47,843 research outputs found
Capacity management of vehicle-to-grid system for power regulation services
Due to green initiatives adopted in many countries, renewable energy will be massively incorporated into the future smart grid. However, the intermittency of the renewables may result in power imbalance, thus adversely affecting the stability of a power system. Voltage regulation may be used to maintain the power balance at all times. As electric vehicles (EVs) become popular, they may be connected to the grid to form a vehicle-to-grid (V2G) system. An aggregation of EVs can be coordinated to provide voltage regulation services. However, V2G is a dynamic system where EVs are connected to the grid according to the owners' habits. In this paper, we model an aggregation of EVs with a queueing network, whose structure allows us to estimate the capacities for regulation up and regulation down, separately. The estimated capacities from the V2G system can be used for establishing a regulation contract between an aggregator and the grid operator, and facilitate a new business model for V2G. © 2012 IEEE.published_or_final_versio
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Small Island Developing States and their suitability for electric vehicles and vehicle-to-grid services
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Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California
This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits
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Provision of secondary frequency regulation by coordinated dispatch of industrial loads and thermal power plants
Demand responsive industrial loads with high thermal inertia have potential to provide ancillary service for frequency regulation in the power market. To capture the benefit, this study proposes a new hierarchical framework to coordinate the demand responsive industrial loads with thermal power plants in an industrial park for secondary frequency control. In the proposed framework, demand responsive loads and generating resources are coordinated for optimal dispatch in two-time scales: (1) the regulation reserve of the industrial park is optimally scheduled in a day-ahead manner. The stochastic regulation signal is replaced by the specific extremely trajectories. Furthermore, the extremely trajectories are achieved by the day-ahead predicted regulation mileage. The resulting benefit is to transform the stochastic reserve scheduling problem into a deterministic optimization; (2) a model predictive control strategy is proposed to dispatch the industry park in real time with an objective to maximize the revenue. The proposed technology is tested using a real-world industrial electrolysis power system based upon Pennsylvania, Jersey, and Maryland (PJM) power market. Various scenarios are simulated to study the performance of the proposed approach to enable industry parks to provide ancillary service into the power market. The simulation results indicate that an industrial park with a capacity of 500 MW can provide up to 40 MW ancillary service for participation in the secondary frequency regulation. The proposed strategy is demonstrated to be capable of maintaining the economic and secure operation of the industrial park while satisfying performance requirements from the real world regulation market
Vehicle-to-grid regulation based on a dynamic simulation of mobility behavior
This study establishes a new approach to analyzing the economic impacts of vehicle-to-grid (V2G) regulation by simulating the restrictions arising from un-predictable mobility requests by vehicle users. A case study for Germany using average daily values (in the following also called the "static" approach) and a dynamic simulation including different mobility use patterns are presented. Comparing the dynamic approach with the static approach reveals a significant difference in the power a vehicle can offer for regulation and provides insights into the necessary size of vehicle pools and the possible adaptations required in the regulation market to render V2G feasible. In a first step, the regulation of primary, secondary and tertiary control is ana-lyzed based on previous static methods used to investigate V2G and data from the four German regulation areas. It is shown that negative secondary control is economically the most beneficial for electric vehicles because it offers the high-est potential for charging with 'low-priced' energy from negative regulation. In a second step, a new method based on a Monte Carlo simulation using stochastic mobility behavior is applied to look at the negative secondary control market in more detail. Our simulation indicates that taking dynamic driving behavior into account results in a 40% reduction of the power available for regulation. Be-cause of the high value of power in the regulation market this finding has a strong impact on the resulting revenues. Further, we demonstrate that, for the data used, a pool size of 10,000 vehicles seems reasonable to balance the var-iation in driving behavior of each individual. In the case of the German regula-tion market, which uses monthly bids, a daily or hourly bid period is recom-mended. This adaptation would be necessary to provide individual regulation assuming that the vehicles are primarily used for mobility reasons and cannot deliver the same amount of power every hour of the week. --
Scenarios for the development of smart grids in the UK: literature review
Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid.
It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers.
The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.
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