Abstract
The increasing use of electric vehicles connected to the power grid gives rise to challenges in the vehicle charging coordination, cost management, and provision of potential services to the grid. Scheduling of the power in an electric vehicle charging station is a quite challenging task, considering time-variant prices, customers with different charging time preferences, and the impact on the grid operations. The latter aspect can be addressed by exploiting the vehicle charging flexibility. In this article, a specific definition of flexibility to be used for an electric vehicle charging station is provided. Two optimal charging strategies are then proposed and evaluated, with the purpose of determining which strategy can offer spinning reserve services to the electrical grid, reducing at the same time the operation costs of the charging station. These strategies are based on a novel formulation of an economic model predictive control algorithm, aimed at minimising the charging station operation cost, and on a novel formulation of the flexibility capacity maximisation, while reducing the operation costs. These formulations incorporate the uncertainty in the arrival time and state of charge of the electric vehicles at their arrival. Both strategies lead to a considerable reduction of the costs with respect to a simple minimum time charging strategy, taken as the benchmark. In particular, the strategy that also accounts for flexibility maximisation emerges as a new tool for maintaining the grid balance giving cost savings to the charging stations.
Highlights
This work has proposed two novel strategies for the scheduling of the charging power of a Electric Vehicle Charging Station (EVCS) that can be used by an aggregator
The first strategy looks for minimising the EVCS operation costs via an economic Model Predictive Control
The second strategy develops an Optimal Control with minimum Cost and maximum Flexibility (OCCF) formulation, where the electric vehicles (EVs) charger flexibility capacity is defined as the power deviations attainable by the charger with respect to a given nominal charging profile
Summary
Renewable Energy Sources (RES) are increasing worldwide by an average of 2.8%/year [1], leading to a possible imbalance between supply and demand in the electrical grid. The RES uncertainty has a significant impact on the scheduling of conventional generation [2] and storage [3]. The main effects of the uncertainty appear both on power system operation and on the need for procuring sufficient reserve capacity to maintain acceptable levels of reliability and security [4]. The participation of the demand in operation scheduling and reserve procurement has increased, with the definition of demand response programmes that involve manual or automatic variation of the demand to reduce the grid risk [5]. The current deployment of the generation and demand resources to improve the power system operation has been represented in the flexibility
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