Sizing and Management of Energy Storage Systems in Large-Scale Power Plants Using Price Control and Artificial Intelligence

Carlos García-Santacruz,Luis Galván,Eduardo Galván,Juan M Carrasco

doi:10.3390/en14113296

Carlos García-Santacruz, Luis Galván + Show 2 more

Open Access

https://doi.org/10.3390/en14113296

Copy DOI

Journal: Energies	Publication Date: Jun 4, 2021
Citations: 7	License type: CC BY 4.0

Affiliation: Universidad de Sevilla

Abstract

Energy storage systems are expected to play a fundamental part in the integration of increasing renewable energy sources into the electric system. They are already used in power plants for different purposes, such as absorbing the effect of intermittent energy sources or providing ancillary services. For this reason, it is imperative to research managing and sizing methods that make power plants with storage viable and profitable projects. In this paper, a managing method is presented, where particle swarm optimisation is used to reach maximum profits. This method is compared to expert systems, proving that the former achieves better results, while respecting similar rules. The paper further presents a sizing method which uses the previous one to make the power plant as profitable as possible. Finally, both methods are tested through simulations to show their potential.

Highlights

The decarbonisation of energy is a major objective for the decades to come [1]
A new energy management method based on price control has been proposed for hybrid power plants
This method uses the E-Broker algorithm and the particle swarm optimisation, along with a new parameterisation to control the behavior of the energy storage system (ESS)

Summary

Introduction

The decarbonisation of energy is a major objective for the decades to come [1]. In Europe, different directives [2,3] aim for at least 32% of energy to be renewable by 2030. Renewable generation plays a key role in achieving these goals These technologies allow the use of natural resources as energy sources, but are dependent on the availability of the natural resource, and conditioned by their intermittency. The gap between production and demand is another problem This can be clearly seen in solar energy production, one of the most installed sources, whose production curve is significantly different from the demand curve. This means that it is not possible to match demand with generation at times. Studies such as [4,5,6] analyse the future of photovoltaic power plants in Europe for the coming decades

Methods

Results

Conclusion