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Modeling the temporal and economic feasibility of electric vehicles providing vehicle-to-grid services in the electricity market under different charging scenarios
... EV owners use the valley tariff to fully charge at night, and when they arrive at their workplace, the idle EVs are managed by the V2G aggregators, thus making profits from the tariff difference. At the end of the workday, the V2G aggregators pay the fee according to the V2G technology's contracts and reserve a certain amount of power to enable the EV owners to return home safely [42]. The business scheme of peak-to-valley arbitrage using V2G technology is shown in Figure 5. Currently, numerous studies have investigated the economic feasibility of V2G technology participation in peak-to-valley arbitrage, with results being generally optimistic. ...
... Consequently, the application scenarios that require V2G technology capabilities primarily fall into three categories: home-based, workplace-based, and CSs-based. The V2G technology's application scenarios classified by location exhibit significant time-scale variations [42]. ...
... If CPs are not installed at home, the majority of EV owners will choose to charge their EVs at workplace [42]. Considering that the typical workday time spans around 8 hours, EVs at workplace have a significant amount of idle time. ...
Electric vehicles (EVs) play a crucial role in the global transition towards decarbonization and renewable energy resources (RERs). As EVs gain popularity, this has resulted in various challenges for the power grid, such as an intensified peak-to-valley load differential, causing transformer overloading. Vehicle-to-grid (V2G) technology has emerged as a promising solution due to its controllable charging and discharging capabilities. Mature business schemes can incentivize the development of V2G technology. However, the business schemes of V2G technology are still unclear. Therefore, this paper provides a comprehensive review of the business schemes associated with V2G technology, especially focusing on its feasibility and challenges with respect to the electricity market. In this paper, several business schemes with respect to the electricity market are explored by conducting extensive literature reviews, including peak-to-valley arbitrage, the spot market, demand–response (DR), frequency regulation, voltage regulation, spinning reserve, and black start. Next, application scenarios and real-world use cases of the V2G technology’s business schemes are investigated. Furthermore, the challenges faced by the V2G technology’s business schemes are assessed by considering the technical, economical, and social aspects. By identifying these challenges, it is important to highlight the existing shortcomings and areas of interest for V2G technology’s research and development. This review contributes to a deeper understanding of V2G technology and its implications for the energy sector.
... An optimization model was formed to maximize EV owners' profits; a quadratic function was used to describe the battery degradation costs in the V2G process. Three typical charging scenarios were evaluated by taking the New York electricity market as the case study [9]. A nonlinear function was formed to describe the EV battery degradation. ...
... To guarantee the daily travel demand for each EV, equation (8) is carried out to ensure that agents have sufficient energy to supply the driving demand of EVs in a disconnected state during time period t. At the same time, when EVs participate in frequency regulation service, the schedulable total energy during period t cannot be lower than the demand energy of EV in a disconnected state during that time period, as shown in the equation (9). ...
Electric vehicles (EVs) are likely to have a continuing presence in the vehicle market all over the world for the next few decades. The rapid development of large‐scale applications of EVs in China has provided a foundation for the implementation of vehicle‐to‐grid (V2G) technology. V2G can help EVs participate in grid regulation services. Based on the economic model of EV integration with the grid, the regulation ability and potential economic and environmental benefits brought by EV high penetration are analyzed using relevant data from Shanghai. Analysis results show that EV participation with V2G capability can not only reduce EV expenditures but also provide peak load‐shifting service. Further analyses show that with the increase of EV charging power and peak‐valley electricity price ratio and the decrease of battery loss cost, the economic benefits of V2G applications will increase. The large‐scale development of EVs also can effectively reduce CO2 emissions according to the model proposed.
... On the other hand, their willingness to participate in V2X has not been investigated in Sweden. Although several countries have started to investigate the barriers and willingness of EV owners to participate in the V2G program, e.g., [19][20][21][22][23][24][25][26], such studies are very limited in Sweden [31]. developed. ...
... On the other hand, their willingness to participate in V2X has not been investigated in Sweden. Although several countries have started to investigate the barriers and willingness of EV owners to participate in the V2G program, e.g., [19][20][21][22][23][24][25][26], such studies are very limited in Sweden [31]. In order to explore Swedish EV owners' willingness surrounding V2X implementation, namely, V2G and V2H, in this study, the authors relied primarily on data collection through an online questionnaire. ...
Vehicle-to-everything (V2X) refers to the technology that enables electric vehicles (EVs) to push their battery energy back to the grid. The system’s V2X integration includes key functions like V2G, V2H, V2B, etc. This paper explores the preferences of Swedish EV drivers in contributing to V2X programs through an online questionnaire. Respondents were asked to answer questions in three contexts: (1) claims related to their EV charging, (2) V2G application by EV, and (3) V2H application by EV. The respondents were questioned about the importance of control, pricing, energy sustainability and climate issues, impact on the battery, the acceptability of V2X, range anxiety, financial compensation, as well as how and where they prefer to charge the EV. The results of the survey indicate that Swedish EV drivers are more interested in the V2H application than in V2G. Additionally, they express more concern about range anxiety than battery degradation due to the V2X application.
... EV owners can also save money by using electricity when prices are low and generate extra income by reselling electricity to the grid when demand is Internal impedance (Ω) ΔE(T B ) Voltage compensation offset due to variation in temperature (K) dV OC /dT Change in voltage due to electrochemical reactions at its peak. Zheng et al. examined the economic viability and time availability of electric vehicles to determine their potential for providing vehicle-to-grid services [12]. Different charging scenarios including at fast charging stations, home, and work were examined. ...
... In the workplace context, Zheng et al. 20 found that workplace EV charging has significant potential to provide grid services, benefiting both the network operator and the EV owner. While there has been growing research interest in the benefits of providing grid services from EV batteries in recent years [21][22][23][24][25][26][27][28] , all the reviewed works in the literature have focused on the level (or existence) of benefits to network operators or electricity market agents [21][22][23][24] and EV owners [25][26][27][28] . ...
Expanding electric vehicle (EV) charging infrastructure is essential for transitioning to an electrified mobility system. With rising EV adoption rates, firms face increasing regulatory pressure to build up workplace charging facilities for their employees. However, the impact of EV charging loads on businesses’ specific electricity consumption profiles remains largely unknown. Our study addresses this challenge by presenting a mathematical optimisation model, available via an open-source web application, that empowers business executives to manage energy consumption effectively, enabling them to assess peak loads, charging costs and carbon emissions specific to their power profiles and employee needs. Using real-world data from a global car manufacturer in South East England, UK, we demonstrate that smart charging strategies can reduce peak loads by 28% and decrease charging costs and emissions by 9% compared to convenience charging. Our methodology is widely applicable across industries and geographies, offering data-driven insights for planning EV workplace charging infrastructure.
... Further studies have examined potential revenue streams for V2G services, such as frequency regulation 74 and renewable energy integration, 75 which can improve the economic income for both EVUs and grids. 76 The economic feasibility of V2G, however, faces several challenges. Battery degradation is a critical issue, as the frequent charge-discharge cycles associated with V2G can accelerate battery wear. ...
Vehicle-to-Grid accelerates the transition to renewable, low-carbon power systems by integrating electric vehicles. This study analyzes the 2023 U.S. electric vehicle charging demand, variable renewable energy capacities, and charging infrastructure...
... Zheng et al. [121] investigated the viability of EVs for V2G applications based on two perspectives: time availability and financial viability. They assessed the suitability of three charging situations for V2G services: at home, at work, and at fast charging stations (FCSs). ...
Electric vehicles (EVs) must be used as the primary mode of transportation as part of the gradual transition to more environmentally friendly clean energy technology and cleaner power sources. Vehicle-to-grid (V2G) technology has the potential to improve electricity demand, control load variability, and improve the sustainability of smart grids. The operation and principles of V2G and its varieties, the present classifications and types of EVs sold on the market, applicable policies for V2G and business strategy, implementation challenges, and current problem-solving techniques have not been thoroughly examined. This paper exposes the research gap in the V2G area and more accurately portrays the present difficulties and future potential in V2G deployment globally. The investigation starts by discussing the advantages of the V2G system and the necessary regulations and commercial representations implemented in the last decade, followed by a description of the V2G technology, charging communication standards, issues related to V2G and EV batteries, and potential solutions. A few major issues were brought to light by this investigation, including the lack of a transparent business model for V2G, the absence of stakeholder involvement and government subsidies, the excessive strain that V2G places on EV batteries, the lack of adequate bidirectional charging and standards, the introduction of harmonic voltage and current into the grid, and the potential for unethical and unscheduled V2G practices. The results of recent studies and publications from international organizations were altered to offer potential answers to these research constraints and, in some cases, to highlight the need for further investigation. V2G holds enormous potential, but the plan first needs a lot of financing, teamwork, and technological development.
... In [10], the authors explored the latest distributed charging control schemes for EVs from the perspectives of charging network operators, EV users, and aggregators, which provided a reference for research on distributed optimization algorithms. In [11,12], the authors investigated the potential of EVs as distributed energy storage devices in participating in V2G services and assessed their influence on the power system, highlighting the practical challenges that V2G scheduling encounters when accounting for business models and market mechanisms. The former introduces temporal and economic indicators to evaluate the feasibility of EVs providing V2G services across various charging scenarios. ...
With the increasing penetration of electric vehicles (EVs), the spatial–temporal coupling between the transportation network (TN) and the power distribution network (PDN) has intensified greatly. Large-scale uncoordinated charging of EVs significantly impacts both the PDN and TN. In this paper, an optimal scheduling strategy for EV charging and discharging in a coupled power–transportation network (CPTN) with Vehicle-to-Grid (V2G) scheduling and dynamic pricing is proposed. The strategy considers the influence of dynamic transportation road network (DTRN) information on EV driving patterns, as well as the unique vehicle characteristics and mobile energy storage capabilities of EVs. Firstly, a DTRN model is established. Subsequently, the dynamic Dijkstra algorithm is utilized to accurately simulate the EV driving paths and predict the spatial–temporal distribution of the EV charging load. Secondly, optimal scheduling for EV charging and discharging within the CPTN is performed, guided by a V2G model coupled with a multi-time dynamic electricity price (MTDEP) strategy to optimize the grid load curve while accommodating the charging requirements of EVs. Finally, the effectiveness and superiority of the proposed optimization scheduling model are validated by the IEEE 33-node PDN test system.
... Incentive payments could draw more participants into V2G contracts, and trading carbon emissions in the system to balance the energy demand could reduce carbon emissions [41,42]. However, a study by Zheng et al. also showed that BEVs participating in V2G for revenue generation at current rates do not cover the cost of battery degradation [43]. Further cost reductions in the battery, decreases in battery degradation per cycle, and increased feed in tariffs or net metering credit are all needed to draw more BEV participants; this also opens up opportunities for using FC-EVs for V2G's implementation. ...
This paper presents an overview of the status and prospects of fuel cell electric vehicles (FC-EVs) for grid integration. In recent years, renewable energy has been explored on every front to extend the use of fossil fuels. Advanced technologies involving wind and solar energy, electric vehicles, and vehicle-to-everything (V2X) are becoming more popular for grid support. With recent developments in solid oxide fuel cell electric vehicles (SOFC-EVs), a more flexible fuel option than traditional proton-exchange membrane fuel cell electric vehicles (PEMFC-EVs), the potential for vehicle-to-grid (V2G)’s implementation is promising. Specifically, SOFC-EVs can utilize renewable biofuels or natural gas and, thus, they are not limited to pure hydrogen fuel only. This opens the opportunity for V2G’s implementation by using biofuels or readily piped natural gas at home or at charging stations. This review paper will discuss current V2G technologies and, importantly, compare battery electric vehicles (BEVs) to SOFC-EVs for V2G’s implementation and their impacts.
... Another study suggested that the widespread use of BEVs with higher battery capacities and the establishment of broader charging accessibility might diminish the peak demand from charging or shift the maximum demand time frame to one that is not aligned with peak household demand [19]. Furthermore, the stress of EDSs [20] could be reduced by implementing storage facilities at the CSs and promoting the potential provision of V2G services by electric vehicle owners [21]. Energies 2024, 17, 5314 3 of 29 ...
Battery electric vehicles represent a technological pathway for reducing carbon emissions in personal road transport. However, for the widespread adoption of this type of vehicle, the user experience should be similar to that of combustion engine vehicles. To achieve this objective, a robust and reliable public charging infrastructure is essential. In Spain, the electric recharging infrastructure is growing quickly in metropolitan areas but much more slowly on roads and highways. The upcoming charging stations must be located along high-volume traffic corridors and in proximity to the Trans-European Transport Network. The main contribution of this research is to offer a method for examining the essential electricity infrastructure investments required in scenarios involving substantial electric vehicle adoption. The methodology includes a sensitivity analysis of fleet composition and market share, recharging user behavior, charging station density, and vehicle efficiency improvements. To this end, the authors have developed a simplified probabilistic model, addressing the effect of the involved parameters through a comprehensive scenario analysis. The results show that the actual number of high-capacity charging plugs on Spanish roads is significantly lower than the European regulation requirements for the year 2030 considering an electric vehicle market share according to the Spanish Integrated National Energy and Climate Plan 2021–2030 objectives and it is far from the necessary infrastructure to cover the expected demand according to the traffic flow. Under these circumstances, the charging peak power demand reaches over 7.4% of the current Spanish total power demand for an electric vehicle fleet, which corresponds to only 12% of the total.
... Zheng et al. [11] found that workplace EV charging has significant potential to provide grid services, benefiting both the network operator and the EV owner. While there has been growing research interest in the benefits of providing grid services from EV batteries in recent years [12][13][14][15][16][17][18][19], all the reviewed works in the literature have focused on the level (or existence) of benefits to network operators or electricity market agents [12][13][14][15] and EV owners [16][17][18][19]. ...
Expanding electric vehicle (EV) charging infrastructure is essential for transitioning to an electrified mobility system. With rising EV adoption rates, firms face increasing regulatory pressure to build up workplace charging facilities for their employees. However, the impact of EV charging loads on businesses’ specific electricity consumption profiles remains largely unknown. Our study addresses this challenge by presenting a mathematical optimisation model, available via an open-source web application, that empowers business executives to manage energy consumption effectively, enabling them to assess peak loads, charging costs, and carbon emissions specific to their power profiles and employee needs. Using real-world data from a global car manufacturer in South East England, UK, we demonstrate that smart charging strategies can reduce peak loads by 28% and decrease charging costs and emissions by 9% compared to convenience charging. Our methodology is widely applicable across industries and geographies, offering data-driven insights for planning EV workplace charging infrastructure.
... Since 2016, the number of electric vehicles (EVs) in China has been climbing year by year and is expected to exceed 80 million in 2030 [2], but the charging demand of electric vehicle users presents randomness, and the large amount of random loads it generates will bring great challenges to the power grid [3], especially in terms of the balance of power supply and demand, grid stability, and economic feasibility [4]. But at the same time, EVs can also be used as distributed energy storage devices to provide vehicle-to-grid (V2G) services to alleviate grid overload and benefit the power system [5]. In addition, EVs can also be included in the optimal scheduling of the carbon market to improve the economic feasibility of China's low-carbon transition through the optimal scheduling of EV charging [6]. ...
The rapid development of electric vehicles (EVs) has brought great challenges to the power grid, so improving the EV load prediction accuracy is crucial to the safe operation of the power grid. Aiming at the problem of insufficient consideration of spatial dimension information in the current EV charging load forecasting research, this study proposes a forecasting method that considers spatio-temporal node importance information. The improved PageRank algorithm is used to carry out the importance degree calculation of the load nodes based on the historical load information and the geographic location information of the charging station nodes, and the spatio-temporal features are initially extracted. In addition, the attention mechanism and convolutional network techniques are also utilized to further mine the spatio-temporal feature information to improve the prediction accuracy. The results on a charging station load dataset within a city in the Hebei South Network show that the model in this study can effectively handle the task of forecasting large fluctuations and long time series of charging loads and improve the forecasting accuracy.
... Some of these studies have focused on simulating optimal charging strategies [24][25][26] and assessing the impact of different levels of EV penetration [27]. They have explored how EVs influence renewable energy integration [27][28][29][30], emissions [31,32], and cost analysis [33,34]. Additionally, there is ongoing research on V2G strategies and their effects on energy systems and energy storage requirements [35][36][37]. ...
As the global transition toward sustainable energy gains momentum, integrating electric vehicles (EVs), energy storage, and renewable energy sources has become a pivotal strategy. This paper analyses the interplay between EVs, energy storage, and renewable energy integration with Indonesia’s grid as a test case. A comprehensive energy system modeling approach using PLEXOS is presented, using historical data on electricity generation, hourly demand, and renewable energy, and multiple scenarios of charging patterns and EV adoption. Through a series of scenarios, we evaluate the impact of different charging strategies and EV penetration levels on generation capacity, battery storage requirements, total system cost, renewable energy penetration, and emissions reduction. The findings reveal that optimized charging patterns and higher EV adoption rates, compared to no EVs adoption, led to substantial improvements in renewable energy utilization (+4%), emissions reduction (−12.8%), and overall system cost (−9%). While EVs contribute to reduced emissions compared to conventional vehicles, non-optimized charging behavior may lead to higher total emissions when compared to scenarios without EVs. The research also found the potential of vehicle to grid (V2G) to reduce the need for battery storage compared to zero EV (−84%), to reduce emissions significantly (−23.7%), and boost penetration of renewable energy (+10%). This research offers valuable insights for policymakers, energy planners, and stakeholders seeking to leverage the synergies between EVs and renewable energy integration to pursue a sustainable energy future for Indonesia.
... 2. Literature review Sustainability must be ensured to conduct an effective market analysis for smart grid technology investments. The most important benefit of the sustainability perspective is that businesses do not focus only on short-term financial returns (Zheng et al., 2023a;Rahman, 2023). Instead, according to Tan et al. (2023), it is possible to say that sustainability takes into consideration the needs of future generations, since natural resources are not consumed unconsciously. ...
Purpose
This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.
Design/methodology/approach
In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.
Findings
The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.
Originality/value
It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.
... Furthermore, the lack of concrete business models slows down V2G adoption [17]. V2G was investigated for the New York electricity market in [18] based on economic aspects and the availability of time for the charging. ...
With more electric vehicles introduced in society, there is a need for the further implementation of charging infrastructure. Innovation in electromobility may result in new charging and discharging strategies, including concepts such as smart charging and vehicle-to-grid. This article provides an overview of vehicle charging and discharging innovations with a cable connection. A MATLAB/Simulink model is developed to show the difference between an electric vehicle with and without the vehicle-to-grid capabilities for electricity grid prices estimated for Sweden for three different electric vehicle user profiles and four different electric vehicle models. The result includes the state-of-charge values and price estimations for the different vehicles charged with or without a bidirectional power flow to and from the electric grid. The results show that there is a greater difference in state-of-charge values over the day investigated for the electric vehicles with vehicle-to-grid capabilities than for vehicles without vehicle-to-grid capabilities. The results indicate potential economic revenues from using vehicle-to-grid if there is a significant variation in electricity prices during different hours. Therefore, the vehicle owner can potentially receive money from selling electricity to the grid while also supporting the electric grid. The study provides insights into utilizing vehicle-to-grid in society and taking steps towards its implementation.
Vehicle-to-Grid (V2G) technology enables electric vehicles (EVs (Unless otherwise specified, Electric Vehicles (EVs) in this study refer to the totality of BEVs, PHEVs, and other battery-equipped vehicles that have the potential to participate in V2G)) to interact with renewable energy sources, positioning it as a key driver of energy system decentralization. While V2G holds significant potential for enhancing grid stability and economic efficiency, its large-scale deployment requires a robust economic assessment. However, existing research predominantly focuses on technical feasibility, lacking comprehensive economic evaluations due to the complexity of V2G system architectures. To bridge this gap, we propose the BSTP (Business-Stakeholders-Technology-Policy) V2G economic evaluation framework and the VRR (Value Realization Rate) methodology, employing a Semi-Systematic Co-Design Approach. This framework systematically characterizes the evolution of V2G business models, the interactions among key stakeholders, the influence of technological and policy factors, and the criteria for economic feasibility assessment. Furthermore, we identify a “Big Models, No Trials” issue in V2G economic research, where large-scale theoretical models lack empirical validation. To address this challenge and ensure the practical applicability of our framework, we define six core challenges that must be resolved for a rigorous economic evaluation of V2G. Our findings provide a structured foundation for future research and policy development, offering insights that could accelerate the transition to decentralized energy systems.
Vehicle-to-Grid (V2G) technology is a transformative solution aimed at enhancing the sustainability and resilience of electric grid infrastructure. This paper provides a review of V2G technology on its technical, economic, and environmental aspects. The paper explains the integration of renewable energy, V2G’s potential to reduce greenhouse gas (GHG) emissions, and its role in improving grid stability through ancillary services. The study discusses the limitations of technical requirements concerned with battery degradation, communication protocols, and cybersecurity associated with grid connectivity. The paper further highlights the economic opportunities of V2G covering the market trends, policies, and regulations that can support widespread adoption. Additionally, implemented V2G cases are analyzed to explore the potential emerging technologies that could address the barriers to V2G large-scale deployments. We also present the major pitfalls that can stand in the way of utilizing electric vehicles (EVs) as dynamic and distributed energy resources (DERs) to serve the future.
div class="section abstract"> Nowadays, electrification is largely acknowledged as a crucial strategy to mitigate climate change, especially for the transportation sector through the transition from conventional vehicles to electric vehicles (EVs). As the demand for EVs continues to rise, the development of a robust and widespread charging infrastructure has become a top priority for governments and decision-makers. In this context, innovative approaches to energy management and sustainability, such as Vehicle-to-Grid (V2G), are gradually being employed, leading to new challenges, like grid service integration, charge scheduling and public acceptance. For instance, the planned use scenario, the user’s behavior, and the reachability of the geographical position influence the optimal energy management strategies both maintain user satisfaction and optimize grid impact. Firstly, this paper not only presents an extensive classification of charging infrastructure and possible planning activities related to different charging scenarios but also indicates the most feasible Point of Interest (POIs) for certain energy strategies and a user’s behavior associated with POIs. Secondly, the article proposes a systematic procedure to analyze the potential location using accessible data from OpenStreetMap (OSM), considering different POIs categories and the classifications proposed above. Therefore, this methodology can support future practitioners both in the definition of the suitability of a charging geographical position for specified energy management strategies (e.g., V2G) and the best path planning for a defined charging location. Lastly, the proposed model is applied to a real case study, functional to the XL-Connect Horizon Europe project. The results proposed utilized open-source geographical data and can be obtained for other worldwide case studies.
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Given the rapid growth of electric vehicles (EVs) ownership and the accelerated construction of novel energy systems, it is urgent to promote the integration of EVs and integrated energy systems (IESs). This study proposes a tri-level optimization model to optimize the operation and capacity of the IES with the orderly charging/discharging (OCD) of EVs considering individual EV behavior. In which, the trip schedule and state of charge (SOC) demand of EVs is predicted by a spatiotemporal-SOC characterization model. Moreover, through the charging and discharging quote based on the trend of time-of-use tariffs to guide the OCD of each EV, the decoupling of the OCD decision-making and IES scheduling is achieved based on an interaction level and a pre-calculation method. Finally, this study optimizes the operation and capacity of the IES with the minimum operating cost and total cost, respectively. Following a simulation case study, the results show that the IES with OCD of EVs can reduce the operating cost by 12.1 % at the expense of 0.9 % increase in equipment cost, which is significantly better than that with the electrical energy storage devices (EESs) which reduces the operating cost by 6.9 % at the expense of 7.9 % increase in equipment cost. Moreover, integrating the OCD of EVs with the EESs can reduce the operating cost by 17.9 % and the final total cost by 7.4 %. At the same time, EV owners in general not only achieve free charging but also receive an overall daily revenue of 613.3 CNY to supplement the additional battery degradation loss of EVs. This study also conducted uncertainty analyses on the number of EVs, battery capacity and charging/discharging power, and energy prices. Generally, this study investigates the economic and technical feasibility of integrating EVs with IES.
The integration of electric vehicles (EVs) into the electricity grid through vehicle-to-grid (V2G) technology represents a promising opportunity to improve energy efficiency and stabilize grid operations in the context of building sustainable cities. This paper provides a systematic review of the literature to assess the status of the research and identify the road ahead. Using bibliometric analysis and systematic assessment, the critical factors that influence the charging behavior of electric vehicles, the adoption of V2G, and the effective use of EVs as dynamic energy resources are identified. The focus is particularly on the ecological transitions toward sustainability, travel characteristics, technical specifications, requirements, and barriers in real use, and the behavioral and psychological aspects of stakeholders. The results lay the foundation for accurate forecasts and the strategic implementation of V2G technology to support the needs of the electric grid. They emphasize the importance of considering the psychological and behavioral aspects of users in the design of V2G strategies and define the key factors to predict the demand for electric vehicle charging. Furthermore, they highlight the main barriers to V2G adoption, which are primarily related to concerns about battery degradation and economic issues. Privacy and security concerns, due to data sharing with electric vehicle aggregators, also limit the adoption of V2G. Addressing these challenges is essential for the successful integration of electric vehicles into the grid.
The aim of this work was to create an original numerical model for conducting an economic analysis of Vehicleto-Grid (V2G) services. This model enables the computation of potential economic earnings for a certain user
providing V2G services to the grid operator, considering Portugal's electricity market and the country's increasing
adoption of Electric Vehicles (EVs). The model incorporates various parameters in its calculations, including
battery degradation, distance traveled, charging frequency, number of V2G charge-discharge cycles, electricity
purchase and sale prices or the cost of new batteries. These factors contribute to robust values that facilitate a
detailed analysis closely aligned with the realities of different citizens, since no study found in the literature has
addressed the economics of V2G technology in this sense. To test this model, we created four hypothetical EV
users with distinct characteristics, aiming to understand the scenarios where providing this energy storage
service is most beneficial from the EV user perspective. We considered and compared three scenarios for the
selling price of electricity back to the grid (0,50 €/kWh, 0,30 €/kWh, and 0,20 €/kWh) and performed a
sensitivity analysis. The goal is that by the time each user needs to replace their battery due to degradation, they
will have generated sufficient income from the V2G service to not only cover the cost of a new battery (10,000 €)
but also make a profit. This takes into account the future development of energy storage and the anticipated
decline in prices. Results suggest that the V2G service can be highly beneficial when electricity sale prices are
high (0,50 €/kWh) for users with very low car usage (profits of 624 € per month and 1547 € in total after the costs
of a new battery), but the same doesn't happen when the prices for selling electricity to the grid drop to 0,30 or
0,20 €/kWh. This service can be advantageous too for users who use their cars intensively, even if the electricity
selling price is low (0,20 €/kWh), as it allows for savings on the purchase of a new battery (savings between 300 €
- 1100 € on the cost of a new battery).
Vehicle-to-grid (V2G) services, utilizing electric vehicle (EV) batteries for grid support, enhance reliability and reduce peak energy demand. We present a physics-based model tuned for three different cell chemistry families and examine the influence of bulk V2G services on EV battery life. We consider various duty cycles, cell chemistries with nickel content (NMCxyz and various anode graphites), and associated dominant degradation mechanisms. To quantify the impact of offering V2G services, we introduce the V2G benefit-to-harm ratio (B2H) . We define the benefit as the Ah gained with V2G and the harm as the life lost in days due to V2G, both compared to the baseline noV2G.
B2H=(normalized Ah gained by 70% capacity fade) divided by (time in days reduction by the time that capacity fade has reached 70%). Note that the 70% capacity fade can be changed for various vehicle models depending on the warranty definition of the % capacity or usable battery energy (UBE) at the end of the warranty.
Our findings indicate that the dominant degradation mechanism plays a crucial role in the benefit-to-harm (B2H) ratio of V2G or vehicle-to-building (V2B) [1]. Specifically, we clarify that the relative contribution of calendar aging to overall capacity loss is pivotal in determining the degradation due to V2G and possible associated benefits.
Our model takes into account four degradation mechanisms based on a single-particle model. SEI growth and cathode transition metal dissolution are part of the calendar aging loss of lithium inventory (LLI Cal ). The remaining LLI is attributed to Li-plating and mechanical degradation caused by particle cracking.
We calibrate the model for three families of cell chemistries and conditions. The primary degradation mechanism for one cell family is anode mechanical degradation (LAM Neg ). The second family of cells predominantly ages due to SEI layer growth, and the third family is degrading due to both mechanisms [2].
We show that, in cases with a higher contribution of calendar aging to degradation (LLI Cal /LLI), V2G can be potentially more beneficial (in Ah gained by 70% capacity fade) than harmful (lifetime reduction in days by the time that capacity fade has reached 70%). Furthermore, we have evidence that the V2G charging pattern can have a secondary effect on the B2H ratio. For example, being a risk taker and charging the battery late or being cautious and charging it as soon as possible can lead to different degrees of degradation depending on the chemistry and conditions of the battery [3].
With our multiphysics reduced order model of battery lifetime degradation, we fully explain why previous studies [4] have shown that the impact on EV battery degradation varies from inconsequential [5] to projecting a need for early battery replacement [6]. Our results clarify that battery chemistry and usage patterns are important factors in determining whether or not to utilize a vehicle for grid support, as well as the overall financial impact on the owner and OEM warranty.
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Figure 1. Capacity retention wrt.(a) days (b) normalized Ah throughput for different scenarios and operational conditions. Discharging to the grid reduces the battery life substantially and increases Ah throughput minimally in NMC111 cells. NMC622-45 case reacts the opposite, and NMC622-25C is somewhere between these two cases. (c) Comparison of the V2G benefit-to-harm ratio wrt. the portion of LLI that is caused by SEI growth.
Figure 1
For the past few years, urban areas have been grappling with increasing pollution and traffic congestion. The adoption of electric rickshaws presents a promising solution for sustainable and clean urban mobility. However, integrating these e-rickshaws into the electrical grid successfully necessitates careful planning and the installation of renewable energy alternatives. Various challenges are faced by the conventional grid systems in accommodating the charging needs of growing fleet of e-rickshaws; and this problem is faced by most of the states in India. Cases of power theft for charging e-rickshaws have become quite common. And thus, to overcome this problem, charging stations can be made separately for e-rickshaws by using renewable energy sources. This chapter deals with the setting up of a plant using renewable energy in a place called ‘Seoraberia,' Howrah, West Bengal, by using biogas and PV as the main source of renewable energy.
Electric vehicle (EV) batteries are often underutilized. Vehicle-to-grid (V2G) services can tap into this unused potential, but increased battery usage may lead to more degradation and shorter battery life. This paper substantiates the advantages of providing load-shifting V2G services when the battery is aging, primarily due to calendar aging mechanisms (active degradation mechanisms while the battery is not used). After parameterizing a physics-based digital-twin for three different dominant degradation patterns within the same chemistry (NMC), we introduce a novel metric for evaluating the benefit and associated harm of V2G services: \textit{throughput gained versus days lost (TvD)} and show its strong relationship to the ratio of loss of lithium inventory (LLI) due to calendar aging to the total LLI (). Our results that focus systematically on degradation mechanisms via lifetime simulation of digital-twins significantly expand prior work that was primarily concentrating on quantifying and reducing the degradation of specific cells by probing their usage and charging patterns. Examining various cell chemistries and conditions enables us to take a broader view and determine whether a particular battery pack is appropriate for load-shifting (V2G) services. Our research demonstrates that the decision "to V2G or not to V2G" can be made by merely estimating the portion of capacity deterioration caused by calendar aging. Specifically, TvD is primarily influenced by the chemistry of cells and the environmental temperature where the car is parked, while the usage intensity and charging patterns of EVs play a lesser role.
Achieving an optimal compromise between economic objectives and sustainability during the operation of an integrated Photovoltaic-Storage Charging Station (PS-CS) poses a common challenge. Traditional multi-objective optimization methods often fall short of effectively addressing nuanced trade-offs and incorporating decision-maker preferences. This paper introduces a novel two-stage optimization scheme to find the optimal compromise of energy management strategy by incorporating an adaptive parameter (lambda) to represent decision-maker preferences. Concretely, the first stage employs a predictive global economic optimization algorithm to maximize the economic objective. In the second stage, an adaptive method, informed by the previous stage results, is employed to reconcile the sustainability objectives, thereby facilitating the identification of an optimal compromise. The optimization problems in each stage can be solved efficiently by commercial solvers in MATLAB making it suitable for real-time energy management. The efficiency of the proposed methodology is evaluated through an actual case. The outcomes substantiate the method's effectiveness in enhancing sustainability objectives by up to 7 % and 18 % while constraining profit reduction to within 3 %. Two comparisons with the conventional weighting approach highlight the proposed method's superior controllability in aligning with the decision-maker preferences and its enhanced robustness in various scenarios.
Vehicle-to-grid (V2G) technology, a key driver for reducing carbon emissions and promoting sustainability, promises significant economic benefits through efficient energy exchanges between electric vehicles (EVs) and power distribution grids. However, the inherent uncertainty and variability in EV charging behavior pose challenges in accurately estimating potential economic gains from coordinated smart charging, presenting difficulties for charging service providers. In response to this, our study introduces a data-driven framework for assessing the profitability of fast-charging stations based on real-world operational data. This framework integrates data analytics, mixed-integer optimization, and behavioral theory. To address the computational challenge posed by optimizing charging schedules for numerous sessions, a tailored sub-gradient method is proposed. Additionally, a logit-based choice model is incorporated to account for the participation decisions of users. The flexibility of 0.7 million charging session profiles is thoroughly analyzed under peak-shaving incentives from the grid and quantifies the resultant monetary benefits. The analysis further extended to multiple influencing factors such as climate and the Covid-19 pandemic. Results suggest that fast charging stations under a coordinated charging scheme could experience a monthly bill curtailment of 20–30% compared to uncoordinated circumstances. These findings could pave the way for more efficient and profitable V2G operations, thereby accelerating the transition toward a more sustainable transportation infrastructure.
The market share of plug-in electric vehicles (PEVs) is growing, thanks to improvements in battery efficiency, declining production costs, and sustained policy support. Concurrently, concerns are growing over the supply of decommissioned PEV batteries. This has attracted a growing interest among scientists to determine the utility of repurposing PEV batteries for energy storage. Previous work has optimized behind-the-meter (BTM) battery storage systems (BSSs) for self-sufficiency and energy arbitrage, but few have used the system to lessen a home's electricity-related carbon footprint. This study uses high-resolution 2018 electricity demand from energy-efficient homes in Austin, Texas and grid generation data to simulate the daily operations of a 6 kWh BTM-BSS to minimize daily CO2e emissions. Results suggest that such homes with rooftop solar can reduce electricity-related household CO2eemissions by 21%, on average (about 1 ton of CO2e annually), while homes without solar could reduce their CO2e emissions by just 2% (about 0.12 tons per year). Pairing a BSS with rooftop solar increases average annual carbon savings by greater energy retention and lessening demand from the grid during carbon-intense generation periods. To make BTM-BSSs cost-effective for Austin homeowners, the price of repurposed PEV batteries must fall to 70.34 for homeowners to reach break-even over an estimated 10-year BSS lifespan.
Transportation electrification plays an important role in developing more sustainable systems. As a result, the adoption of electric vehicles (EVs) is increasingly endorsed by governmental policies. It can be even more encouraged by promoting the provision of different ancillary services using vehicle-to-grid (V2G) enabled EVs, since EV owners may obtain additional profit by market participation. This paper presents an assessment of the economic benefits of using EVs to participate in the primary frequency regulation markets from the EV owner perspective. A heuristic method is proposed to optimize the power bid that maximizes the EV owners’ revenue along with a set of operational strategies that facilitates the service provision, which is evaluated using a simulation-based approach. A comparison analysis is performed to individually demonstrate the economic potential that four EVs with different battery capacities may offer to the owner when providing frequency-controlled normal operation reserves (FCR-N) in the Nord Pool market. The assessment of the power bid is performed considering the influence of the operation strategies and customer preferences. In addition, the effect of FCR-N on EV battery degradation and the grid impact caused by the service provision are considered in the economic evaluation. The results estimate annual benefits ranging between €100 and €1100 per vehicle, which demonstrates that EV owners can obtain substantial revenues by providing FCR-N.
The increasing penetration of renewable generation in electricity markets as well as the rising number of electric vehicles pose new challenges for transmission grids. Additional demand and regionally clustered generation force system operators to consider costly expansion plans and employ expensive redispatch measures in the meantime. In this paper, we assess the ability of the expanded German transmission grid to cope with the additional demand of uncoordinated electric vehicle charging using a transportation problem formulation. We then propose local flexibility markets for electric vehicle owners to relieve the grid of congestion and to provide a heuristic that finds feasible solutions. We test our models on empirical data from the German electricity system of 2016. We find that the currently proposed expansion of the German electricity grid will not suffice to cope with increased electricity demand from uncoordinated electric vehicle charging. However, with coordination, electric vehicles can support transmission grid balancing and local flexibility markets can provide reasonable remuneration for electric vehicle owners.
The idea that electric vehicles can connect to the electric grid to provide ancillary services, such as frequency regulation, peak shaving and spinning reserves is compelling, especially in jurisdictions where traditional forms of storage, backup or peak supply are unavailable or expensive. Since conception, the economic viability of vehicle-to-grid operations has been the subject of debate. A common shortcoming of most of the previous studies has been a proper accounting of Lithium-ion battery degradation in the development of business models. Very recently, papers on the viability of V2G were published for which the detailed account of battery degradation resulted in what appeared to be two ostensibly contradictory conclusions. In this paper, the authors of these two major studies jointly reconcile their previous conclusions by providing clarity on how methodologies to manage battery degradation can reliably extend battery life. The paper also reviews the associated technology and policy implications of better managing battery use in vehicle and electrical grid applications.
Upgrading the internal combustion engine (ICE) driven cars to the electric vehicles (EVs) offers the opportunity to reduce the fossil fuel consumption, emission rates and total driving costs. However, the large scale utilization of the EVs introduces a stochastic load demand to the power grid. The effect of EVs charging demand on the distribution network operation should be investigated properly. This paper proposed a novel model to study the effects of power exchange between the grid and EVs on the power system demand profile, the operation stability index, and the reliability indices. To this end, the operation instability indices are introduced by the range and standard deviation of the load factor of the network components to evaluate the system stability. Further, the CAIFI, 1 SAIDI, 2 SAIFI, 3 and ASAI 4 reliability indices are calculated for various vehicle-to-grid (V2G) and grid-to-vehicle (G2V) power level to estimate the impact of different level of power exchange on system reliability. We introduced an EV charging scheduling approach which considers the specification of Li-Ion battery and the limitations for increasing battery life. The power exchange profile for V2G is also calculated using the constant power method to discharge the energy at different levels for times which cars are parked at the workplace. Due to the stochastic nature of EVs, the minimal path method is used to compute the stability and reliability parameters and the backward–forward algorithm is used to load flow analysis. The proposed model is evaluated via modified IEEE 33-bus test system.
Accurate battery health modeling allows one to make better design decisions, enables health conscious control, and allows for feed-forward State of Health estimation. However, experiments are necessary in order to obtain and validate these models. Unfortunately, battery health experiments are costly in terms of time, person-hours, and equipment. This makes it extremely important to minimize the number of experimental iterations.This paper aims to minimize time and expense of experiments while maximizing information gathered by bridging an important gap between the Optimal Experimental Design (OED) and the battery health experimental/modeling literature. We demonstrate how to apply static OED methods to a battery aging experiment. This allows us to select a set of Constant Current Constant Voltage (CCCV) cycles that maximizes the amount of information gathered — in turn allowing us to better identify the health model parameters. The CCCV cycling is carried out in a laboratory using 14 LiFePO4 cells (10 for fitting and 4 for validation). Each of these cells undergoes 429 days of battery health cycling. Results from these experiments include: a model of battery capacity fade based on voltage and current, battery health dependence on voltage, and a lack of power fade under the cycling conditions. The use of OED to coordinate our model form and experiment helped to ensure a fruitful model resulted when processing the collected data. Based on this success we suggest a generalized framework for Optimal Battery Health Model Experiments (OBHME), which allows one to apply OED to a variety of related problems.
Electric vehicles (EVs), which are eco-friendly and energy-efficient, create an alternative solution to achieve the sustainable and low-emission traffic system when coupled with the renewable energy sources. EVs can serve as distributed energy storage devices to provide vehicle-to-grid (V2G) services for power grids. However, the extra battery degradation would be incurred for EVs. In this context, it is essential to investigate the economic viability of EVs to offer V2G services. It should be noted that few attentions are given to the economic evaluation of EV aggregators participating in the current electricity market framework for the falling battery costs. Herein, the EV aggregator is a new entity for employing large-scale EVs to provide V2G services in electricity markets to explore business opportunities. In this paper, in order to gain the optimal market participation strategy of EV aggregators, an optimization model is formulated with the target of the profit maximization while considering the battery degradation costs. After that, the generalized reduced gradient (GRG) method is used to solve this nonlinear programming problem. Moreover, the New York competitive market is taken as the case study for the economic evaluation. Results reveal that it is highly likely that EV aggregators operate at a loss under the current battery costs; however, with the decrease of battery costs, there will be huge opportunities for EV aggregators to employ EVs to earn profits in electricity markets in the near future.
Nowadays, several countries have adopted an energy transition policy to achieve carbon targets and decarbonize transport while improving their electricity mixes. Electric vehicles are ubiquitous, considering its role in the energy transition as a promising technology for large-scale storage of intermittent power generated from renewable energy sources. However, the widespread adoption and commercialization of EV remain linked to policy measures and government incentives. Here in this work, we review the current bottlenecks and key barriers for large-scale development of electric vehicles. First, the impact of massive integration of electric vehicles is analysed, and the energy management tools of electric energy storage in EVs are provided. Then, the variety of services that EVs may provide is investigated. We also, highlight how the optimal placement and sizing of EV charging infrastructure can plays a crucial role in electric vehicle development. The different methods for Li-ion battery states estimation and cells characterization are outlined. Furthermore, we present the different incentives to accelerate EVs adoption. And finally, we provide insightful suggestions and policy recommendations for future studies. The work presented in this paper will be very beneficial for policymakers seeking to promote electric mobility, and advance sustainable EV technologies.
The escalation in the usage of conventional fuel in the transportation sector resulted in rapid depletion of the same. Thus, the past decade saw the electrification of the transportation division as the primary research area. It has been seen in the past few years that Electric Vehicles (EV) are displacing the internal combustion engine at a rapid pace. The escalation in EV density on the road caused a substantial adverse effect on the existing electric grid and led to grid reliability issues. With an increase in the charging station to cater to Electric Vehicle's needs, some countermeasures are required to be taken to overcome the adverse effects. A comprehensive review is plotted concerning the current EV scenario, charging infrastructure, EV impacts, and Electric Vehicles optimal allocation provisioning in this paper. This paper especially presents the study on the optimal allocation of rapid charging stations based on economic benefits and grid impacts. Adoption challenges that are being faced are also discussed. In contrast, future trends in the field, such as the procurement of energy from renewable energy sources and the benefit of the vehicle to grid technology, are presented and summarized.
Vehicle-to-grid (V2G) technology could turn electric vehicles (EVs) into a potentially valuable solution to the problem of increased load demand caused by large-scale EV integration. Successful market penetration of V2G relies not only on developing the technology itself, but also on EV drivers' willingness to participate in this technology. This paper aims to explore Dutch EV drivers' preferences for participating in V2G contracts. In particular, we conduct a context-dependent stated choice experiment to examine the impact of EV recharging technology on the V2G contract preferences. Two contexts have been designed: the current EV recharging time and fast recharging. Our results show that in the context of current recharging time, Dutch EV drivers in general prefer not to participate in V2G contracts, while the opposite is true in the context of fast recharging. With regard to specific V2G contract attributes, Dutch EV drivers are most concerned about ‘discharging cycles’. Also important to them is ‘the guaranteed minimum battery level’, but its importance drops significantly in the fast charging context. In addition, ‘monthly remuneration’ and ‘plug-in time’ also influence people's preferences for adopting V2G. From these findings, we draw the implications for the aggregator and policy makers.
Electric vehicles are considered as additional loads to the power grid and may pose possible threats to the power grid reliability by overloading the grid equipment, disturbing the grid voltage stability and injecting harmonics into the power grid. Nonetheless, electric vehicles can also provide supports to the power grid through Vehicle-to-Grid application by discharging battery energy into the power grid. This paper presents an optimal priority-based Vehicle-to-Grid scheduling with the objective to minimize the grid load variance. An optimal strategy was developed to optimize the amount of charging/discharging power based on the electric vehicle battery's state-of-charge. This study desires to find a central point which can benefit power utility and electric vehicle users. The algorithm can operate in three modes, which are valley filling, peak load shaving and priority charging. The charging of the electric vehicle can be performed in all three modes, as long as the charging of electric vehicle is required. Meanwhile, discharging of the electric vehicle only occurs during peak load shaving mode. To ensure the practicability of this study, numerous constraints were considered and the study was conducted in a commercial-residential area with electric vehicle mobility of 1300. The results indicated that the algorithm was able to minimize the grid load variance while prioritizing the electric vehicle with a low percentage of state-of-charge. The original maximum variation between peak loading and off-peak loading measured at 5 MW was effectively reduced to 1.5 MW following the deployment of the proposed algorithm.
Electric Vehicles (EVs) portray the important role in reduction of greenhouse gases and fuel utilization. The spike in number of EVs put large burden of power on grid system. This enormous power demand causes serious issues on the performance of power system and can leads to power failure. Optimal management strategies are required to alleviate such issues and to maintain the continuous supply of power. Due to integration of EVs various issues related to grid system are reviewed briefly in this paper. This paper reviews different management strategies to minimize the impacts of integration of EVs into grid system. Decentralized coordination helps to reduce load variability and stability issue of grid due to EVs but it needs accurate forecast of EVs travelling pattern. Central coordination reduces load variance, voltage variations, power losses, computational complexity and helps in determining the EVs charging location but it has less customer stratification. Integration of renewables reduces the burden on local grid, optimizes the production cost and enhances the charging capacity but it has intermittent power supply. EVs charging functioning reduce the power losses and waiting time but require huge investments. Public policies maximize the overall profit but it requires proper load managements. Among these methods it is found that centralized coordination can be more effective in solving EVs integration issues. The optimal power, energy capacity and location of EVs in centralized coordination can accurately found by optimizing the objective functions. Centralized coordination becomes more effective to resolve the EVs issues when addition of smooth power from renewables is included in the system.
The uncoordinated charging of large amounts of electric vehicles (EVs) can lead to a substantial surge of peak loads, which will further influence the operation of power system. Therefore, this study proposed a coordinated charging scheduling method for EVs in microgrid to shift load demand from peak period to valley period. In the proposed method, the charging mode of EVs was selected based on a charging urgency indicator, which can reflect different charging demand. Then, a coordinated charging scheduling optimization model was established to minimize the overall peak-valley load difference. Various constraints were considered for slow-charging EVs, fast-charging EVs, and microgrid operation. Furthermore, Monte Carlo Simulation (MCS) was used to simulate the randomness of EVs. The results have shed light on both the charging modes selection for EV owners and peak shaving and valley filling for microgrid operation. As a result, this model can support more friendly power supply-demand interaction to accommodate the increasing penetration of EVs and the rapid development of flexible microgrid.
Without any doubt, the environmental issues are the top worries between all the nations in the current century. According to the recent studies, the researchers have shown that the transportation fleet is one of the biggest sources of emission. The penetrating the renewable energy sources (RESs) and electric vehicles (EVs) are the green solutions to decrease the current environmental issues. Due to intermittent nature of RESs and high investment costs of developing EVs’ infrastructure, tendency for using them is under the predicted estimations. In this paper, by analyzing a precise and comprehensive literature review, we consider all aspects of implementing the EVs especially their supporting roles for the grid in vehicle to grid system (V2G). Moreover, we study the integration of the electrified fleet with RESs in smart grid and evaluate their possible impacts on the power network. In addition, we count the advantages and disadvantages of implementing the V2G system on the power network. The main purpose of this paper is analyzing the influences of the V2G system on the power grid in four main subjects and classifying them based on their proposed methodology for the future studies. However there are some review papers related to this topic, this field of study suffers a lack of clear direction for future studies and researchers and also a comprehensive analysis about the V2G-related articles is still missing. Finally, an analysis and survey of the last two decades of scholarly literature and projects in this field of study from 2004 to March 2019 is presented. The results show that a limited number of articles have conducted to investigate the social aspects of implementation of V2G system. In addition, however, there are many researches about integration of the V2G system with RESs and smart grid; a few of them use the real data for estimating the availability of RESs in each hour of day.
Under the new climate-change regime, electric vehicles (EVs) have received particular attention for their ability to help mitigate greenhouse gas emissions. The government is looking to implement a vehicle-to-grid (V2G) service for EV use. The present study estimates the economic value of a V2G service, adopting the contingent valuation approach. An online contingent valuation oriented survey of 1007 interviewees was conducted for deriving their willingness-to-accept for the service. The mean willingness-to-accept estimate was achieved as KRW 9821 (USD 8.83) per month, per vehicle; thus, the estimated annual benefit amounted to KRW 117,852 (USD 106.01). The findings can offer a valuable guideline for determining the economic feasibility of a V2G service. From a management perspective, the results can help primary stakeholders decide the optimal price level for that service.
Plug-in electric vehicles (PEV) have gained popularity to support environmental sustainability and reach net-zero emission goals. However, accommodating large numbers of PEVs is a complex problem as concurrent PEV demand significantly increases peak demand and stresses supporting network elements. In this paper, we present a large-scale PEV charging lot equipped with an on-site storage. Power drawn from the grid is utilized to meet customer demand and charge the storage unit which, in return, is employed to lower peak load and demand charges. By considering the probabilistic nature of the customer demand, the proposed architecture is modelled by a Markov-modulated Poisson Process and a matrix-geometric based algorithm is developed to solve the associated capacity planning problem. Station outage probability (defined as the probability of not serving PEV demand) is used as the main metric to size station resources. Case studies show that by accounting for the statistical variations in customer demand, the power required for the station is significantly less than the sum of chargers’ rated power. In addition, on-site storage can considerably reduce the stress on the supporting grid components and lower stations’ running cost.
Today in developed megacities, municipal waste incinerators are a practical solution although they require a relatively high initial investment. On the other hand, E-Transport is growing in metropolitans along with the Renewable Energy Sources (RES). This study proposes an Urban Micro Grid (UMG) consisting of a Waste-to-Energy Combined Heat and Power generation unit (WtE-CHP) and series of Plugin Electric Vehicles (PEV). The main purpose is to provide ancillary services through the incorporation of PEVs as fast-responsive storages. The parking lots may aggregate to form PEV clusters and make bilateral contracts with WtE-CHP to be able to participate in the regulating power markets. A Crow Search Algorithm (CSA) is developed for the UMG operation. In addition, a data analysis section is provided focusing on the behavior of urban drives to extract the realistic probabilities for PEVs available during the daytime. Moreover, the power market of Denmark east (DK2) is considered for the case study of Copenhagen. The results confirm that in case the UMG succeeds in selling the products in the regulating up market, the economic value per MW is remarkably enhanced and the total profit is escalated.
The accelerating energy demand, growing concern regarding global warming and climate change has paved the path of electrification of the transport sector. Large scale adoption of Electric Vehicles (EVs) call for availability of sustainable and easily accessible charging infrastructure. The sporadic energy demand, different battery storage capacity and diverse penetrating patterns of electric vehicles have significantly raised the load elasticity on a power grid. Smart-grid environment promises to assist the addition of EVs into national grids by enabling both EV-charging and discharging (G2V and V2G) load. This will modify the load profile and reduce cost.This paper discusses comprehensively three basic infrastructures by which charging of EVs can be done. These infrastructures are studied and compared on the basis of some parameters. It has been found that distributed infrastructure shows best results for the charging of electric vehicles. The other two infrastructures prove costlier and increase power demand. Also, this paper examines three specific smart charging strategies and the impact of each strategy on the power system load profile and realization cost. Simulation results establish the superiority of smart charging over dumb charging.
Electric vehicles (EVs) offer a significant potential towards developing transportation systems with low carbon footprint. However, a proper accommodation of EVs poses significant challenges to distribution system planning and operations. This paper aims to investigate EVs scheduling strategies with cost benefit analysis (CBA) to obtain optimal planning scheme. EVs can either behave as load or as distributed energy resource, a concept referred to as vehicle to grid (V2G). A V2G capable vehicle can offer active power support and reactive power support to the distribution system. To maximize the benefits of integrating EVs in the distribution system, charging of EVs needs to be coordinated with the available V2G technology. In this study, two scheduling strategies are implemented considering active power dispatch (APD) and reactive power dispatch (RPD) from the EVs. The objective of both the strategies is to minimize losses in the system by utilizing V2G operation of the EVs. APD based strategy minimize losses by optimal charging and discharging of the EVs. On the other hand, RPD based strategy minimize losses by optimal charging and reactive power injection from the EVs. Furthermore, cost and benefit analysis of developed EVs scheduling strategies is presented from the planning perspective. Finally, the constructive influence of distribution system reconfiguration (DSR) is evaluated on operation and planning of the system with two different scheduling strategies. Simulations are conducted on a 33-bus distribution system to demonstrate the effectiveness and feasibility of the proposed approach.
Photovoltaics (PV) and electric vehicles (EVs) are two emerging technologies often considered as cornerstones in the energy and transportation systems of future sustainable cities. They both have to be integrated into the power systems and be operated together with already existing loads and generators and, often, into buildings, where they potentially impact the overall energy performance of the buildings. Thus, a high penetration of both PV and EVs poses new challenges. Understanding of the synergies between PV, EVs and existing electricity consumption is therefore required. Recent research has shown that smart charging of EVs could improve the synergy between PV, EVs and electricity consumption, leading to both technical and economic advantages. Considering the growing interest in this field, this review paper summarizes state-of-the-art studies of smart charging considering PV power production and electricity consumption. The main aspects of smart charging reviewed are objectives, configurations, algorithms and mathematical models. Various charging objectives, such as increasing PV utilization and reducing peak loads and charging cost, are reviewed in this paper. The different charging control configurations, i.e., centralized and distributed, along with various spatial configurations, e.g., houses and workplaces, are also discussed. After that, the commonly employed optimization techniques and rule-based algorithms for smart charging are reviewed. Further research should focus on finding optimal trade-offs between simplicity and performance of smart charging schemes in terms of control configuration, charging algorithms, as well as the inclusion of PV power and load forecast in order to make the schemes suitable for practical implementations.
The increasing integration of electric vehicles (EVs) is adding higher future potentials for the smart grid because the residual energy stored in EV batteries can be discharged to support the grid when needed. However, the stochasticity of EV user behaviors pose challenges to the regulators of distribution systems. How the regulators decide upon a control strategy for the vehicle to grid and how EV users respond to the strategy will significantly influence the variation of load profiles in the planning horizon. In this paper, a comprehensive cost analysis is performed to obtain the optimal planning scheme, considering the variation in EV penetration, charging preference, and customer damage cost. The economics and stability of the planned distribution system are assessed with real-world travel records and cost statistics to quantitatively show the effectiveness of the optimization algorithm and the importance of user behavior concern.
Coordinated charging can utilize the properties of electric vehicles (EVs) to obtain various benefits. However, there are two major challenges, viz. the uncertainty of EV charging behaviors and the overlong solving time for the optimal solutions in the charging scheduling problem of large-scale EVs. It is almost infeasible to precisely predict the charging information of EVs due to the uncertainty of their mobility as transportation tools. In order to tackle this issue, the real-time charging scheduling method is employed in this paper. Even so, the computational complexity is crucially important in the real-time scheduling methods since the charging strategies of large-scale EVs must be acquired in a short time. Hence, a high efficient methodology is proposed for EV real-time scheduling based on the definition of capacity margin index and charging priority index. Finally, the simulation results show that the proposed scheduling method has a significant superiority over the uncoordinated charging in the regard of relieving the demand stress on the power system. Moreover, the complexity analysis demonstrates that the proposed method has near-linear complexity so that it can acquire the optimal real-time charging scheme in a rather shorter time than other methods.
The risk of accelerated electric vehicle battery degradation is commonly cited as a concern inhibiting the implementation of vehicle-to-grid (V2G) technology. However, little quantitative evidence exists in prior literature to refute or substantiate these concerns for different grid services that vehicles may offer. In this paper, a methodology is proposed to quantify electric vehicle (EV) battery degradation from driving only vs. driving and several vehicle-grid services, based on a semi-empirical lithium-ion battery capacity fade model. A detailed EV battery pack thermal model and EV powertrain model are utilized to capture the time-varying battery temperature and working parameters including current, internal resistance and state-of-charge (SOC), while an EV is driving and offering various grid services. We use the proposed method to simulate the battery degradation impacts from multiple vehicle-grid services including peak load shaving, frequency regulation and net load shaping. The degradation impact of these grid services is compared against baseline cases for driving and uncontrolled charging only, for several different cases of vehicle itineraries, driving distances, and climate conditions.
Over the lifetime of a vehicle, our results show that battery wear is indeed increased when vehicles offer V2G grid services. However, the increased wear from V2G is inconsequential compared with naturally occurring battery wear (i.e. from driving and calendar ageing) when V2G services are offered only on days of the greatest grid need (20 days/year in our study). In the case of frequency regulation and peak load shaving V2G grid services offered 2 hours each day, battery wear remains minimal even if this grid service is offered every day over the vehicle lifetime. Our results suggest that an attractive tradeoff exists where vehicles can offer grid services on the highest value days for the grid with minimal impact on vehicle battery life.
In expectation of extensive usage of electric vehicles (EVs) in the near future, vehicle-to-grid (V2G) system is envisioned to be a key component of the smart grid, and it has demonstrated great potential in providing valuable ancillary services such as load balancing, regulation, and reserves. The success of a V2G system largely depends on a credible incentive scheme to motivate a huge number of EVs to participate, but the side effect is that EVs in V2G may suffer from privacy risks concerning their whereabouts. So far little has been done to address the privacy threat, and existent work is inefficient in computation and communication and/or provides defective protection. In this paper, we propose a privacy-preserving solution for V2G communications known as PRAC (Privacy via Randomized Anonymous Credentials). As a full-fledged security protocol suite, PRAC features not only anonymity and untraceability for EVs in authentication as well as service rewarding, but also rewarding fairness and non-repudiation. Thorough analysis reveals that PRAC is secure and is also cost-effective. Compared with the V2G literature, this paper features a prototype implemented on commodity hardware and free software. Extensive experiments demonstrate that PRAC is likely to be a promising solution for any modern electric vehicle.
The need to reduce greenhouse gas emissions and fossil fuel consumption has increased the popularity of plug-in electric vehicles. However, a large penetration of plug-in electric vehicles can pose challenges at the grid and local distribution levels. Various charging strategies have been proposed to address such challenges, often separately. In this paper, it is shown that, with uncoordinated charging, distribution transformers and the grid can operate under highly undesirable conditions. Next, several strategies that require modest communication efforts are proposed to mitigate the burden created by high concentrations of plug-in electric vehicles, at the grid and local levels. Existing transformer and battery electric vehicle characteristics are used along with the National Household Travel Survey to simulate various charging strategies. It is shown through the analysis of hot spot temperature and equivalent aging factor that the coordinated strategies proposed here reduce the chances of transformer failure with the addition of plug-in electric vehicle loads, even for an under-designed transformer while uncontrolled and uncoordinated plug-in electric vehicle charging results in increased risk of transformer failure.
Smart charging systems for battery electric vehicles (BEVs) are one promising smart grid technology that has the potential to help balance energy supply and demand. In the present study, we aimed to investigate users' real-life experiences with a smart charging system and their evaluation of it. In a 5-month field trial, 10 BEV drivers compared conventional BEV charging with smart charging. Via smartphone application, users could modify settings which determined the charging process (e.g., departure times). Before and after experiencing the prototype system, users' motivation, attitudes, willingness to use smart charging and charging behavior were assessed via interviews and questionnaires. Furthermore, participants reported how they experienced and integrated the smart charging system. Results showed that users were motivated and positive about the system at both points of data collection. On average, users agreed that the system is suitable for daily life, reliable and trustworthy. They were willing to use smart charging before and after testing it, but some participants stated that reliability of the system should be improved. In sum, results indicate that a smart charging system like the one implemented in this study is assimilable in everyday life and provide valuable indications for further development of smart charging systems.
Day ahead optimization of an electric vehicle fleet providing ancillary services in the Los Angeles Air Force Base vehicle-to-grid demonstration
- DeForeast
An extended simplex method
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