Willingness to pay for vehicle-to-grid (V2G) electric vehicles and their contract terms

Vehicle-to-grid (V2G) electric vehicles can return power stored in their batteries back to the power grid and be programmed to do so at times when the grid needs reserve power. Since providing this service can lead to payments to owners, it effectively reduces the life-cycle cost of owning an electric vehicle. Using data from a national stated preference survey, this paper presents a study of the potential consumer demand for V2G electric vehicles. In a choice experiment, 3029 respondents compared their preferred gasoline vehicle with two V2G electric vehicles. The V2G vehicles were described by a set of electric vehicle attributes and V2G contract requirements such as “required plug-in time” and “guaranteed minimum driving range”. The contract requirements specify a contract between drivers and a power aggregator for providing reserve power to the grid. Our findings suggest that the V2G concept is most likely to help EVs on the market if power aggregators operate either on pay-as-you-go basis (more pay for more service provided) or provide consumers with advanced cash payment (upfront discounts on the price of EVs), rather than imposing fixed requirements on participants.     

Vehicle-to-grid power implementation: From stabilizing the grid to supporting large-scale renewable energy

Vehicle-to-grid power (V2G) uses electric-drive vehicles (battery, fuel cell, or hybrid) to provide power for specific electric markets. This article examines the systems and processes needed to tap energy in vehicles and implement V2G. It quantitatively compares today's light vehicle fleet with the electric power system. The vehicle fleet has 20 times the power capacity, less than one-tenth the utilization, and one-tenth the capital cost per prime mover kW. Conversely, utility generators have 10–50 times longer operating life and lower operating costs per kWh. To tap V2G is to synergistically use these complementary strengths and to reconcile the complementary needs of the driver and grid manager. This article suggests strategies and business models for doing so, and the steps necessary for the implementation of V2G. After the initial high-value, V2G markets saturate and production costs drop, V2G can provide storage for renewable energy generation. Our calculations suggest that V2G could stabilize large-scale (one-half of US electricity) wind power with 3% of the fleet dedicated to regulation for wind, plus 8–38% of the fleet providing operating reserves or storage for wind. Jurisdictions more likely to take the lead in adopting V2G are identified.     

The many factors that affect the success of regulatory mechanisms designed to foster investments in energy efficiency

A utility??s profit-maximizing level of investment in energy efficiency or demand-side management (DSM) programs and mix of programs is affected by natural load growth, the frequency of rate cases, program costs, and the structure of any mechanism designed to either compensate the utility for foregone profits or sever the link between sales and profits. Under a range of reasonable assumptions, decoupling can incent a utility to invest in DSM. However, a utility experiencing high natural load growth and little inflation is likely to resist the imposition of a decoupling mechanism, as it would tend to lower profits. A utility with low growth in per-customer sales will tend to favor decoupling, as it will tend to lead to higher profits than under traditional regulation. The results presented here are quite sensitive to the assumptions made regarding natural load growth, regulatory lag, the frequency of price changes, price elasticity of demand, and other factors. This suggests that there is not a single approach to promoting energy efficiency without penalizing utility profits that will work in all situations for all utilities.     

Managing peak loads in energy grids: Comparative economic analysis

One of the key issues in modern energy technology is managing the imbalance between the generated power and the load, particularly during times of peak demand. The increasing use of renewable energy sources makes this problem even more acute. Various existing technologies, including stationary battery energy storage systems (BESS), can be employed to provide additional power during peak demand times. In the future, integration of on-board batteries of the growing fleet of electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) into the grid can provide power during peak demand hours (vehicle-to-grid, or V2G technology).This work provides cost estimates of managing peak energy demands using traditional technologies, such as maneuverable power plants, conventional hydroelectric, pumped storage plants and peaker generators, as well as BESS and V2G technologies. The derived estimates provide both per kWh and kW year of energy supplied to the grid. The analysis demonstrates that the use of battery storage is economically justified for short peak demand periods of <1 h. For longer durations, the most suitable technology remains the use of maneuverable steam gas power plants, gas turbine,reciprocating gas engine peaker generators, conventional hydroelectric, pumped storage plants.     

The cost of uncertainty in capacity expansion problems

The goals of this paper are to present a two‐stage programming model for the capacity expansion problem under uncertainty of demand and explore the impact of this uncertainty on cost. The model is a mixed integer nonlinear programming (MINLP) model with the consideration of uncertainty used to maximize the expected present value of utility profits over the planning horizon, under the constraints of rate of return and reserve margin regulation. The results reveal that the uncertainty harms the profit seriously. In this paper both microeconomics and mathematical programming are used to analyse the problem. We try to observe the economic behaviour of the utility with uncertainty involved. We also investigate the influence on the cost of uncertainty of each economic parameter. Copyright © 1999 John Wiley & Sons, Ltd.     

A price‐regulated electric vehicle charge‐discharge strategy for G2V,V2H,and V2G

Electric vehicles (EVs) and smart grids are gradually revolutionising the transportation sector and electricity sector respectively. In contrast to unplanned charging/discharging, smart use of EV in home energy management system (HEMS) can ensure economic benefit to the EV owner. Therefore, this paper has proposed a new energy pricing controlled EV charging/discharging strategy in HEMS to acquire maximum financial benefit. EV is scheduled to be charged/discharged according to the price of electricity during peak and off‐peak hours. In addition, two different types of EV operation modes, ie, grid‐to‐vehicle (G2V) in off‐peak time and vehicle‐to‐home (V2H) in on‐peak time are considered to determine comparative economic benefit of planned EV charging/discharging. The real load profile of a house in Melbourne and associated electricity pricing is selected for the case study to determine the economic gain. The simulation results illustrate that EV participating in V2H contributes approximately 11.6% reduction in monthly electricity costs compared with G2V operation mode. Although the facility of selling EV energy to the grid is not available currently, the pricing controlled EV charging/discharging presented in the paper can be used if such facility becomes available in the future.     

Aggregator-based demand response mechanism for electric vehicles participating in peak regulation in valley time of receiving-end power grid

With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles (EVs), an aggregator-based demand response (DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator (ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.     

Examination of optimum benefits of customer and LSE by incentive and dynamic price-based demand response

ABSTRACT

The balancing approach of electricity generation and consumption is an essential part of a reliable power system. The mismatch between supply and demand may also cause fluctuation in the power system. This study proposes an incentive and penalty-based demand response (I&P-DR) program for improving the profitability of both LSE and customers. First, we use a parameter that weighs the financial benefits of LSE and customers and provides considerable economic benefits to both sides. Second, an incentive and penalty (I&P) price scheme have been employed to recompense and penalize customers and reduce the electricity demand at peak hours. Finally, the study analyzes the importance of (I&P-DR) and its impact on customers’ sensitivity during peak intervals. Simulation results showed that the flexibility to consumption can be brought through the application of the proposed (I&P-DR) program and also provide the financial benefits to both, customers and LSEs.     

Vehicle-to-grid power fundamentals: Calculating capacity and net revenue

As the light vehicle fleet moves to electric drive (hybrid, battery, and fuel cell vehicles), an opportunity opens for “vehicle-to-grid” (V2G) power. This article defines the three vehicle types that can produce V2G power, and the power markets they can sell into. V2G only makes sense if the vehicle and power market are matched. For example, V2G appears to be unsuitable for baseload power—the constant round-the-clock electricity supply—because baseload power can be provided more cheaply by large generators, as it is today. Rather, V2G's greatest near-term promise is for quick-response, high-value electric services. These quick-response electric services are purchased to balance constant fluctuations in load and to adapt to unexpected equipment failures; they account for 5–10% of electric cost—$ 12 billion per year in the US. This article develops equations to calculate the capacity for grid power from three types of electric drive vehicles. These equations are applied to evaluate revenue and costs for these vehicles to supply electricity to three electric markets (peak power, spinning reserves, and regulation). The results suggest that the engineering rationale and economic motivation for V2G power are compelling. The societal advantages of developing V2G include an additional revenue stream for cleaner vehicles, increased stability and reliability of the electric grid, lower electric system costs, and eventually, inexpensive storage and backup for renewable electricity.     

基于V2G的配电网负荷优化策略研究

基于电动汽车与电网互动（V2G）系统,提出一种电动汽车参与配电网负荷优化调节的分析模型。设计了V2G参与负荷调节的控制系统框架,以配电网负荷曲线波动方差最小为目标,考虑电动汽车用户的充电需求、动力电池的充电约束和传输线的功率约束构建了优化分析模型,并采用遗传算法（GA）分析计算,获得负荷优化后的负荷曲线和电动汽车的充放电时间。实例仿真验证了该优化控制法的有效性。     

国内石油公司在天然气发电领域应有所作为

从我国电力消费逐年大幅增加,远大于能源消费增幅,我国电力企业长期以来具有收益稳定、持续盈利能力强的特点等几方面分析了国内石油公司参与天然气发电业务的必要性。指出,在我国电力需求增长潜力巨大、燃气发电有很大潜力、以及大规模开发和利用天然气资源的大好形势下,国内石油公司作为天然气供应者和电力消费大户,应借鉴国际石油公司的经验,积极主动地培育天然气发电市场,通过优化资源配置、与电力公司结成天然气利用同盟军、争取得到更多的政策支持等措施,推进天然气发电项目的落实,促进我国天然气发电事业的发展。     

Improving energy efficiency and smart grid program analysis with agent-based end-use forecasting models

Electric utilities and regulators face difficult challenges evaluating new energy efficiency and smart grid programs prompted, in large part, by recent state and federal mandates and financial incentives. It is increasingly difficult to separate electricity use impacts of individual utility programs from the impacts of increasingly stringent appliance and building efficiency standards, increasing electricity prices, appliance manufacturer efficiency improvements, energy program interactions and other factors. This study reviews traditional approaches used to evaluate electric utility energy efficiency and smart-grid programs and presents an agent-based end-use modeling approach that resolves many of the shortcomings of traditional approaches. Data for a representative sample of utility customers in a Midwestern US utility are used to evaluate energy efficiency and smart grid program targets over a fifteen-year horizon. Model analysis indicates that a combination of the two least stringent efficiency and smart grid program scenarios provides peak hour reductions one-third greater than the most stringent smart grid program suggesting that reductions in peak demand requirements are more feasible when both efficiency and smart grid programs are considered together. Suggestions on transitioning from traditional end-use models to agent-based end-use models are provided.     

A 10 year installation program for wave energy in Ireland: A case study sensitivity analysis on financial returns

This paper is a case study which examines the finances of a proposed installation schedule of 500 MW of a wave energy device type in Ireland. The novel aspects of the analysis were the modelling of the combined influence of learning curves, supply and demand rates as well as future cost of cash on the phased deployment over the 10 years. There are many studies which have examined the economics of renewable energy project installations, including wave energy. However, there is lack of research in the impact and implications of phased installations over time, especially when using a feed-in tariff (FIT) revenue mechanism. The goal of the study was twofold. The first goal was to assess the viability of the current Irish feed-in tariff within the context of a phased installation program for the wave energy device chosen for the study, and measures required to produce a positive rate of return. The second aim was to assess the impact of learning curve, supply/demand curves and future cost of cash on phased project installations. The wave energy device chosen for the study was the Pelamis P1 and the economic model used was NAVITAS, created by HMRC. The assessment was based on net present value and internal rate of return. The wave energy data for the study was 2007 from M4 of the west coast of Ireland, obtained from Marine Institute, Ireland. Results from the case study indicated that the high initial costs for the case study wave energy device had a significant impact on financial returns. Results of the case study indicate that higher tariffs may be required than the current Irish, static, nonindex linked, FIT to foster positive returns for future wave energy projects, especially if phased installations are considered, which are susceptible to future cash and supply/demand factors. The large range of sensitivity factors assessed in the case study demonstrates the vulnerable nature of these large scale projects when estimating financial returns. Further studies will be required to assess multiple device types, update initial costs for wave energy devices, provide reliable power matrices, as well as appropriate learning curve and supply demand rates.     

A multi-model method to assess the value of power-to-gas using excess renewable

Power-to-Gas (P2G) is a process that produces a gas from electricity, which is most commonly hydrogen via electrolysis. While some studies have considered hydrogen as a power-to-power storage vector, it could also be used as a fuel across the energy system, for example for transport or heat generation. Here, two energy models are used to explore the potential contribution of P2G as a cost-effective source of hydrogen, particularly for future energy systems with high variable renewable energy (VRE) in which there are occasional periods when electricity supply exceeds demand. A detailed electricity system model is iterated with a multi-vector energy system model using a soft-linking approach. This iterative approach addresses shortcomings in each model to better understand the optimal capacity of P2G and the potential economic capture rate of excess VRE. The modelling method is applied to Great Britain in 2050 as a case study. A substantial proportion of excess VRE in 2050 can be captured by P2G, and it is economically competitive compared with alternative sources. Moreover, the effectiveness and economic viability of P2G for reducing excess renewable is robust at even very high levels of renewable penetration.     

Feasibility evaluation of fermentative biomass-derived gas production from condensed molasses in a continuous two-stage system for commercialization

The excessive burning of fossil fuels is one of the main sources of emissions of carbon dioxide (CO₂) which causes the greenhouse effect. The effect could be resulted in climate changes and disorder of our ecosystem. Thus, bioenergy developments will play important roles to help decreasing CO₂ emission for better global environment in the future. In the domain of biohydrogen production, biomass including: cellulose, wastewater and agricultural waste are the main resources to maintain feedstock demand. Developing sustainable energy with sustainable feedstock sources like sugary wastewater by using two-stage biomass-derived gas production system might bring great economic profits to business. In this study, the system will be chosen to testify its sustainability when producing the sugary wastewater to renewable source energy. The commercial potential analysis is derived from the internal rate of return (IRR). The novelty finding of this study, as the result showed, found out that the energy recovery is 1.12 times higher than single stage. According to the IRR analysis with the calculated years of 15 years, the IRR is 32.47% that means the system can payback within 3.19 years. Therefore, the feasibility of commercialization potential of biomass-derived gas production system can be verified.     

深化调峰的电动私家车/出租车群组合优化充放电策略

文章提出一种深化调峰的私家车/出租车群组合优化充放电策略,该策略采用蒙特卡洛模拟法模拟私家车、出租车和公交车3种类型电动汽车充电负荷,分析不同类型电动汽车对电网负荷峰谷特性的影响。基于车主意愿差异确定车主对充电价格差和放电电价的响应特性,将电动汽车细分为V0G,V1G,V2G 3种类型,并计算出3种类型电动汽车数量。进而以负荷峰谷差和负荷方差最小为优化目标,决策求解各类型电动汽车充放电起止时刻。仿真算例结果表明:文章所提充放电策略能更好地激励各类型电动汽车积极参与调峰,可进一步减小负荷峰谷差。     

The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review

Peak demand for electricity in North America is expected to grow, challenging electrical utilities to supply this demand in a cost-effective, reliable manner. Therefore, there is growing interest in strategies to reduce peak demand by eliminating electricity use, or shifting it to non-peak times. This strategy is commonly called “demand response”. In households, common strategies are time-varying pricing, which charge more for energy use on peak, or direct load control, which allows utilities to curtail certain loads during high demand periods. We reviewed recent North American studies of these strategies. The data suggest that the most effective strategy is a critical peak price (CPP) program with enabling technology to automatically curtail loads on event days. There is little evidence that this causes substantial hardship for occupants, particularly if they have input into which loads are controlled and how, and have an override option. In such cases, a peak load reduction of at least 30% is a reasonable expectation. It might be possible to attain such load reductions without enabling technology by focusing on household types more likely to respond, and providing them with excellent support. A simple time-of-use (TOU) program can only expect to realise on-peak reductions of 5%.     

Time-averaging period for regulation service

Because electricity is a real-time product, power system operators must adjust generation to match load on a moment-to-moment basis, providing the ancillary service called regulation. But what is meant by moment-to-moment? This article addresses that question by providing background information on the regulation ancillary service and by analyzing short-interval changes in system-level generation and load for four electrical systems. Three systems are large, with peak demands between 10,000 and 20,000 MW, while the fourth system has a peak demand of under 5,000 MW. One of the large systems relies primarily on hydro units for regulation, while the other three systems use fossil units. For each system, the authors obtained 30-second data for 1 or more days on total generation and load. They analyzed these data to see how quickly and with how much lag generation follows load     

An economic analysis of a clean-development mechanism project: a case introducing a natural gas-fired combined heat-and-power facility in a Chinese industrial area

A case study of the installation of a combined heat-and-power (CHP) facility as a potential clean-development mechanism (CDM) project in an industrial area in China was undertaken using a newly developed mathematical programming model. The model was developed to optimize the installation capacity of the CHP under constraints on electricity-and-heat supply and demand balances, etc. Energy cost and emissions of CO₂ and SO_x were also calculated with the model. Parametric surveys were carried out for natural gas and CHP capital prices, which inherently include large uncertainties; the resultant calculations revealed that in some cases the CHP would be voluntarily (i.e., without financial support from an investor's country) introduced in China, and that in some cases the CHP could be certified as a CDM project with financial support by the investor country. In some combinations of parameters, the value of CO₂ emission reduction credit offsets the CHP capital price, although shared allocation of economic profits yielded by the CDM project between the two countries greatly mitigated the restraints on the project, while at the same time qualifying it for the CDM.     

Household electricity demand forecast and energy savings potential for Vientiane,Lao PDR

This paper uses the survey data on household electricity demand from five districts of Vientiane, Lao PDR, for the demand projection up to 2030 using the end-use model. The scenario analysis is used to verify the potential of an energy-saving program by alternating selected appliances with more energy-efficient ones following the labelling standard of Thailand. The demographic structure of electrified households and the energy efficiency of electric appliances are considered as the dominant factors affecting electricity demand. Under the base-case scenario, the total electricity demand of Vientiane increased from 593?GWh in 2013 to 965?GWh in 2030. In the energy efficiency scenario, it is revealed that the appliance standard enhancement program can save total electricity demand in 2030 by 147?GWh (?15.2%), where 117?GWh (?12.1%) of which is contributed by the air conditioner and 30?GWh (?3.1%) by the lighting equipment.