Penetration Of Plug-in Hybrid Electric Vehicles Research Articles

Coordinated Charging Scheduling Approach for Plug-In Hybrid Electric Vehicles Considering Multi-Objective Weighting Control in a Large-Scale Future Smart Grid

The growing popularity of plug-in hybrid electric vehicles (PHEVs) is due to their environmental advantages. But uncoordinated charging of a large number of PHEVs can lead to a significant surge in peak loads and higher charging costs for PHEV owners. To end this, this paper introduces an innovative approach to address the issue by proposing a multi-objective weighting control for coordinated charging of PHEVs in a future smart grid, which aims to find an economically optimal solution while also considering load stabilization with large-scale PHEV penetration. Technical constraints related to the owner’s demand and power limitations are considered. In the proposed approach, the charging behavior of PHEV owners is modeled by a normal distribution. It is observed that owners typically start charging their vehicles when they arrive home and stop charging when they go to their workplace. The charging cost is then calculated based on the tiered electricity price and charging power. By adjusting the cost weighting factor and the load stability weighting factor in the multi-objective function, the grid allows for flexible weight selection between the two objectives. This approach effectively encourages owners to actively participate in coordinated charging scheduling, which sets it apart from existing works. The algorithm offers better robustness and adaptability for large-scale PHEV penetration, making it highly relevant for the future smart grid. Finally, numerical simulations are presented to demonstrate the desirable performance of theory and simulation.

Hierarchically Distributed Charge Control of Plug-In Hybrid Electric Vehicles in a Future Smart Grid

Plug-in hybrid electric vehicles (PHEVs) are becoming increasingly widespread due to their environmental benefits. However, PHEV penetration can overload distribution systems and increase operational costs. It is a major challenge to find an economically optimal solution under the condition of flattening load demand for systems. To this end, we formulate this problem as a two-layer optimization problem, and propose a hierarchical algorithm to solve it. For the upper layer, we flatten the load demand curve by using the water-filling principle. For the lower layer, we minimize the total cost for all consumers through a consensus-like iterative method in a distributed manner. Technical constraints caused by consumer demand and power limitations are both taken into account. In addition, a moving horizon approach is used to handle the random arrival of PHEVs and the inaccuracy of the forecast base demand. This paper focuses on distributed solutions under a time-varying switching topology so that all PHEV chargers conduct local computation and merely communicate with their neighbors, which is substantially different from the existing works. The advantages of our algorithm include a reduction in computational burden and high adaptability, which clearly has its own significance for the future smart grid. Finally, we demonstrate the advantages of the proposed algorithm in both theory and simulation.

Demand Side Management for Charging Plug-In Hybrid Electric Vehicles

In future the usage of Plug-in hybrid electric vehicles (PHEV) will be in wide range, which will impose huge burden to the distributive system. The peak load at the distribution system can be controlled by Demand Side Management (DSM) strategy. In the proposed study, the load curve of Low-voltage Transformers (LVTs) is made to be flatten, on satisfying the requirement of charging PHEV at given time to the required level. The proposed problem statement is formulated as convex optimization problem, and then the random arrival of PHEV is handled by introducing the moving horizon strategy. Based on this, the PHEV are being disconnected from the LVTs beyond their respective exit times. Such that the demand curve of the LVTs is flattened. This problem is solved using MATLAB and the power demand curves of the LVTs, power curves of the PHEVs and non- PHEV load are compared over a time of 24 hours to show that the power curve is flattened with the penetration of PHEV.

Environmental sustainability policy on plug-in hybrid electric vehicle penetration utilizing fuzzy TOPSIS and game theory

In this paper, environmental policymaking based on sustainable development was evaluated in Tehran to increase the penetration of plug-in hybrid electric vehicles. First, different aspects of sustainable development, including the environmental, economic, social, and technical aspects of Tehran’s vehicles from 2002 to 2018, were examined through the extended sustainable development model. The model documented the unsustainability of the development of vehicles in Tehran, the main reason for which could be the current air pollution in this city. Following this, based on the principle of sustainable development, some policy indices for the development of plug-in hybrid electric vehicle penetration were introduced and ranked using the fuzzy TOPSIS method, which ranked in the point of view of two players, namely buyers of vehicles and the state. Finally, to find the appropriate policy index, using the game theory method and taking the vehicle buyer and the state as the players, the Nash equilibrium point was defined as an appropriate policy for the development of plug-in hybrid electric vehicles. Thus, using the data obtained, the number of these vehicles for the year 2032 was estimated.

Reliability Evaluation of Composite Power Systems: Evaluating the Impact of Full and Plug-in Hybrid Electric Vehicles

The rising concerns over global climate change and depleting fossil fuel reserves are two of the main reasons for the ongoing efforts towards the electrification of the transportation sector. While greenhouse gases (GHGs) emissions from other sectors are generally falling, emissions from the road transport have increased over the past few decades, with both full electric vehicles (FEVs) and plug-in hybrid electric vehicles (PHEVs) being recognized as potential alternatives to combat climate change and reduce GHG emissions. However, wide-spread integration of FEVs and PHEVs will substantially increase the load on the power system which will eventually affect the reliability of existing power systems. In this paper, a probabilistic model for integrating FEVs and PHEVs with existing power grids is proposed that incorporates important FEV and PHEV characteristics, such as battery capacity, charge depleting distance, and charging rates. In addition, user behavior is taken into account through time of recharging, arrival and departure times, and daily miles driven. Furthermore, different charging strategies, i.e., opportunistic charging and controlled charging with and without vehicle-to-grid (V2G) scheme have been considered to evaluate the impact of FEVs and PHEVs on the composite power system. IEEE-RTS-79 system is used to examine the proposed probabilistic technique considering different FEV and PHEV penetration levels as well as charging strategies. Simulation results show that even a relatively low penetration level of FEVs or PHEVs might have a significant impact on the system reliability unless a proper charging and/or discharging schemes are utilized.

Impact of PHEV in active distribution network under gas station network attack

This paper proposes a novel method to analyze the impacts of plug-in hybrid electric vehicle (PHEV) charging on branch power flows and voltages of an active distribution network under gas station network attack. Specifically, when the gas station network is attacked and cannot provide refueling service, PHEVs running out of gasoline will be only driven in the electric vehicle (EV) mode, which will significantly increase PHEV charging load and lead to branch power flow increment and voltage drop or even voltage collapse in distribution network. To overcome the problem, the switch of PHEV operating mode (i.e., the EV mode and the combustion engine (CE) mode) is first analyzed by considering whether the remaining gasoline can satisfy daily gasoline consumption, and based on that, a novel model of the PHEV charging load is constructed. Then, an integrated approach including Nataf/normalization transformation and elementary transformation (ET) is employed to deal with the general correlation of spatially close distributed generations in the active distribution network. Furthermore, point estimate method (PEM) based probabilistic load flow (PLF) is used to analyze the impacts of PHEV charging on branch power flows and voltages of the active distribution network under gas station network attack. Finally, the proposed method is tested on a real coastal active distribution network, and simulation results verify that PHEV charging could result in continuous branch power flow increase and voltage decrease over a prolonged attack time. Moreover, the higher PHEV operating status (OS) leads to slower branch power flow growth and voltage drop, and a higher PHEV penetration level will exacerbate branch power flow increment and voltage limit violation over with the extension of the attack.

Investigation on distribution transformer loss-of-life due to plug-in hybrid electric vehicles charging

This paper is concerned with the adverse influences of electric vehicles battery charging on the distribution system. This crucial issue is of greater importance when these ever-growing vehicles, plug-in hybrid electric vehicles (PHEVs), get charged as extra electric loads from a standard outlet at home. At first, a comprehensive method is proposed in this study to evaluate the damaging impact of several PHEV penetration levels on the loss of distribution transformers life. Next, the proposed method is applied to a real-life distribution system supplying residential customers. Finally, simulation results via MATLAB reveal that the loss-of-life rate during evening peak is 12.21 for a scenario with 40% penetration of PHEVs. In contrast, night-time coordinated charging of PHEVs causes the least harmful effects on the loss of transformer life.

The impact of PHEVs charging and network topology optimization on bulk power system reliability

Exhausting fossil fuels and increasing environmental pollutions call for the wider deployment of plug-in hybrid electric vehicles (PHEVs), which enable the interactions of transportation and electric sectors. The extra loads for charging massive PHEVs could compromise the power system reliability and impose considerable stress on the power system. Transmission line congestions and generation capacity inadequacy could be caused under this circumstance. However, there is little literature which comprehensively studies the impact of large-scale PHEVs on the bulk power system reliability when smart grid technologies are incorporated including smart charging and flexible transmission topology control technologies. This work studies the impacts of different charging strategies and transmission network operation strategies on the bulk power system reliability with high PHEVs integration. An evolution strategy particle swarm optimization (ESPSO) algorithm is applied to optimize the charging load of PHEVs and shave the peak load. A network topology optimization (NTO) operation strategy is employed to lessen the transmission congestions and reduce the load curtailment. Based on the sequential Monte Carlo simulation method, these technologies are integrated into the reliability evaluation process. Numerical studies and sensitivity analysis are conducted on modified IEEE RTS-79 systems. The results verify the effectiveness of the technologies to realize the potential of existing power system infrastructures so as to relieve the stress caused by the PHEVs load, increase the available penetration of PHEVs and promote the bulk power system reliability which is meaningful for power system planning and risk management.

Exploiting PHEV to Augment Power System Reliability

Environmental concerns with gasoline vehicles have led to increased attention to electric vehicles in recent years. Plug-in hybrid electric vehicles (PHEV) use both electricity and gasoline to propel the vehicle, and is being recognized as a potential alternative to conventional vehicles. PHEVs offer opportunity to use electric energy generated by renewable resources and significantly reduce greenhouse gas emissions. The electric energy requirement of PHEV can, however, cause negative impacts on the power system reliability, especially when the size of a PHEV fleet is relatively large. This paper presents the development of a probabilistic model considering the driving distance, charging times, charging locations, battery state of charge, and charging requirements of a PHEV. A methodology using hybrid analytical and Monte Carlo simulation approach is presented to evaluate the reliability of a power system integrated with PHEVs, considering the important PHEV characteristics, charging scenarios, and power system parameters. Studies are presented on the IEEE-reliability test system to illustrate the impact of PHEV penetration in a power system. Based on the study results, the methods of augmenting system reliability through controlled PHEV charging are presented in this paper.

Introduction of plug-in hybrid electric vehicles in an isolated island system

ABSTRACTThis paper considers the case of São Miguel in the Azores archipelago as a typical example of an isolated island with high renewable energy potential, but largely dependent on fossil fuels incurring high import costs, in order to assess and analyse the potential impact of the plug-in hybrid electric vehicle (PHEV) technology on the local power supply system. To this end, the present work employs The Integrated MARKAL-EFOM System (TIMES) to examine a number of scenarios with different levels of PHEVs penetration under the grid-to-vehicle (G2V) approach, taking into account the established Government policies, regarding the increase in renewable energy production quotas, for the evolution of demand and supply over time. The results obtained indicate that the PHEVs integration into the local grid system under the G2V energy transferring paradigm can be realized without immediate technical barriers and bears the potential to yield significant benefits to the energy mix, reducing thus the environmental impact.

Determining the size of PHEV charging stations powered by commercial grid-integrated PV systems considering reactive power support

Due to low electricity rates at nighttime, home charging for electric vehicles (EVs) is conventionally favored. However, the recent tendency in support of daytime workplace charging that absorbs energy produced by solar photovoltaic (PV) panels appears to be the most promising solution to facilitating higher PV and EV penetration in the power grid. This paper studies optimal sizing of workplace charging stations considering probabilistic reactive power support for plug-in hybrid electric vehicles (PHEVs), which are powered by PV units in medium voltage (MV) commercial networks. In this study, analytical expressions are first presented to estimate the size of charging stations integrated with PV units with an objective of minimizing energy losses. These stations are capable of providing reactive power support to the main grid in addition to charging PHEVs while considering the probability of PV generation. The study is further extended to investigate the impact of time-varying voltage-dependent charging load models on PV penetration. The simulation results obtained on an 18-bus test distribution system show that various charging load models can produce dissimilar levels of PHEV and PV penetration. Particularly, the maximum energy loss and peak load reductions are achieved at 70.17% and 42.95% respectively for the mixed charging load model, where the system accommodates respective PHEV and PV penetration levels of 9.51% and 50%. The results of probabilistic voltage distributions are also thoroughly reported in the paper.

Energy Saving and CO2 Mitigation of Electric Vehicle (EV) Technology in Lao Transport Sector

The high increase in number of vehicles in Lao transport sector in the medium and long-term happens due to continuous growth in transport service demand, which in turn will increase energy consumption in the transport sector. Electric vehicle (EV) technologies can inhibit increment in energy demand growth and energy-related CO 2 emissions in the transport sector; however, cost remains a barrier for the technology diffusion. In this study, a stock vehicle turnover model of the passenger vehicles was developed to assess the potential of EV technology employment for energy saving and CO 2 mitigation in the case of Lao PDR. Three vehicle technologies of EV were chosen to develop countermeasure scenarios. They were the battery electric vehicles (BEVs), hybrid electric vehicles (HEVs), and plug-in hybrid electric vehicles (PHEVs). The Long-rang Energy Alternative Planning (LEAP) model was used to forecast sector-wise transport demand until 2050, considering the base year as 2010. Altogether three scenarios were developed namely, the business as usual (BAU) scenario that relies on conventional internal combustion engine vehicles (ICEVs), and two alternative scenarios, namely CM-R and CM-I scenarios, targeting the penetration of (i) BEVs, (ii) HEVs, and (iii) PHEVs. In addition to the analysis of emission mitigation and energy system impacts, co-benefits of CO 2 mitigation are also investigated in terms of emissions of local air pollutants under modelled scenarios. Results show that in the BAU scenario, energy consumption in the transport sector will increase from 548 ktoe in 2010 to 2,823 ktoe in 2050 while CO 2 emission will increase from 1,656 kt-CO 2 in 2010 to 8,511 kt-CO 2 in 2050. However, in countermeasure scenarios, the high penetration of EV technologies will result in reduction of CO 2 emissions when compared with the BAU scenario. In co-benefit analysis, reduction in emissions of other air pollutants was also observed.

Optimal power allocation scheme for plug-in hybrid electric vehicles using swarm intelligence techniques

AbstractGreen technologies gain popularity to reduce the pollution and give higher penetration of renewable energy source in the transportation. This research induce that the extensive involvement of plug-in hybrid electric vehicles (PHEVs) requires adequate charging allocation strategy using a combination of smart grid systems and smart charging infrastructures. It is also noticed that daytime charging station are necessary for daily usage of PHEVs due to the limited all-electric-range. Most of the researches in the past have been stated that only proper charging control and infrastructure management can assure the larger participation of PHEVs. Therefore, researchers are trying to develop efficient control mechanism for charging infrastructure in order to facilitate upcoming PHEVs penetration in highway. Nevertheless, most of the past researcher already aware with the issue related to intelligent energy management. Yet, these studies could not fill the gap of the problem associated with intelligent ener...

Harmonic Impact of Plug-In Hybrid Electric Vehicle on Electric Distribution System

This paper presents the harmonic effects of plug-in hybrid electric vehicles (PHEV) on the IEEE 37-bus distribution system at different PHEV penetration levels considering a practical daily residential load shape. The PHEV is modeled as a current harmonic source by using the Open-Source Distribution System Simulator (OpenDSS) and DSSimpc software. Time series harmonic simulation was conducted to investigate the harmonic impact of PHEV on the system by using harmonic data obtained from a real electric vehicle. Harmonic effects on the system voltage profile and circuit power losses are also investigated by using OpenDSS and MATLAB software. Current/voltage total harmonic distortion (THD) produced from the large scale of PHEV is investigated. Test results show that the voltage and current THDs are increased up to 9.5% and 50%, respectively, due to high PHEV penetrations and these THD values are significantly larger than the limits prescribed by the IEEE standards.

Adequacy Assessment of Power Distribution Network with Large Fleets of PHEVs Considering Condition-Dependent Transformer Faults

As a new form of distributed energy resources, massive plug-in hybrid electric vehicles (PHEVs) could affect the power distribution system adequacy considering their intermittent charging loads and the load recovery ability during system outages. This paper proposes a comprehensive framework for adequacy evaluation of power distribution networks with PHEVs penetration. A condition-dependent outage model is used in this paper to obtain the time sequential failure rate of the transformer. Also, a business model for the PHEVs is developed to encourage the PHEV owners to charge their vehicles in such a way that the distribution system adequacy is enhanced. Based on this model, a smart charging algorithm is proposed for the PHEVs to minimize their charging cost and enhance the adequacy of the distribution network at the same time. Various simulation studies are carried out to verify the effectiveness of the proposed smart charging approach. The simulation results show that the proposed approach is effective in enhancing both the adequacy of the distribution network and economic profits of PHEVs.

Modeling the Impact of PHEV Penetration on the Residential Electrical Networks

Plug-in Hybrid Electric Vehicles (PHEV) have a better future in term of providing sustainable mobility due to their high efficiency and low emission levels. However, the global penetration of PHEVs can create negative impacts if their charging activities are not scheduled and controlled. This paper presents the impact of PHEVs charging on the residential network in Malaysia under various charging scenarios. The simulation results shows there will be a significant voltage drop in the cable and increment in load profile due to additional load. In order to avoid any unwanted circumtances, several PHEV charging profiles are analysed and some potential solutions are suggested including controlling and resizing of the cable.

Multi-Period Optimization Model for Electricity Generation Planning Considering Plug-in Hybrid Electric Vehicle Penetration

One of the main challenges for widespread penetration of plug-in hybrid electric vehicles (PHEVs) is their impact on the electricity grid. The energy sector must anticipate and prepare for this extra demand and implement long-term planning for electricity production. In this paper, the additional electricity demand on the Ontario electricity grid from charging PHEVs is incorporated into an electricity production planning model. A case study pertaining to Ontario energy planning is considered to optimize the value of the cost of the electricity over sixteen years (2014–2030). The objective function consists of the fuel costs, fixed and variable operating and maintenance costs, capital costs for new power plants, and the retrofit costs of existing power plants. Five different case studies are performed with different PHEVs penetration rates, types of new power plants, and CO2 emission constraints. Among all the cases studied, the one requiring the most new capacity, (~8748 MW), is assuming the base case with 6% reduction in CO2 in year 2018 and high PHEV penetration. The next highest one is the base case, plus considering doubled NG prices, PHEV medium penetration rate and no CO2 emissions reduction target with an increase of 34.78% in the total installed capacity in 2030. Furthermore, optimization results indicate that by not utilizing coal power stations the CO2 emissions are the lowest: ~500 tonnes compared to ~900 tonnes when coal is permitted.

Aggregation and Bidirectional Charging Power Control of Plug-in Hybrid Electric Vehicles: Generation System Adequacy Analysis

With increasing penetration of plug-in hybrid electric vehicles (PHEVs), it is necessary to introduce a two-way interactive mechanism between PHEVs and the power system to improve system reliability and satisfy the PHEV charging requirements. To address these requirements, a bidirectional charging power control method, based on the time series model of PHEV charging, is developed. The control strategy ensures that PHEVs achieve full-charge before the users’ desired disconnecting time, and allows the spare time during users desired charging horizons to be used to manage PHEV charging power and to respond to the generation capacity shortage signal. Grid-to-vehicle (G2V) and vehicle-to-grid (V2G) control strategies are defined to determine whether PHEVs draw power from the grid or inject power to the grid. Generation system adequacy and PHEV charging behavior are analyzed for various scenarios under this interactive mechanism, and the costs and benefits to vehicle users and utilities are analyzed based on several new generation system adequacy indices. The simulation results illustrate how charging power control can effectively improve generation system adequacy, particularly for higher PHEV penetration and when users are incentivized to extend charging horizons.

Decentralized Optimal Demand-Side Management for PHEV Charging in a Smart Grid

Plug-in hybrid electric vehicles (PHEV) are expected to become widespread in the near future. However, high penetration of PHEVs can overload the distribution system. In smart grid, the charging of PHEVs can be controlled to reduce the peak load, known as demand-side management (DSM). In this paper, we focus on the DSM for PHEV charging at low-voltage transformers (LVTs). The objective is to flatten the load curve of LVTs, while satisfying each consumer's requirement for their PHEV to be charged to the required level by the specified time. We first formulate this problem as a convex optimization problem and then propose a decentralized water-filling-based algorithm to solve it. A moving horizon approach is utilized to handle the random arrival of PHEVs and the inaccuracy of the forecast nonPHEV load. We focus on decentralized solutions so that computational load can be shared by individual PHEV chargers and the algorithm is scalable. Numerical simulations are given to demonstrate the effectiveness of our algorithm.

PHEV Charging and Discharging Cooperation in V2G Networks: A Coalition Game Approach

Recently, plug-in hybrid electric vehicles (PHEVs) have attracted considerable attention as a sustainable transport system and also an essential component of the smart grid. With the rapid growth of PHEVs penetration, the charging and discharging of PHEVs will pose a significant impact on the residential electricity distribution network. For this reason, the management of PHEV charging and discharging has become one of the key issues in the research of PHEVs. In most existing work, PHEVs are supposed to operate individually for charging and discharging in the grid. However, we argue that, by leveraging the cooperation among PHEVs, the grid will efficiently stimulate PHEV users to charge in load valley and discharge in load peak. As a consequence, the electricity load is well balanced. Meanwhile, the PHEV users also achieve higher profit. The PHEV charging and discharging cooperation is a win-win strategy for both the grid and the PHEV users. We formulate and resolve the PHEV charging and discharging cooperation in the framework of coalition game. The simulation results indicate that the peak-valley difference in electricity load of the grid is significantly reduced. Besides, the PHEV users have better satisfaction in the vehicle battery status and the economic profit.