Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/3/3143/tde-19012021-100846/ |
Resumo: | 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. |
id |
USP_8b0cdbb67e4192cb2a3c36399d0cceee |
---|---|
oai_identifier_str |
oai:teses.usp.br:tde-19012021-100846 |
network_acronym_str |
USP |
network_name_str |
Biblioteca Digital de Teses e Dissertações da USP |
repository_id_str |
2721 |
spelling |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation dataO dimensionamento do sistema de armazenamento de energia da bateria em sistemas fotovoltaicos isoladas usando dados de radiação solar previstosAnálise de séries temporaisAutoregressiveAutorregressivoBattery energy storage SystemBattery sizingDimensionamento de bateriaEconomic performanceEnergia (Armazenamento)Energia renovávelIntermitênciaIntermittencyIrradiância solarPerformance econômicaPhotovoltaic systemsRenewable energySérie sintéticaSistema de armazenamento de energia por bateriaSistemas fotovoltaicosSolar irradianceSynthetic seriesTime seriesThis 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.Este estudo apresenta uma metodologia para o dimensionamento de Sistemas para Armazenamento de Energia por Baterias (SAEB), gerada a partir de Sistemas Fotovoltaicos (FV) isolados, usando dados da radiação solar horária prevista. O método baseia-se em uma relação matemática estabelecida entre energia gerada por FV, demanda por carga horária e capacidade de armazenamento, permitindo determinar períodos de interrupção de energia e déficit de oferta. Para conseguir isso, o comportamento da radiação solar deve ser previsto através da aquisição e processamento de um conjunto de dados históricos de radiação solar horária, para que modelos autorregressivos (AR) e séries temporais sejam usados para gerar séries sintéticas horárias. As séries geradas, combinadas com a demanda de carga horária disponível, são usadas como entradas na simulação. O dimensionamento do SAEB é considerado ajustando as variáveis [na simulação para determinar a potência correspondente e a capacidade de energia até que sejam atingidas porcentagens aceitáveis de déficit de energia e interrupções de fornecimento. A análise de probabilidade também é realizada usando vários cenários de radiação de dados de radiação solar sintética, representados usando curvas de distribuição cumulativa e de probabilidade. O método proposto é aplicado em um local no Nordeste do Brasil, usando o método Box Jenkins AR, a fim de facilitar a avaliação do desempenho de vários possíveis SAEB, indicar o risco de déficit de energia e a possível frequência de interrupção de energia. A análise de custo é realizada para analisar os riscos e benefícios investidos na instalação do sistema de armazenamento de energia da bateria em plantas fotovoltaicas e mostra as contribuições da abordagem proposta. A metodologia foi aplicada a estudos de caso autossuficientes em escala não utilitária para fins de captação e redução de energia, resultados foram discutidos e conclusões tiradas.Biblioteca Digitais de Teses e Dissertações da USPAlmeida, Carlos Frederico MeschiniAbubakar, Ahmad2020-07-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/3/3143/tde-19012021-100846/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2021-01-19T16:20:02Zoai:teses.usp.br:tde-19012021-100846Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212021-01-19T16:20:02Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data O dimensionamento do sistema de armazenamento de energia da bateria em sistemas fotovoltaicos isoladas usando dados de radiação solar previstos |
title |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data |
spellingShingle |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data Abubakar, Ahmad 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 |
title_short |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data |
title_full |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data |
title_fullStr |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data |
title_full_unstemmed |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data |
title_sort |
Sizing of battery energy storage systems in isolated photovoltaic plants using predicted solar radiation data |
author |
Abubakar, Ahmad |
author_facet |
Abubakar, Ahmad |
author_role |
author |
dc.contributor.none.fl_str_mv |
Almeida, Carlos Frederico Meschini |
dc.contributor.author.fl_str_mv |
Abubakar, Ahmad |
dc.subject.por.fl_str_mv |
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 |
topic |
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 |
description |
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. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-07-15 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/3/3143/tde-19012021-100846/ |
url |
https://www.teses.usp.br/teses/disponiveis/3/3143/tde-19012021-100846/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
_version_ |
1809090850178727936 |