Impact Of Plug-in Electric Vehicles Research Articles

Modelling probabilistic transmission expansion planning in the presence of plug‐in electric vehicles uncertainty by multi‐state Markov model

Increasing penetration of plug-in electric vehicles (PEVs) in the power system makes a need to consider the impact of PEVs on the transmission expansion planning (TEP) studies especially for large-scale PEV parking lots. Modelling of PEVs (as vehicle to grid (V2G)) is highly dependent on the owner's behaviour. In this study, a systematic method based on multi-state Markov model is utilised to represent the uncertainty of V2G's presence. To investigate the impact of PEVs, a probabilistic TEP in the presence of V2Gs (P_TEPV2G) is proposed. In the proposed TEP model, the objective function consists of the total line and risk costs (RCs). Moreover, the optimal place and capacity of PEV parking lots are considered as the decision variables. It is assumed that there is an electric vehicle fleet operator for the management of electric vehicles. Because P_TEPV2G is a complex and non-linear optimisation problem, an improved cuckoo search algorithm (ICS) is utilised to effectively solve the problem. On the IEEE 24-bus system, simulation results show that the availability of the PEVs at the proper bus leads to decreasing RC and deferring construction of new transmission lines.

An Investigation of Plug-In Electric Vehicle Charging Impact on Power Systems Scheduling and Energy Costs

This paper investigates the impact of plug-in electric vehicle (EV) integration on the power systems scheduling and energy cost. An intermediary entity, the EV aggregator, participates in the market on behalf of the EV owners by optimally self-scheduling under the price-taking approach. Through detailed rolling simulations for a year and different EVs' penetration scenarios at a large insular power system, this work highlights the different impact of direct and smart charging on power system scheduling and energy costs, the limitations of the price-taking approach, which is widely used in self-scheduling models, and the difference in system value and market value that smart charging adoption creates in restructured markets under the marginal pricing rule.

Impact of plug-in electric vehicles on voltage unbalance in distribution systems

Plug-in electric vehicle (PEV) will soon be connected to residential distribution networks. They are considered as huge residential loads when being charged. However, as the battery technology and required facilities improves, they will also be able to support the network as small dispersed generation units which transfer the energy stored in their battery into grid. Even though the PEV connection gradually increases, their connection points and charging/discharging levels randomly vary. Therefore, such single-phase bi-directional power flow can have adverse effect on the voltage unbalance of a three-phase distribution network. In this work, impact of plug-in electric vehicles on voltage imbalance in distribution system is presented. In G2V as well as V2G modes, the voltage unbalance analysis is carried out for various cases. Additionally, the voltage unbalance due to PEVs discharging and other types of distribution generator such as solar photovoltaic and wind turbines are investigated. Finally, some voltage unbalance mitigation techniques are summarized.Keywords: Distribution Network, Electric Vehicle, G2V, V2G, Voltage Unbalance

Impacts of plug-in electric vehicles in a balancing area

High contributions of the electricity generation and transportation sectors to criteria pollutant and greenhouse gas emissions have resulted in an increased interest and shift towards low to non-carbon generation options such as renewable wind and solar, and alternative transportation options including plug-in electric vehicles. Since plug-in electric vehicles transfer the tailpipe emissions to the electric grid, it is important to study the interaction between the two sectors. In this paper, a previously developed spatially and temporally resolved unit commitment model is used to determine the dispatch schedule of resources with and without battery electric vehicles for 2050 in a fictitious balancing area located within the South Coast Air Basin of California. Cases studied include various charging profiles, penetration in light-duty fleet, imports mix, and grid dispatch strategies. Results of the analysis include average cost of electricity production, market clearing price, temporal production of individual generators, and emissions from electricity generation and the transportation sectors.The results show that deploying battery electric vehicles (1) has little impact on the average cost of electricity generation-maximum of $2.5 per MWh for the cases studied with 40% penetration in the light-duty fleet, (2) reduces the overall criteria pollutant emissions except for one case, and (3) results in a smoother load profile, reduces the use of peaking units, and reduces the average emission intensity of the grid through controlled off-peak charging.

Modeling and Impacts of Plug-in Electric Vehicles in Residential Distribution Systems with Coordinated Charging Schemes

This paper proposes a modeling methodology for implementation of a charging infrastructure of Plug-in Electric Vehicles (PEVs) within residential distribution systems. Using the feeder daily models, driving patterns, PEVs penetration and charging characteristics, the impact of their connection in the Power Distribution Network (PDN) is determined. In doing so, the number and distribution of PEVs in a residential distribution network are applied to the IEEE 13-node test feeder. Then, coordinated charging of the PEVs is proposed in order to minimize overloading and under-voltage events in the network, and also to perform peak load shaving through the means of load shifting, by delaying the start charging time of PEVs to off peak hours. Finally, impacts such as change in feeder demand curves, voltage deviation, overloading elements, electrical losses, and voltage unbalance, are addressed; taking into account the coordinated charging schemes proposed.

Economic assessment of phase reconfiguration to mitigate the unbalance due to plug-in electric vehicles charging

This paper investigates the economic feasibility of a phase reconfiguration approach to mitigate the unbalance impact of plug-in electric vehicles using split-phase Level 1 charging on the secondary distribution system. The impact resulting from plug-in battery electric vehicles charging as single-phase loads in terms of reliability and power quality are quantified using a Monte Carlo Simulation. The cost-effectiveness of introducing phase reconfiguration in the secondary system is evaluated after mathematically formulating the phase reconfiguration as an optimization problem. The results have shown that the application of phase reconfiguration may result in a significant reduction in unbalance experienced by the system due to high penetration of plug-in battery electric vehicles taking into consideration the time of use pricing.

Distribution planning with hourly profiles for analysing electric vehicle charging strategies

This paper analyses the impact of plug-in electric vehicles (PEVs) on distribution networks. The reference network model (RNM) is used to model the grids and to carry out sensitivity analysis for several scenarios. The set of scenarios selected includes PEV penetration levels, charging strategies and location distributions. Each scenario is characterised in terms of the number of electric vehicles, the vehicles' class, technical parameters and charging time. Five large-scale real distribution networks are modelled and analysed. The topologies selected are intended to be representative of some typical European distribution networks. Results show that the charging strategies are critical. At least, new multi-tariff schemes should be established to encourage charging at valley hours. Depending on the PEV location distribution, smart charging may also be necessary to reduce the distribution network costs further.

Probabilistic Impact of Transportation Electrification on the Loss-of-Life of Distribution Transformers in the Presence of Rooftop Solar Photovoltaic

In this paper, the impact of plug-in electric vehicle (PEV) charging on distribution transformer overload and loss-of-life (LOL) in the presence of rooftop solar photovoltaic (PV) is probabilistically quantified. The Monte Carlo (MC) method is used to address the uncertainties resulting from solar irradiance and temperature in case of solar PV and also to emulate the probabilistic aspect of PEV charging. Twenty scenarios of different penetration levels of solar PVs and PEVs are considered in this work. The results have shown significant reduction in percentage LOL due to solar PV contribution in the case of all-electric (AE) residential dwellings and hence the transformer replacement may be deferred by nearly 4 years, while it has a minor effect in the case of residential dwellings with gas heat and electric water heaters (WWH).

Investigate the Impacts of PEV Charging Facilities on Integrated Electric Distribution System and Electrified Transportation System

Nowadays, plug-in electric vehicles (PEVs) are becoming one of the most promising solutions for consumers due to its economical and environmentally friendly characteristics. An ever-increasing number of PEVs have been radically changing the traditional view of the power industry, transportation industry, and business world. Research on grid integration of PEVs typically addresses topics at the vehicle-grid boundary, such as peak load impacts and charging control. While researchers around the world are making significant advances in these areas, there is little work addressing the coupled effects of PEV charging with the mobility-focused, transportation ecosystem to meet the dynamic needs of a changing society. In this paper, we propose a systematic co-modeling and simulation framework to investigate the impacts of PEV charging facilities on the electric distribution system and transportation system. Moreover, we explore the possibilities to improve the system’s stability and the efficiency of the integrated electrified transportation systems by taking advantage of a variety of charging control strategies. The case studies focus on the PEV charging facilities in a relatively small portion of electric power system and transportation system, especially in metropolitan areas. However, the ideas contained here will apply to more generally coupled, and large-scale electrified transportation systems.

Analysis for Evaluating the Impact of PEVs on New-Town Distribution System in Korea

This paper analyzes the impact of Plug-in Electric vehicles(PEVs) on power demand and voltage change when PEVs are connected to the domestic distribution system. Specifically, it assesses PEVs charging load by charging method in accordance with PEVs penetration scenarios, its percentage of total load, and voltage range under load conditions. Concretely, we develop EMTDC modelling to perform a voltage distribution analysis when the PEVs charging system by their charging scenario was connected to the distribution system under the load condition. Furthermore we present evaluation algorithm to determine whether it is possible to adjust it such that it is in the allowed range by applying ULTC when the voltage change rate by PEVs charging scenario exceed its allowed range. Also, detailed analysis of the impact of PEVs on power distribution system was carried out by calculating existing electric power load and additional PEVs charge load by each scenario on new-town in Korea to estimate total load increases, and also by interpreting the subsequent voltage range for system circuits and demonstrating conditions for countermeasures. It was concluded that total loads including PEVs charging load on new-town distribution system in Korea by PEVs penetration scenario increase significantly, and the voltage range when considering ULTC, is allowable in terms of voltage tolerance range up to a PEVs penetration of 20% by scenario. Finally, we propose the charging capacity of PEVs that can delay the reinforcement of power distribution system while satisfying the permitted voltage change rate conditions when PEVs charging load is connected to the power distribution system by their charging penetration scenario.

Method to Assess the Power-Quality Impact of Plug-in Electric Vehicles

This paper presents a probabilistic harmonic simulation method to study the power-quality impact of electric vehicles (EVs). The proposed method takes into account the random operating characteristics of the vehicles, such as random charging time, charging duration, and vehicle locations. A multiphase model of the primary and secondary systems is used to represent the study system. Extensive case studies have been conducted using the method and the measured EV data. The results reveal that the current versions of plug-in hybrid EVs have no significant harmonic impact on power systems. However, the Level 1 charger can increase the neutral-to-earth voltage at homes which could lead to increased stray voltage incidents.

Analysis of the Impact of Different PEV Battery Chargers during Faults

With a high penetration of Plug-In Electric Vehicles (PEVs) in the electric grid, utilities will have to face the challenges related to them. Considerable research is being done to study and mitigate the impact of PEVs on the electric grid and devise methodologies to utilize them for energy storage and distributed generation. In this paper, the impact of PEVs in a smart car park, placed in an unbalanced distribution system, during a Single Line to Ground fault with auto-recloser operation is studied. Level-2, bidirectional battery chargers with Current Controlled and Voltage Controlled Voltage Source Converters are modeled for the battery charging systems of the PEVs. A smart car park, with 16 vehicles connected to each of the three phases is simulated at one of the buses in the IEEE 13 Bus Test Feeder. The impacts observed during the fault are analyzed and a method to mitigate them is suggested.

Forecasting Plug-In Electric Vehicle Sales and the Diurnal Recharging Load Curve

The expected market penetration of plug-in electric vehicles has drawn much attention to the potential impact on power systems, which to a large extent depends on the number of electric vehicles on the road and the fleet's diurnal recharging load curve. We present two interactive models to jointly forecast plug-in electric vehicle sales and the diurnal recharging load curve in the U.S. between 2012 and 2020. The sales forecasting model is based on information about consumer preferences between hybrid electric vehicles and internal combustion engine vehicles, which can be extracted from historical data. The recharging load forecasting model is based on the assumption that electric vehicle users' recharging behavior will demonstrate a gradual transition from a convenience driven mode in 2012 to a cost driven mode in 2020. A case study is conducted for the Midwest ISO region. Compared to the sales forecasts from the literature, our results turn out to be less optimistic. Our recharging load forecast results also suggest that, if appropriately managed, the impact of plug-in electric vehicles on electricity load would not be overwhelming in the next decade.

Resident Plug-In Electric Vehicle Charging Modeling and Scheduling Mechanism in the Smart Grid

With the development of smart grid and the increase of global resident Plug-In Electric Vehicle (PEV) market in the near future, the interaction between limited distribution grid capacity and uncontrollable PEV charging loads can lead to violations of local grid restrictions. And the proper model charging scheduling mechanism is the key to assess and satisfy various resident charging requirements and help in optimizing utility utilization. In this paper, the distribution grid profile model with PEV charging power is firstly constructed for the purpose of studying resident PEV charging impact on the distribution grid. To better reflect the actual impact of PEVs, we use real data on driving behaviors, vehicle characteristics, and electricity loads to generate our model. Furthermore, an improved queuing-theory-based scheduling mechanism is proposed, the distribution grid communication structure and the algorithm are illustrated, and computer simulations are demonstrated to verify their performance. The results show that the proposed scheduling mechanism will enhance the distribution grid flexibility to meet various charging requirements while maximizing the grid capacity.

Charging Behavior Impacts on Electric Vehicle Miles Traveled

The growing market for plug-in electric vehicles (PEVs) features new models of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) with varying battery sizes and electric driving ranges. How are the various models being used in the real world? A common assumption in PEV impact analysis is that PEV owners will maximize their vehicle's utility by appropriately sizing the battery to their driving needs and by charging their vehicle as much as possible to recover the cost of the vehicle purchase. On the basis of these assumptions, a high correlation between PHEV owner use of the vehicle and the number of plug-in events is expected, and drivers of PHEVs with a small battery are expected to plug in more than do owners of vehicles with a larger battery and similar driving patterns. The assumptions presented are examined through a survey of more than 3,500 PEV owners conducted in California in May and June 2013. The online survey included extensive data on driving and charging behavior using web map questions. Owners of all PEV models on the market, including more than 600 Volts and 800 Prius Plug-Ins, were surveyed. The results show that small-battery PHEV electric vehicle miles traveled are lower than longer-range PHEV or BEV electric vehicle miles traveled not only because of battery size but also because of public charging availability and charging behavior. Higher electric-range PHEV and BEV drivers charge more often and report more charging opportunities in areas where smaller-battery PHEVs could not find chargers.

Estimating the Impact of Electric Vehicle Smart Charging on Distribution Transformer Aging

This paper describes a method for estimating the impact of plug-in electric vehicle (PEV) charging on overhead distribution transformers, based on detailed travel demand data and under several different schemes for mitigating overloads by shifting PEV charging times (smart charging). The paper also presents a new smart charging algorithm that manages PEV charging based on estimated transformer temperatures. We simulated the varied behavior of drivers from the 2009 National Household Transportation Survey, and transformer temperatures based an IEEE standard dynamic thermal model. Results are shown for Monte Carlo simulation of a 25 kVA overhead distribution transformer, with ambient temperature data from hot and cold climate locations, for uncontrolled and several smart-charging scenarios. These results illustrate the substantial impact of ambient temperatures on distribution transformer aging, and indicate that temperature-based smart charging can dramatically reduce both the mean and variance in transformer aging without substantially reducing the frequency with which PEVs obtain a full charge. Finally, the results indicate that simple smart charging schemes, such as delaying charging until after midnight can actually increase, rather than decrease, transformer aging.

Highly-resolved modeling of personal transportation energy consumption in the United States

This paper centers on the estimation of the total primary energy consumption for personal transportation in the United States, to include gasoline and/or electricity consumption, depending on vehicle type. The bottom-up sector-based estimation method introduced here contributes to a computational tool under development at The Ohio State University for assisting decision making in energy policy, pricing, and investment.In order to simulate highly-resolved consumption profiles three main modeling steps are needed: modeling the behavior of drivers, generating realistic driving profiles, and simulating energy consumption of different kinds of vehicles.The modeling proposed allows for evaluating the impact of plug-in electric vehicles on the electric grid – especially at the distribution level. It can serve as a tool to compare different vehicle types and assist policy-makers in estimating their impact on primary energy consumption and the role transportation can play to reduce oil dependency.

Hourly Coordination of Electric Vehicle Operation and Volatile Wind Power Generation in SCUC

In this paper, the coordinated integration of aggregated plug-in electric vehicle (PEV) fleets and renewable energy sources (wind energy) in power systems is studied by stochastic security-constrained unit commitment (Stochastic SCUC) model, which minimizes the expected grid operation cost while considering the random behavior of the many PEVs. PEVs are mobile and distributed devices with deferrable options for the supply/utilization of energy at various times and locations. The increased utilization of PEVs, which consume electricity rather than fossil fuel for driving, offers unique economic and environmental opportunities, and brings out new challenges to electric power system operation and planning. The storage capability of PEVs could help power systems mitigate the variability of renewable energy sources and reduce grid operation costs. Vehicle-to-grid (V2G) enables PEVs to have bi-directional power flows once they are connected to the grid, i.e., they can either inject power to, and draw power from, the grid which adds further complexity to power system operations. PEVs signify customers' random behavior when considering their driving patterns, locational energy requirements, topological grid interconnections, and other constraints imposed by the consumers. Numerical tests demonstrate the effectiveness of the proposed approach for analyzing the impact of PEVs on the grid operation cost and hourly wind energy dispatch.

Will Smart Prices Induce Smart Charging of Electric Vehicles?

The societal and environmental benefits of plug-in electric vehicles (PEVs) have been well documented. However, the near-term impact of PEVs on the distribution grid has yet to be fully explored. Whether PEVs will help or hinder electricity provision will depend on how customers charge their vehicles, which will be driven in part by the rate structures that are offered by utilities and the associated customer response. In this discussion paper, we explore the relationship between PEV charging behavior and varying time-of-use rates, and offer suggestions for conducting a well-designed pricing experiment that will determine whether varying rates will help reduce future grid reliability problems as PEVs penetrate the vehicle market.

Assessment of the Impact of Plug-in Electric Vehicles on Distribution Networks

Plug-in electric vehicles (PEVs) present environmental and energy security advantages versus conventional gasoline vehicles. In the near future, the number of plug-in electric vehicles will likely grow significantly in the world. Despite the aforementioned advantages, the connection of PEV to the power grid poses a series of new challenges for electric utilities. This paper proposes a comprehensive approach for evaluating the impact of different levels of PEV penetration on distribution network investment and incremental energy losses. The proposed approach is based on the use of a large-scale distribution planning model which is used to analyze two real distribution areas. Obtained results show that depending on the charging strategies, investment costs can increase up to 15% of total actual distribution network investment costs, and energy losses can increase up to 40% in off-peak hours for a scenario with 60% of total vehicles being PEV.