Energy Management Strategy for an Autonomous Hybrid Power Plant Destined to Supply Controllable Loads.

Imene Yahyaoui,Natalia Vidal De La Peña

doi:10.3390/s22010357

Imene Yahyaoui, Natalia Vidal De La Peña

Open Access

https://doi.org/10.3390/s22010357

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Abstract

This paper proposes an energy management strategy (EMS) for a hybrid stand-alone plant destined to supply controllable loads. The plant is composed of photovoltaic panels (PV), a wind turbine, a diesel generator, and a battery bank. The set of the power sources supplies controllable electrical loads. The proposed EMS aims to ensure the power supply of the loads by providing the required electrical power. Moreover, the EMS ensures the maximum use of the power generated by the renewable sources and therefore minimizes the use of the genset, and it ensures that the batteries bank operates into the prefixed values of state of charge to ensure their safe operation. The EMS provides the switching control of the switches that link the plant components and decides on the loads’ operation. The simulation of the system using measured climatic data of Mostoles (Madrid, Spain) shows that the proposed EMS fulfills the designed objectives.

Highlights

Microgrids can be classified as grid-connected or stand-alone
The energy management strategy (EMS) allows the operating of the plant components to be deduced in such a way that the RE sources and/or the battery bank and the diesel generator supply the loads with AC power
Measured climatic data of the solar radiation, the ambient temperature, and the wind speed that correspond to a typical day in July, March, and December have been used to test the Fuzzy Management Algorithm (FMA) efficiency

Summary

Introduction

Microgrids can be classified as grid-connected or stand-alone. It can be classified following the use that can be for military, industrial, residential, or agricultural applications, etc. These microgrids can be based on renewable sources, namely, photovoltaic panels, wind turbines, fuel cells, waves energy, etc., or nonrenewable energy sources, namely, gensets. For the case of renewable stand-alone plants, many studies have been developed and focused on the energy management. In [1], the authors developed an intelligent control strategy based on the ANN and applied on a grid-connected plant composed of Photovoltaic (PV) panels and a Li-ion Battery Energy Storage System. The ANN is used to estimate the battery bank state of charge (SOC), which is used to decide on the battery bank charging and discharging using a smart controller for a DC/DC bidirectional converter

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