Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10953/2827
Título: A novel methodology for optimal sizing photovoltaic-battery systems in smart homes considering grid outages and demand response
Autoría: Tostado-Véliz, Marcos
Icaza-Alvarez, Daniel
Jurado-Melguizo, Francisco
Resumen: This paper deals with the optimal sizing of a hybrid photovoltaic-battery storage system for home energy management considering reliability against grid outages and demand response. To that end, a novel optimization framework is developed which aims at minimizing the electricity bill while the reliability of the system is ensured for certain common outages. In order to ensure the accuracy of the results, a large amount of characteristic outages along with demand, solar irradiance and temperature profiles are generated from real data. Clustering techniques are used for reducing this data to those most characteristics profiles and manage with the unpredictable behaviour of the outage events. Demand response is incorporated via different incentives like tariffs based on time of use and real time pricing, along with the optimal scheduling of different typical deferrable appliances. A case study on a smart-prosumer environment serves to illustrate the capabilities of the developed approach as providing sufficient guidelines for its universal applicability. Different cases studies are simulated considering different battery technologies and electricity tariffs for comparison. Various aspects related with the reliability against grid outages are also analysed like its impact on the project cost or the influence of demand response strategies.
Palabras clave: Photovoltaic array
Battery storage
Home energy management
Reliability
Fecha: jun-2021
Editorial: Elsevier
Citación: Marcos Tostado-Véliz, Daniel Icaza-Alvarez, Francisco Jurado, A novel methodology for optimal sizing photovoltaic-battery systems in smart homes considering grid outages and demand response, Renewable Energy, Volume 170, 2021, Pages 884-896, ISSN 0960-1481, https://doi.org/10.1016/j.renene.2021.02.006. (https://www.sciencedirect.com/science/article/pii/S0960148121001701)
Aparece en las colecciones: DIE-Artículos

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