Optimization of Bi-Directional V2G Behavior With Active Battery Anti-Aging Scheduling

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. INDEX TERMS Electric vehicle, vehicle to grid, active battery anti-aging and heuristic algorithm.

Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles

“…Li et al [2] used particle swarm optimization to design a SC scheme targeting minimal battery aging and grid load fluctuations. To quantify battery aging, a novel rain-flow cycle counting algorithm was used.…”

“…In this context, Smart Charging (SC), i.e. the controlled and coordinated charging of EVs, helps to minimize EV operating cost [18] and prolong EV battery life [2]. To further diminish negative power grid impacts due to EV charging, [4], [5] [6]- [13] [14]- [16] [17] proposed work…”

A Decision-Making Framework for the Smart Charging of Electric Vehicles Considering the Priorities of the Driver

“…In addition, to mitigate the computational time of the integer linear programming (ILP), game theoretic algorithms have been proposed [18,19]. Considering that the criteria and the objective function of a charge scheduling problem can often be not linear or quadratic, the conventional convex optimisation may not be sufficient, and heuristics need to be employed [20].…”

“…In addition, the two heuristic algorithms that are evaluated, namely PSO and GA, are briefly demonstrated. The suitability of the PSO and the GA in scheduling problems has been investigated in [17,20,24,33,34]. Afterwards, those algorithms were investigated for the proposed application.…”

“…The exhaustive search evaluated all possible charging current combinations for all timeslots with steps of 2 A. The exhaustive search always provided the best solution, and as a result the error was always positive and calculated using (20).…”