Multi-objective Optimization of Production Scheduling Using Particle Swarm Optimization Algorithm for Hybrid Renewable Power Plants with Battery Energy Storage System

作     者：Jon Martinez-Rico Ekaitz Zulueta Ismael Ruiz de Argandona Unai Femandez-Gamiz Mikel Armendia Jon Martinez-Rico;Ekaitz Zulueta;Ismael Ruiz de Argando?a;Unai Fernandez-Gamiz;Mikel Armendia

作者机构：The Automation and Control UnitFundacion TeknikerBasque Research and Technology Alliance(BRTA)Ifiaki Goenaga520600 the University of the Basque CountryIng.Torres Quevedo148013 BilbaoSpain the Department of Systems Engineering and ControlCollege of Engineering at Vitoria-GasteizUniversity of the Basque CountryNieves Cano1201006 Vitoria-GasteizSpain the Department of Nuclear and Fluid MechanicsCollege of Engineering at Vitoria-GasteizUniversity of the Basque CountryNieves Cano1201006 Vitoria-GasteizSpain 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2021年第9卷第2期

页      面：285-294页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 081104[工学-模式识别与智能系统] 0807[工学-动力工程及工程热物理] 0811[工学-控制科学与工程] 

主　　题：Battery energy storage system energy arbitrage hybrid renewable energy system particle swarm optimization 

摘      要：Considering the increasing integration of renewable energies into the power grid,batteries are expected to play a key role in the challenge of compensating the stochastic and intermittent nature of these energy sources.Besides,the deployment of batteries can increase the benefits of a renewable power plant.One way to increase the profits with batteries studied in this paper is performing energy arbitrage.This strategy is based on storing energy at low electricity price moments and selling it when electricity price is high.In this paper,a hybrid renewable energy system consisting of wind and solar power with batteries is studied,and an optimization process is conducted in order to maximize the benefits regarding the dayahead production scheduling of the plant.A multi-objective cost function is proposed,which,on the one hand,maximizes the obtained profit,and,on the other hand,reduces the loss of value of the battery.A particle swarm optimization algorithm is developed and fitted in order to solve this non-linear multi-objective function.With the aim of analyzing the importance of considering both the energy efficiency of the battery and its loss of value,two more simplified cost functions are proposed.Results show the importance of including the energy efficiency in the cost function to optimize.Besides,it is proven that the battery lifetime increases substantially by using the multi-objective cost function,whereas the profitability is similar to the one obtained in case the loss of value is not considered.Finally,due to the small difference in price among hours in the analyzed Iberian electricity market,it is observed that low profits can be provided to the plant by using batteries just for arbitrage purposes in the day-ahead market.