43 research outputs found
Feasibility study: investigation of car park-based V2G services in the UK central hub
The increasing uptake of electric vehicles, and the established practice of long-term parking at stations and airports, offers an opportunity to develop a flexible approach to help with the energy storage dilemma. This paper investigates the feasibility of using a number of EV batteries as an energy storage and grid balancing solution within the UK Central Hub area. Here, the capital cost of the vehicle is a sunk cost to the EV owner. The potential income generated, or discount on long-term parking, is an additional benefit of ownership. This paper considers the income available to a small and large size car park from the different market mechanisms to offer grid support in the UK and contrasts this with the complexity and costs of the EV charging infrastructure required within these types of scheme
Optimal planning of plug‐in hybrid electric vehicle charging station in distribution network considering demand response programs and uncertainties
Application of data envelopment analysis theorem in plug‐in hybrid electric vehicle charging station planning
Monte Carlo simulation of electric vehicle loads respect to return home from work and impacts to the low voltage side of distribution network
Coordination of bidirectional charging for plug-in electric vehicles in smart distribution systems
The random and uncoordinated charging of plug-in electric vehicles (PEVs) at the home applications has negative effects on the technical operation indexes such as power loss and voltage stability of smart distribution systems. Hence, this paper provides an optimized approach which coordinates PEVs charging to reduce power losses and improve voltage profile of feeders in both cases grid to vehicle and vehicle to grid in real-time domain. In the proposed approach, there is a load smart management center (LSMC), which the coordination of EVs is its main duty. Moreover, this algorithm manages PEV based on time priorities due to the on-peak and off-peak periods of distribution system. The proposed algorithm uses maximum sensitivity selection for the optimized management of the vehicle charging in order to minimize power losses and minimize variations of average voltage of feeders. In order to show the performance of the proposed algorithm and LSMC, the actual distribution network (voltage levels of 20 and 0.4 kV) has been simulated that belongs to a city of southwest Iran with residential and commercial loads (for exact simulation of network). Total power losses and voltage profile have been calculated to show capability of proposed method.</p