Integration of a Pb-acid battery management algorithm within the optimization of predictive control strategies for a connected micro grid
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Within the framework of microgrid systems, ESS (energy storage systems) are becoming essential in developing relevant markets in the use of more renewable sources and for Smart Grids. ESS are projected to strengthen grid resilience by solving complications such as hourly variations in demand and price, excessive power fluctuation and lack of energy supply that are related with the instability of renewable energy sources. Then, the preservation of the battery lifetime infers a starting point in the development of an ESS. It comprises everything related to the electrical system, where the critical inconvenient consist on dealing with the different charging process of the batteries, which consist on applying three stages: Bulk, absorption and float. To address this problem, with the aim of providing a viable solution, this project introduces an ESS control algorithm within the optimization control strategies minimizing cost functions for a microgrid system. The proposed solution is established on a modification of the optimization strategy for adding absorption and float stages after each bulk charge to preserve the battery lifetime. Where, as a part of a tertiary control system, theses stages are estimated out of the optimization program to reduce computation complexity. Taken a look at the simulation results and at expenses of only a slight cost function increase, it has been confirmed the feasibility of this procedure. These growth at the cost function can be assumed to preserve the battery lifetime.