Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach

Abstract

As the number of electric vehicles (EVs) is steadily increasing, their aggregation can offer significant storage to improve the electric system operation in many aspects. To this end, a comprehensive stochastic optimization framework is proposed in this paper for the joint operation of a fleet of EVs with a wind power producer (WPP) in a three-settlement pool-based market. An aggregator procures enough energy for the EVs based on their daily driving patterns, and schedules the stored energy to counterbalance WPP fluctuations. Different sources of uncertainty including the market prices and WPP generation are modeled through proper scenarios, and the risk is hedged by adding a risk measure to the formulation. To obtain more accurate results, the battery degradation costs are also included in the problem formulation. A detailed case study is presented based on the Iberian electricity market data as well as the technical information of three different types of EVs. The proposed approach is benchmarked against the disjoint operation of EVs and WPP. Numerical simulations demonstrate that the proposed strategy can effectively benefit EV owners and WPP by reducing the energy costs and increasing the profits.

Total output power variation of several small wind turbines

“…In WT systems, these negative impacts are caused especially by aerodynamic factors such as turbulence and wind shifts. Studies of methods to address these problems, such as controls of WTs and energy storage systems, have been conducted (Abbasi et al, 2019;Shangfeng et al, 2017;Xing et al, 2019;Yang and Yang, 2019). On one hand, these methods compensate only low-frequency components of output power fluctuation with a response delay of several seconds at least.…”

Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles

“…Many control schemes have been proposed to overcome the negative impacts of EV charging. A control strategy using data-driven models has been implemented to relax power system components and prevent excessive loading due to EV charging demand [27][28][29]. Demand side management (DSM) works to guarantee EVs' demand satisfaction in all grid situations and certifies grid stability [30][31][32][33][34].…”

A day‐ahead sleeved power purchase agreement model for estimating the profit of wind farms in the Indian energy market

“…With the assistance of energy storage technologies, the volatility of WP can be mitigated 25 . Again, the usage of pumped hydro storages, 26,27 battery energy storage, 28 plug‐in electric vehicles, 29,30 etc. can additionally maximize the operating economy of WF.…”