Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants

The unpredictable nature of renewable energies is drawing attention to lithium-ion batteries. In order to make full utilization of these batteries, some research works are focused on the management of existing systems, while others propose sizing techniques based on business models. However, in orde...

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Autores: Berrueta Irigoyen, Alberto, Heck, Michael, Jantsch, Martin, Ursúa Rubio, Alfredo, Sanchis Gúrpide, Pablo
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/33235
Acceso en línea:https://hdl.handle.net/2454/33235
Access Level:acceso abierto
Palabra clave:Energy storage system
Lithium-ion battery
Optimal energy dispatch scheduling
Dynamic programming method
Energy arbitrage
Renewable energy
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spelling Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants Berrueta Irigoyen, Alberto Heck, Michael Jantsch, Martin Ursúa Rubio, Alfredo Sanchis Gúrpide, Pablo Energy storage system Lithium-ion battery Optimal energy dispatch scheduling Dynamic programming method Energy arbitrage Renewable energy The unpredictable nature of renewable energies is drawing attention to lithium-ion batteries. In order to make full utilization of these batteries, some research works are focused on the management of existing systems, while others propose sizing techniques based on business models. However, in order to optimise the global system, a comprehensive methodology that considers both battery sizing and management at the same time is needed. This paper proposes a new optimisation algorithm based on a combination of dynamic programming and a region elimination technique that makes it possible to address both problems at the same time. This is of great interest, since the optimal size of the storage system depends on the management strategy and, in turn, the design of this strategy needs to take account of the battery size. The method is applied to a real installation consisting of a 100 kWp rooftop photovoltaic plant and a Li-ion battery system connected to a grid with variable electricity price. Results show that, unlike conventional optimisation methods, the proposed algorithm reaches an optimised energy dispatch plan that leads to a higher net present value. Finally, the tool is used to provide a sensitivity analysis that identifies key informative variables for decision makers The authors would like to acknowledge the support of the Spanish State Research Agency and FEDER-UE under grants DPI2016-80641-R and DPI2016-80642-R; of Government of Navarra through research project PI038 INTEGRA-RENOVABLES; and the FPU Program of the Spanish Ministry of Education, Culture and Sport (FPU13/00542). Elsevier https://hdl.handle.net/2454/33235
title Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants
spellingShingle Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants
Berrueta Irigoyen, Alberto
Energy storage system
Lithium-ion battery
Optimal energy dispatch scheduling
Dynamic programming method
Energy arbitrage
Renewable energy
title_short Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants
title_full Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants
title_fullStr Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants
title_full_unstemmed Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants
title_sort Combined dynamic programming and region-elimination technique algorithm for optimal sizing and management of lithium-ion batteries for photovoltaic plants
author Berrueta Irigoyen, Alberto
author_facet Berrueta Irigoyen, Alberto
Heck, Michael
Jantsch, Martin
Ursúa Rubio, Alfredo
Sanchis Gúrpide, Pablo
author_role author
author2 Heck, Michael
Jantsch, Martin
Ursúa Rubio, Alfredo
Sanchis Gúrpide, Pablo
author2_role author
author
author
author
topic Energy storage system
Lithium-ion battery
Optimal energy dispatch scheduling
Dynamic programming method
Energy arbitrage
Renewable energy
topic_facet Energy storage system
Lithium-ion battery
Optimal energy dispatch scheduling
Dynamic programming method
Energy arbitrage
Renewable energy
description The unpredictable nature of renewable energies is drawing attention to lithium-ion batteries. In order to make full utilization of these batteries, some research works are focused on the management of existing systems, while others propose sizing techniques based on business models. However, in order to optimise the global system, a comprehensive methodology that considers both battery sizing and management at the same time is needed. This paper proposes a new optimisation algorithm based on a combination of dynamic programming and a region elimination technique that makes it possible to address both problems at the same time. This is of great interest, since the optimal size of the storage system depends on the management strategy and, in turn, the design of this strategy needs to take account of the battery size. The method is applied to a real installation consisting of a 100 kWp rooftop photovoltaic plant and a Li-ion battery system connected to a grid with variable electricity price. Results show that, unlike conventional optimisation methods, the proposed algorithm reaches an optimised energy dispatch plan that leads to a higher net present value. Finally, the tool is used to provide a sensitivity analysis that identifies key informative variables for decision makers
publishDate 2018
format article
status_str acceptedVersion
url https://hdl.handle.net/2454/33235
eu_rights_str_mv openAccess
publisher Elsevier
institution Universidad Pública de Navarra
collection Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
reponame_str Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname_str Universidad Pública de Navarra
_version_ 1878443485917347840
publishDateSort 2018
author_browse Berrueta Irigoyen, Alberto
Heck, Michael
Jantsch, Martin
Sanchis Gúrpide, Pablo
Ursúa Rubio, Alfredo
publisherStr Elsevier
score 6,9303427

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