Non-Linear Model Predictive Control for Preventing Premature Aging in Battery Energy Storage System

摘要

This paper discusses non-linear model predictive control (NMPC) for preventing premature aging in a Battery Energy Storage System (BESS). The BESS can be used in both residential and commercial buildings in order to reduce the cost of energy consumption. Apart from maintaining the BESS's life expectancy, the NMPC is also responsible for securing the maximum possible economic profit. The implementation of the NMPC requires the modeling of the BESS, the modeling of an aging prediction mechanism for the 15-Lithium Ion batteries stack and the identification of the needs and requirements for energy management in a dynamic pricing environment where the GRID is the unique source of power to the building and to the BESS. The NMPC utilizes forecasted profiles for the energy demand and the energy prices which are retrieved from a data knowledge warehouse in order to propose an optimal discharge profile for the BESS. Furthermore, the intra-day alternations of the energy prices and the uncertainty that the day-ahead energy demand profile will match the actual demand profile, makes the necessity of the controller to update the proposed discharge profile during the day inevitable. Indicative results of the proposed method are presented in order to demonstrate the ability of the NMPC to provide an optimal solution for achieving a specific capacity loss target for the batteries stack and simultaneously ensuring high financial profit.