We propose a novel way to use Electric Vehicles (EVs) as dynamic mobile energy storage with the goal to support grid balancing during peak load times. EVs seeking parking in a busy expensive inner city area, can get free parking with a valet company in exchange for being utilized for grid support. The valet company would have an agreement with the local utility company to receive varying rewards for discharging EVs at designated times and locations of need (say, where power lines are congested). Given vehicle availabilities, the valet company would compute an optimal schedule of which vehicle to utilize where and when so as to maximize rewards collected. Our contributions are a detailed description of this new concept along with supporting theory to bring it to fruition. On the theory side, we provide new hardness results, as well as efficient algorithms with provable performance guarantees that we also test empirically.
An online auction framework for EV charging is proposeded by Xiang al @cite_9 , where in a large parking lot, every spot is equipped with a charging point, and the EV users submit bids on their charging demands. The parking lot then decides on the allocation and pricing based on the collected bids. It is shown that the proposed mechanism is truthful and individually rational, while approximately maximizing social welfare. Vehicle to grid (V2G) discharging is not considered in the proposed market mechanism, while effective discharging is our main objective.
@cite_9
2015020077 2444333355 2225115145 2063915800
The increasing market share of electric vehicles (EVs) makes large-scale charging stations indispensable infrastructure for integrating EVs into the future smart grid. Thus their operation modes have drawn great attention from researchers. One promising mode called park-and-charge was recently proposed. It allows people to park their EVs at a parking lot, where EVs can get charged during the parking time. This mode has been experimented and demonstrated in small scale. However, the missing of an efficient market mechanism is an important gap preventing its large-scale deployment. Existing pricing policies, e.g., pay-by-use and flat-rate pricing, would jeopardize the efficiency of electricity allocation and the corresponding social welfare in the park-and-charge mode, and thus are inapplicable. To find an efficient mechanism, this paper explores the feasibility and benefits of utilizing auction mechanism in the EV park-and-charge mode. The auction allows EV users to submit and update bids on their charging demand to the charging station, which makes corresponding electricity allocation and pricing decisions. To this end, we propose Auc2Charge, an online auction framework. Auc2Charge is truthful and individual rational. Running in polynomial time, it provides an efficient electricity allocation for EV users with a close-form approximation ratio on system social welfare. Through both theoretical analysis and numerical simulation, we demonstrate the efficacy of Auc2Charge in terms of social welfare and user satisfaction. Parking-lot electric vehicle (EV) charging promises reduced on-board battery capacity for commuters, which would decrease the payback time. However, the parking-lot EV charging scenario is rendered complicated by the large number of agents involved and highly dynamic price of electricity during the day. This study solves the parking-lot EV charging scheduling problem through a noncooperative game approach that considers the coupled constraint therein. The total charging amount is restrained by the transformer capacity. Such a coupled constraint makes the parking-lot EV charging game distinct from other EV charging scenarios. The theoretical framework of the Rosen–Nash normalized equilibrium is applied to deal with such a problem. The Nikaido–Isoda relaxation algorithm is used to calculate the equilibrium point. The dynamic game extension is then provided. Numerical simulation validates the proposed framework. Moreover, the impact of major parameters of the EV charging game on the equilibrium point that can be achieved is investigated. We address the optimal bidding problem of an aggregator that manages the charging of a group of plug-in electric vehicles. The aggregator purchases energy in the day-ahead market, and offers capacity in the frequency regulation market. The charging flexibility of the fleet is expressed as a set of time-varying power and energy constraints. The impact of the aggregator's demand on day-ahead market prices is endogenously modelled by formulating the problem as a bilevel problem: The upper level represents the aggregator's cost minimisation, and the lower level represents the market clearing. We explore several settings of the regulation market, analysing the impact of restrictions that may apply on the capacity offers (e.g., symmetric bids). Moreover, we compare the options of providing regulation with unidirectional charging, and with vehicle-to-grid (V2G). We test the proposed method in a case study for Switzerland, with historical day-ahead and regulation market data, and realistic driving patterns. Vehicle-to-grid (V2G) units are gaining prominence and may dominate the auto-market in the near future. The V2G batteries require corporate parking lots for charging and discharging operations. The electric power capacity of an existing parking lot can be increased by the installation of photovoltaic (PV) rooftops. This paper describes mathematical models for estimating the electric power capacity of a V2G parking lot (VPL) system with PV canopy. The electric vehicle (EV) demand supply model was formulated as a queuing theory problem, exhibiting stochastic characteristics. New formulae were developed to address the impacts of battery charger efficiency on the amount of power demand during battery charging, and also how the latter is effected by inverter efficiency during discharging. Mathematical models for grid gain factor were developed. The proposed models were tested using Tesla Roadster EV and Nissan leaf EV. Promising simulation results are gained leading to a conclusion that vehicle parking lots with PV facilities can potentially relieve and enhance the grid capacity. Results show that 60 gain factor is possible. The effect of weather uncertainties and energy market price were studied. The study could be useful in battery-charger control studies.