Electric vehicles in imperfect electricity markets: The case of Germany

We use a game-theoretic model to analyze the impacts of a hypothetical fleet of plug-in electric vehicles on the imperfectly competitive German electricity market. Electric vehicles bring both additional demand and additional storage capacity to the market. We determine the effects on prices, welfare, and electricity generation for various cases with different players in charge of vehicle operations. Vehicle loading increases generator profits, but decreases consumer surplus in the power market. If excess vehicle batteries can be used for storage, welfare results are reversed: generating firms suffer from the price-smoothing effect of additional storage, whereas power consumers benefit despite increasing overall demand. Strategic players tend to under-utilize the storage capacity of the vehicle fleet, which may have negative welfare implications. In contrast, we find a market power-mitigating effect of electric vehicle recharging on oligopolistic generators. Overall, electric vehicles are unlikely to be a relevant source of market power in Germany in the foreseeable future.     

Methodology for modelling plug-in electric vehicles in the power system and cost estimates for a system with either smart or dumb electric vehicles

The article estimates the costs of plug-in electric vehicles (EVs) in a future power system as well as the benefits from smart charging and discharging EVs (smart EVs). To arrive in a good estimate, a generation planning model was used to create power plant portfolios, which were operated in a more detailed unit commitment and dispatch model. In both models the charging and discharging of EVs is optimised together with the rest of the power system. Neither the system cost nor the market price of electricity for EVs turned out to be high (36-263 €/vehicle/year in the analysed scenarios). Most of the benefits of smart EVs come from smart timing of charging although benefits are also accrued from provision of reserves and lower power plant portfolio cost. The benefits of smart EVs are 227 €/vehicle/year. This amount has to cover all expenses related to enabling smart EVs and need to be divided between different actors. Additional benefits could come from the avoidance of grid related costs of immediate charging, but these were not part of the analysis.     

Integration of renewable energy into the transport and electricity sectors through V2G

Large-scale sustainable energy systems will be necessary for substantial reduction of CO₂. However, large-scale implementation faces two major problems: (1) we must replace oil in the transportation sector, and (2) since today's inexpensive and abundant renewable energy resources have fluctuating output, to increase the fraction of electricity from them, we must learn to maintain a balance between demand and supply. Plug-in electric vehicles (EVs) could reduce or eliminate oil for the light vehicle fleet. Adding “vehicle-to-grid” (V2G) technology to EVs can provide storage, matching the time of generation to time of load. Two national energy systems are modelled, one for Denmark, including combined heat and power (CHP) and the other a similarly sized country without CHP (the latter being more typical of other industrialized countries). The model (EnergyPLAN) integrates energy for electricity, transport and heat, includes hourly fluctuations in human needs and the environment (wind resource and weather-driven need for heat). Four types of vehicle fleets are modelled, under levels of wind penetration varying from 0% to 100%. EVs were assumed to have high power (10 kW) connections, which provide important flexibility in time and duration of charging. We find that adding EVs and V2G to these national energy systems allows integration of much higher levels of wind electricity without excess electric production, and also greatly reduces national CO₂ emissions.     

Optimal recharging strategy for battery-switch stations for electric vehicles in France

Most papers that study the recharging of electric vehicles focus on charging the batteries at home and at the work-place. The alternative is for owners to exchange the battery at a specially equipped battery switch station (BSS). This paper studies strategies for the BSS to buy and sell the electricity through the day-ahead market. We determine what the optimal strategies would have been for a large fleet of EVs in 2010 and 2011, for the V2G and the G2V cases. These give the amount that the BSS should offer to buy or sell each hour of the day. Given the size of the fleet, the quantities of electricity bought and sold will displace the market equilibrium. Using the aggregate offers to buy and the bids to sell on the day-ahead market, we compute what the new prices and volumes transacted would be. While buying electricity for the G2V case incurs a cost, it would have been possible to generate revenue in the V2G case, if the arrivals of the EVs had been evenly spaced during the day. Finally, we compare the total cost of implementing the strategies with the cost of buying the same quantity of electricity from EDF.     

Robust design of off-grid solar-powered charging station for hydrogen and electric vehicles via robust optimization approach

In this article, a robust optimization approach for designing an off-grid solar-powered charging station is proposed to provide electric vehicles (EVs) with electricity and hydrogen vehicles (HV) with hydrogen. A water electrolyzer (WE) is installed in the system to produce and store hydrogen, which is used by the HVs and fuel cell (FC). During the inaccessibility of the photovoltaic (PV) system to feed the EVs, the FC runs on hydrogen to regenerate electricity. Besides, in case the PV system and FC have power shortage to meet the demand of EVs, a diesel generator contributes to electricity production. There are uncertainties involved in the power profile of the PV system as well as the hydrogen and electric demands of the charging station. The novelty of this paper is to integrate robust optimization as a powerful nonstochastic framework into the mixed-integer linear programming (MILP) of the deterministic model to deal with the uncertainties. The technical and economic results prove that the construction of the charging station by considering the highs level of robustness against the negative impacts of uncertainties leads to higher capacities of the PV system and diesel generator. Consequently, the total annualized cost increases from $ 287,256 in deterministic mode to $ 326,757 in robust mode, by 13.75%.     

Potential impacts assessment of plug-in electric vehicles on the Portuguese energy market

Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs), which obtain their fuel from the grid by charging a battery, are set to be introduced into the mass market and expected to contribute to oil consumption reduction. In this research, scenarios for 2020 EVs penetration and charging profiles are studied integrated with different hypotheses for electricity production mix. The impacts in load profiles, spot electricity prices and emissions are obtained for the Portuguese case study. Simulations for year 2020, in a scenario of low hydro production and high prices, resulted in energy costs for EVs recharge of 20 cents/kWh, with 2 million EVs charging mainly at evening peak hours. On the other hand, in an off-peak recharge, a high hydro production and low wholesale prices' scenario, recharge costs could be reduced to 5.6 cents/kWh. In these extreme cases, EV's energy prices were between 0.9€ to 3.2€ per 100 km. Reductions in primary energy consumption, fossil fuels use and CO₂ emissions of up to 3%, 14% and 10%, respectively, were verified (for a 2 million EVs' penetration and a dry year's off-peak recharge scenario) from the transportation and electricity sectors together when compared with a BAU scenario without EVs.     

The impact of climate change on the electricity market: A review

Climate change will impact electricity markets through both electricity demand and supply. This paper reviews the research on this topic. Whereas there is much that remains unknown or uncertain, research over the last few years has significantly advanced our knowledge. In general, higher temperatures are expected to raise electricity demand for cooling, decrease demand for heating, and to reduce electricity production from thermal power plants. The effect of climate change on the supply of electricity from non-thermal sources shows great geographical variability due to differences in expected changes to temperature and precipitation. Whereas the research frontier has advanced significantly in the last few years, there still remains a significant need for more research in order to better understand the effects of climate change on the electricity market. Four significant gaps in the current research are regional studies of demand side impacts for Africa, Asia, the Caribbean and Latin America, the effects of extreme weather events on electricity generation, transmission and demand, changes to the adoption rate of air conditioning, and finally, our understanding of the sensitivity of thermal power supply to changes in air and water temperatures.     

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.     

Assessment of electric vehicles concerning impacts,charging infrastructure with unidirectional and bidirectional chargers,and power flow comparisons

The advancement and deployment of electric vehicle (EV) technologies are considered as an emergent solution to meet the current and future energy crises. The electrification of transportation systems is a promising approach to green the transportation systems and to reduce the issues of climate change. This paper investigates the present status, latest deployment, and challenging issues in the implementation of EV infrastructure, charging power levels, in conjunction with several charging power topologies, and analyzes EV impacts and prospects in society. In this study, the on‐board and off‐board categories of charging systems with unidirectional and bidirectional power flow comparison are addressed. Moreover, an extensive analysis of unidirectional and bidirectional chargers is presented. Unidirectional charging offers hardware limitation and reduces the interconnection issues. Bidirectional charging provides the fundamental feature of vehicle‐to‐grid technology. Furthermore, the beneficial and harmful impacts of EVs are categorized with remedial measures for harmful impacts and prolific benefits for beneficial impacts.     

A realistic framework to a greener supply chain for electric vehicles

The quantity of electric vehicles in the transport sector has steadily risen over the last 10 years. Most developed countries and China have laid out ambitious plans for electric vehicles penetration. However, there are several challenges that must be addressed on the supply‐chain side of the problem for a successful transition toward an alternative and less environmentally harmful transport system. This study proposes a methodology for the optimal plan and decision making of primary energy sources, electricity generation, electricity distribution to vehicles' charging stations, carbon capture and sequestration, and electric vehicles' charging stations network to satisfy the electricity demand of the overall economy including electric vehicles at a regional/countrywide level under operation and green constraints. The optimization problem was modeled as a mixed integer program in general algebraic modeling system (GAMS). The formulation was employed to propose the upcoming electricity supply chain for electric vehicles in the most populous German state (North Rhine‐Westphalia) in 2025. The optimization show that fossil‐based power still controls the generation in 2025, while carbon capture and sequestration along with higher renewable penetration help meeting the state's greenhouse gases (GHG) emission target. The charging stations network expansion consists of 12 820 charging points mainly alternating current (AC) chargers (22‐kW capacity).     

Distributed generation integrated with thermal unit commitment considering demand response for energy storage optimization of smart grid

This paper deals with an optimal battery energy storage capacity for the smart grid operation. Distributed renewable generator and conventional thermal generator are considered as the power generation sources for the smart grid. Usually, a battery energy storage system (BESS) is used to satisfy the transmission constraints but installation cost of battery energy storage is very high. Sometimes, it is not possible to install a large capacity of the BESS. On the other hand, the competition of the electricity market has been increased due to the deregulation and liberalization of the power market. Therefore, the power companies are required to reduce the generation cost in order to maximize the profit. In this paper, a thermal units commitment program considers the demand response system to satisfy the transmission constraints. The BESS capacity can be reduced by the demand response system. The electric vehicle (EV) and heat pump (HP) in the smart house are considered as the controllable loads of the demand side. The effectiveness of the proposed method is validated by extensive simulation results which ensure the reduction of BESS capacity and power generation cost, and satisfy the transmission constraints.     

Assessing the potential for concentrated solar power development in rural Australia

This paper identifies the potential for concentrated solar power (CSP) to generate electricity in a rural region of Western Australia. A review of policies designed to stimulate the contribution of renewable sources highlights the continued reliance upon fossil fuels to supply current and future electricity needs in Australia. Potential CSP sites are defined in the Wheatbelt region of Western Australia through overlaying environmental variables and electricity infrastructure on a high resolution grid using widely available datasets and standard geographical information system (GIS) software. The analysis confirms that CSP facilities can be sited over large areas of the Wheatbelt which can be tailored to local patterns of supply and demand. The research underlines the necessity to develop a policy regime which actively supports and stimulates CSP in order to capitalize upon its potential to facilitate rural economic development while contributing towards greenhouse gas emission reduction targets.     

Plug-in hybrid vehicle GHG impacts in California: Integrating consumer-informed recharge profiles with an electricity-dispatch model

This paper explores how Plug-in Hybrid Vehicles (PHEVs) may reduce source-to-wheel Greenhouse Gas (GHG) emissions from passenger vehicles. The two primary advances are the incorporation of (1) explicit measures of consumer interest in and potential use of different types of PHEVs and (2) a model of the California electricity grid capable of differentiating hourly and seasonal GHG emissions by generation source. We construct PHEV emissions scenarios to address inherent relationships between vehicle design, driving and recharging behaviors, seasonal and time-of-day variation in GHG-intensity of electricity, and total GHG emissions. A sample of 877 California new vehicle buyers provide data on driving, time of day recharge access, and PHEV design interests. The elicited data differ substantially from the assumptions used in previous analyses. We construct electricity demand profiles scaled to one million PHEVs and input them into an hourly California electricity supply model to simulate GHG emissions. Compared to conventional vehicles, consumer-designed PHEVs cut marginal (incremental) GHG emissions by more than one-third in current California energy scenarios and by one-quarter in future energy scenarios—reductions similar to those simulated for all-electric PHEV designs. Across the emissions scenarios, long-term GHG reductions depends on reducing the carbon intensity of the grid.     

Optimal dispatch of hydrogen/electric vehicle charging station based on charging decision prediction

The hydrogen/electric vehicle charging station (HEVCS) is widely regarded as a highly attractive system for facilitating the popularity of hydrogen and electric vehicles in the future. However, conventional optimal dispatch of HEVCS could lead to poor performance due to the lack of adequate consideration of vehicle charging decision behaviours and neglection of the impacts of different information sources on it. This paper investigates a charging demand prediction method that considers multi-source information and proposes a multi-objective optimal dispatching strategy of HEVCS. First, an information interaction framework of integrated road network, vehicles and HEVCS is introduced. Road network model and HEVCS model are established based on the proposed framework. To improve the flexibility of dispatch, two charging modes are designed, which are intended to guide drivers to adjust their consumption behaviour by electricity price incentives. Furthermore, psychologically based hybrid utility-regret decision model and Weber-Fechner (W–F) stimulus model are developed to reasonably predict drivers' choice of charging stations and charging modes. The daily revenue of HEVCS and the total queuing time of drivers are the objective functions considered in this paper simultaneously. The above multi-objective optimization results that the proposed strategy can effectively improve the benefits of HEVCS and reduce energy waste. Additionally, this paper discusses the results of a sensitivity analysis conducted by varying incentive discount, which reveals the combined benefits of the HEVCS and the vehicles are effectively increased by setting reasonable incentive discounts.     

Medium-term demand for European cross-border electricity transmission capacity

The aim of this paper is to discuss the needs for investment in electricity interconnectors in Europe by 2025. We evaluate the impact of cross-border transmission capacity on dispatch costs, curtailment needs for renewable energy sources (RES), on CO₂ emissions, on hydro storage utilisation and on security of supply (in terms of energy not served). The analysis is performed with EUPowerDispatch, a minimum-cost dispatch model. For the evolution of the electricity generation portfolio and electricity consumption we use the latest Scenario Outlook and Adequacy Forecast of the European Network of Transmission System Operators for Electricity (ENTSO-E). The model results show that the planned additional cross-border transmission capacity between 2010 and 2025 will reduce annual dispatch costs, will have limited impact on the security of supply and will not be a significant cause of variable RES curtailment. However, in case of more RES, it will reduce dispatch costs to a larger extent and will considerably reduce RES curtailment needs, and, if demand grows at the historical rate of 2%, it will be needed to maintain the current level of security of supply. Moreover, our study shows that hydro pumping and storage and cross-border transmission are partly complementary technologies.     

Electrification in Yugoslavia - a progress report

Widespread industrialization and a low initial level of electrification have led to rapid expansion of the Yugoslavian electricity supply industry since the second world war. Here Peter and Lucia Feith consider recent trends in the supply, demand and transmission of electricity in Yugoslavia, and its growing exports to neighbouring countries.     

Sustainability constraints on UK bioenergy development

Use of bioenergy as a renewable resource is increasing in many parts of the world and can generate significant environmental, economic and social benefits if managed with due regard to sustainability constraints. This work reviews the environmental, social and economic constraints on key feedstocks for UK heat, power and transport fuel. Key sustainability constraints include greenhouse gas savings achieved for different fuels, land availability, air quality impacts and facility siting. Applying those constraints, we estimate that existing technologies would facilitate a sustainability constrained level of medium-term bioenergy/biofuel supply to the UK of 4.9% of total energy demand, broken down into 4.3% of heat demands, 4.3% of electricity, and 5.8% of transport fuel. This suggests that attempts to increase the supply above these levels could have counterproductive sustainability impacts in the absence of compensating technology developments or identification of additional resources. The barriers that currently prevent this level of supply being achieved have been analysed and classified. This suggests that the biggest policy impacts would be in stimulating the market for heat demand in rural areas, supporting feedstock prices in a manner that incentivised efficient use/maximum greenhouse gas savings and targeting investment capital that improves yield and reduces land-take.     

Renewable energy potential on brownfield sites: A case study of Michigan

Federal priorities are increasingly favoring the replacement of conventional sources of energy with renewable energy. With the potential for a federal Renewable Electricity Standard (RES) legislation, many states are seeking to intensify their renewable energy generation. The demand for wind, solar, geothermal and bio-fuels-based energy is likely to be rapidly expressed on the landscape. However, local zoning and NIMBYism constraints slow down the placement of renewable energy projects. One area where land constraints may be lower is brownfields; whose development is currently constrained by diminished housing, commercial, and industrial property demand. Brownfield sites have the potential for rapid renewable energy deployment if state and national interests in this area materialize. This study investigates the application of renewable energy production on brownfield sites using Michigan as a case study. Wind and solar resource maps of Michigan were overlaid with the brownfield locations based on estimates of brownfield land capacity. The total estimated energy potential available on Michigan’s brownfield sites is 4320 megawatts (MW) of plate capacity for wind and 1535for solar, equating to 43% of Michigan’s residential electricity consumption (using 30% capacity factor). Estimated economic impacts include over $15 billion in investments and 17,500 in construction and long-term jobs.     

基于智能电网的电动汽车充放电分时电价及引导策略

为了以绿色、环保能源满足全球可持续发展的需求,可再生能源和电动汽车在全球范围内受到广泛推崇.在此情形下,高比例可再生能源发电和大规模电动汽车无序分散接入电网必将导致供求曲线的不稳定.为此,借助云存储技术和智能电网,提出了一种基于供求曲线的电动汽车充放电分时电价,并在制定充放电价格时考虑充电站的空闲率.以实现充电站和用户...     

An energy demand model for a fleet of plug-in fuel cell vehicles and commercial building interfaced with a clean energy hub

This paper presents an energy demand model for a fleet of plug-in fuel cell vehicles and a medium-sized commercial/office building interfaced with a clean energy hub. The approach taken is to model the architecture and daily operation of every individual vehicle in the fleet. A simplified architecture model was developed, with daily operation divided into two periods: charging and travelling. During the charging period, the vehicle charges its batteries and refills its compressed hydrogen tanks. During the travelling period, the vehicle depletes the batteries and hydrogen tanks based on distance travelled. Daily travel distance is generated by a stochastic model. The modeling of the clean energy hub is also presented. The clean energy hub functions as an interface between electricity supply and the energy demand (i.e. hydrogen and electricity) of the vehicle fleet and the commercial building. Finally, a sample case is presented to demonstrate the use of the models.