And optimum solutions are conducted regarding costs and operation aspects by determining demand distribution proportions.
Grid Load Contributions Through Electric Vehicles and Their Uncertainties
Zeitschrift für Energiewirtschaft, 2017
With the numbers of electric vehicles on the increase, their additional electricity demand can no longer be neglected. From a power systems' perspective, it is the time dependent electricity consumption that matters. In particular, the peak demand is increased in the case of uncontrolled charging, imposing additional stress on the system. Unfortunately, since there is an absence of representative electric vehicle driving patterns, a quantification of such temporal charging requirements is challenging. To overcome this problem, we developed a detailed model, which maps combustion engine vehicles onto electric vehicle equivalents. The model's main strengths are the consideration of the diversity within the vehicle fleet as well as the differentiation into the boundary cases of pure battery electric vehicles and plug-in hybrid electric vehicles. Applied to a German traffic study, load curves for these two cases were generated. In addition, the existing uncertainty in between was quantified using Monte Carlo method. We show that the peak energy demand through electric vehicles is much greater on working days than on weekend days. Moreover, we find that the distinction between pure and plug-in-hybrid electric vehicles matters, at least for the time being. Apart from the numerical results, the model is well suited to generate input for more sophisticated investigations of charging strategies within energy system simulations.
Analysis of EV Cost-Based Charging Load Profiles
Proceedings, 2020
During the last few decades, electric vehicles (EVs) have emerged as a promising sustainable alternative to traditional fuel cars. The work presented here is carried out in the context of the Horizon 2020 project MERLON and targets the impact of EVs on electrical grid load profiles, while considering both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operation modes. Three different charging policies are considered: the uncontrolled charging, which acts as a reference scenario, and two strategies that fall under the umbrella of individual charging policies based on price incentive strategies. Electricity prices along with the EV user preferences are taken into account for both charging (G2V) and discharging (V2G) operations, allowing for more realistic scenarios to be considered.
Modelling the Impacts of Large-Scale Penetration of Electric Vehicle on Electricity Networks
Electric vehicles (EVs) offer several significant potential economic, social and environmental benefits -reductions in the transport sector's current very heavy reliance on petroleum-based fuels, improvements in urban air quality and reductions in transport sector greenhouse gas emissions. The batteries of electric vehicles, however, need to be recharged and electrification of transport systems will increase electricity loads, which could potentially place stress on some electricity distribution systems. The actual impacts of EV recharging on local distribution systems will depend on a number of factors and on the timing of the recharging events in particular. The results of the several studies have attempted to assess the potential impacts that EV recharging will have on local distribution networks suggest that coordinated managed charging of EV demand could actually have a significantly positive impact on distribution system reliability.