Abstract
The bi-directional linkage between the power grid and electric vehicles (EVs) enables flexible, cheap and fast-responding use of vehicle batteries in the grid. However, the battery aging effects due to the additional operation cycles caused by Vehicle-to-Grid (V2G) service and the concern of the battery degradation are the main reason that keeps the customer from being the named prosumer of the grid. This paper proposes a novel active battery anti-aging V2G scheduling approach. Firstly, to evaluate the battery aging effect in V2G service, the battery degradation phenomenon is quantified by a novel use of rain-flow cycle counting (RCC) algorithm. Then, the V2G scheduling is modeled as a multi-objective optimization problem, in which the minimal battery degradation and grid load fluctuation are designed as the optimization objectives. Finally, a multi-population collaborative mechanism, which is particularly designed for the V2G scheduling problem, is also developed to improve the practicability and performance of the heuristic optimization based V2G scheduling method. The proposed methodologies are verified by numerical analysis, which highlights that the proposed V2G scheduling method can minimize battery charge/discharge cycles by optimizing the time and scale of each V2G participant while providing the same services to the grid as expected.
Highlights
Energy is an essential part of modern life and energy management is an eternal topic in modern society
The key contributions are as follows: (1) The battery degradation phenomenon during V2G services is quantified by a novel rain-flow cycle counting (RCC) algorithm; (2) A mathematical optimization model is established for the active battery anti-aging V2G scheduling problem, in which the minimal battery degradation and grid load fluctuation are designed as the optimization objectives; (3) A multipopulation collaborative mechanism is developed with the ability to solve the large-scale, multi-objective, and nongradient optimization problem in active battery anti-aging V2G scheduling
The V2G participants’ behavior data were collected by Beijing Electric Vehicles Monitoring and Service Center, which is affiliated to National Engineering Laboratory for Electric Vehicles and serves as a national big data platform for electric vehicles in China
Summary
Energy is an essential part of modern life and energy management is an eternal topic in modern society. Electric vehicles (EVs) and power grid are two important components of the energy system. Instead of the one-way energy flow from the grid to EVs, their bi-directional link enables the flexible, cheap and fast-responding application of the vehicle batteries in the power grid [1], [2]. It leads to the concept of Vehicle-to-Grid (V2G) that effectively integrates EVs into the grid as distributed energy resources [3]. Liu et al [7] established a V2G behavior scheduling model based on Blockchain technology to improve grid operation stability. The simulation results showed that the proposed scheme can reduce the grid power fluctuation level and overall charging
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