A Novel Formulation for the Energy Storage Scheduling Problem in Solar Self-consumption Systems

Icíar Lloréns*, Ricardo Alonso, Sergio Gil-López, Sandra Riaño, Javier Del Ser

*Autor correspondiente de este trabajo

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Energy storage systems are key components to increase photovoltaic (PV) self-consumption profitability. Indeed, they allow for the intermittency dampening of the PV production so as to adequately cover end-users’ consumption. Given that in most grid-connected PV systems electricity prices are variable, an informed battery scheduling can significantly decrease energy costs. Moreover, energy storage systems can cover consumption peaks to enable contracted power reduction and hence additional savings in electricity bill. This work elaborates on a scalable and flexible optimization system based on production and load forecasting as a Model Predictive Control (MPC) for battery scheduling that aims at minimizing energy costs for consumers. The system provides a 24-hour-ahead battery plan that reduces purchase cost from grid, extends the battery lifetime and guarantees purchases below the maximum contracted power. The formulated problem is solved by means of a MINLP solver and several evolutionary algorithms. Results obtained by these optimization algorithms over real data are promising in terms of cost savings within Spanish electricity market, particularly when compared to the results rendered by other methods from the state of the art. We end by outlying several research directions rooted on the findings reported in this study.

Idioma originalInglés
Título de la publicación alojada15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020
EditoresÁlvaro Herrero, Carlos Cambra, Daniel Urda, Javier Sedano, Héctor Quintián, Emilio Corchado
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas67-78
Número de páginas12
ISBN (versión impresa)9783030578015
DOI
EstadoPublicada - 2021
Evento15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020 - Burgos, Espana
Duración: 16 sept 202018 sept 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1268 AISC
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

Conferencia15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020
País/TerritorioEspana
CiudadBurgos
Período16/09/2018/09/20

Financiación

FinanciadoresNúmero del financiador
Department of Education of the Basque Government
EU?s Horizon 2020 research and innovation program
EU’s Horizon 2020 research and innovation program691768, IT1294-19

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