Optimizing B2G Usage to Maximize Revenue and Ensure Warranty Compliance

Abstract

With the development of maritime electrification, the Boat-to-Grid (B2G) system shows great application potential. The battery is not only used for ship propulsion, but can also participate in grid services. However, B2G usage may accelerate battery degradation. To solve this problem, this thesis builds an optimization model to find the optimal daily usage strategy for boat batteries under B2G. The goal is to maximize profit while protecting battery lifetime. This study selects two typical battery types, Lithium Iron Phosphate (LFP) and Nickel Cobalt Aluminum (NCA), and creates daily usage profiles based on seasonal energy demand in two Swedish cities, Gothenburg and Luleå. The degradation models are considered as constraints. Two optimization methods are used. The first one is based on Model Predictive Control (MPC) with IPOPT solver, using current as the decision variable to maximize daily revenue. The second one is based on Genetic Algorithm (GA) with the DEAP framework, using power as the decision variable to minimize daily cost. In Frequency Containment Reserve (FCR) service, the results show that in most cases both methods can generate optimal charging and discharging strategies under different usage conditions, saving at least 4 % in summer. The battery can still achieve profits while limiting degradation, which reflects that the model has the capability to balance revenue and battery lifetime.