Multi-Objective Fuzzy Logic-Based Energy Management System for Microgrids with Battery and Hydrogen Energy Storage System

Abstract

<jats:p>This paper proposes a fuzzy logic-based energy management system (EMS) for microgrids with a combined battery and hydrogen energy storage system (ESS), which ensures the power balance according to the load demand at the time that it takes into account the improvement of the microgrid performance from a technical and economic point of view. As is known, renewable energy-based microgrids are receiving increasing interest in the research community, since they play a key role in the challenge of designing the next energy transition model. The integration of ESSs allows the absorption of the energy surplus in the microgrid to ensure power supply if the renewable resource is insufficient and the microgrid is isolated. If the microgrid can be connected to the main power grid, the freedom degrees increase and this allows, among other things, diminishment of the ESS size. Planning the operation of renewable sources-based microgrids requires both an efficient dispatching management between the available and the demanded energy and a reliable forecasting tool. The developed EMS is based on a fuzzy logic controller (FLC), which presents different advantages regarding other controllers: It is not necessary to know the model of the plant, and the linguistic rules that make up its inference engine are easily interpretable. These rules can incorporate expert knowledge, which simplifies the microgrid management, generally complex. The developed EMS has been subjected to a stress test that has demonstrated its excellent behavior. For that, a residential-type profile in an actual microgrid has been used. The developed fuzzy logic-based EMS, in addition to responding to the required load demand, can meet both technical (to prolong the devices’ lifespan) and economic (seeking the highest profitability and efficiency) established criteria, which can be introduced by the expert depending on the microgrid characteristic and profile demand to accomplish.</jats:p>

A Review of Recent Advances on Hybrid Energy Storage System for Solar Photovoltaics Power Generation

“…The FLC strategy requires appropriate models and methods. The FLC algorithm is based on membership function rules [142], [143].…”

Towards Optimal Management in Microgrids: An Overview

“…Fuzzy logic is a form of manyvalued logic in which the true values of variables may be any real number between zero and one, both inclusive, unlike Boolean logic, for which the true values of variables may only be the integer values of zero or one. In [130], an EMS was proposed based on a fuzzy logic controller (FLC) to improve the MG's performance from both a technical (to prolong the device's lifespan) and an economic (to have the highest profitability and efficiency) point of view. The proposed controller was tested in a residential MG found at the Spanish Institute of Aerospace Technology.…”

Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

“…Fuzzy logic control is also employed in grid-connected battery hydrogen systems. However, they are of lesser relevance to this work, as the degrees of freedom and main objectives are markedly different [25][26][27].…”