Real-Time Welfare-Maximizing Regulation Allocation in Dynamic Aggregator-EVs System

Abstract

The concept of vehicle-to-grid (V2G) has gained recent interest as more and more electric vehicles (EVs) are put to use. In this paper, we consider a dynamic aggregator-EVs system, where an aggregator centrally coordinates a large number of dynamic EVs to perform regulation service. We propose a Welfare-Maximizing Regulation Allocation (WMRA) algorithm for the aggregator to fairly allocate the regulation amount among its EVs. Compared to previous works, WMRA accommodates a wide spectrum of vital system characteristics, including dynamics of EV, limited EV battery size, EV battery degradation cost, and the cost of using external energy sources for the aggregator. The algorithm operates in real time and does not require any prior knowledge of the statistical information of the system. Theoretically, we demonstrate that WMRA is away from the optimum by O(1/V), where V is a controlling parameter depending on EV's battery size. In addition, our simulation results indicate that WMRA can substantially outperform a suboptimal greedy algorithm.

13 pages

Cited by in corpus (7)

• Charging Electric Vehicles in the Smart City: A Survey of Economy-driven Approaches
• Distributed Real-Time Power Balancing in Renewable-Integrated Power Grids with Storage and Flexible Loads
• Real-Time Residential-Side Joint Energy Storage Management and Load Scheduling with Renewable Integration
• Co-optimizing Bidding and Power Allocation of an EV Aggregator Providing Real-time Frequency Regulation Service
• Real-Time Operation Strategy of Virtual Power Plants With Optimal Power Disaggregation Among Heterogeneous Resources
• Distributed Control for Charging Multiple Electric Vehicles with Overload Limitation
• A Fair and Privacy-Aware EV Discharging Strategy using Decentralized Whale Optimization Algorithm for Minimizing Cost of EVs and the EV Aggregator