Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data

• Ano de defesa: 2020
• Autor(a) principal: Abubakar, Ahmad
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Análise de séries temporais; Autoregressive; Autorregressivo; Battery energy storage System; Battery sizing; Dimensionamento de bateria; Economic performance; Energia (Armazenamento); Energia renovável; Intermitência; Intermittency; Irradiância solar; Performance econômica; Photovoltaic systems; Renewable energy; Série sintética; Sistema de armazenamento de energia por bateria; Sistemas fotovoltaicos; Solar irradiance; Synthetic series; Time series
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/3/3143/tde-19012021-100846/

This study presents a methodology for the sizing of Battery Energy Storage Systems (BESS) in isolated Photovoltaic Plants (PV) using predicted hourly solar radiation data. The method is based on a mathematical relationship that was established between PV generated energy, hourly load demand and storage capacity, allowing one to determine energy deficit and supply interruption periods. To achieve this, solar radiation behavior must be predicted through acquisition and processing sets of historical hourly solar radiation data so that autoregressive (AR) and time series models are used to generate hourly synthetic series. The generated series, combined with available hourly load demand, are used as inputs in the simulation. The sizing of BESS is considered by adjusting the variables in the simulation to determine the corresponding power output and energy capacity until acceptable percentages of energy deficit and supply interruptions are attained. Probability analysis is also carried out using multiple radiation scenarios of synthetic solar radiation data, represented using probability and cumulative distribution curves. The proposed method is applied to a location in Northeastern Brazil using the Box Jenkins AR method in order to facilitate the assessment of the performance of several possible BESS, indicate the risk of energy deficit and the possible frequency of energy interruption. A cost analysis is carried out to analyze the risks and benefits of investing in battery energy storage system installation in PV plants and shows the contributions of the proposed approach. The methodology was applied to self-sufficient nonutility scale case studies for purposes of energy harvesting and curtailment, results were presented, discussed and conclusions were drawn.