Evaluation of methods to select representative days for the optimization of polygeneration systems

Pinto Maquilón, Edwin Samir (Universidad de Zaragoza) ; Serra, Luis M. (Universidad de Zaragoza) ; Lázaro, Ana (Universidad de Zaragoza)

Resumen: The optimization of polygeneration systems considering hourly periods throughout one year is a computationally demanding task, and, therefore, methods for the selection of representative days are employed to reproduce reasonably the entire year. However, the suitability of a method strongly depends on the variability of the time series involved in the system. This work compares the methods Averaging, k-Medoids and OPT for the selection of representative days by carrying out the optimization of grid-connected and standalone polygeneration systems for a building in two different locations. The suitability of the representative days obtained with each method were assessed regarding the optimization of the polygeneration systems. Sizing errors under 5% were achieved by using 14 representative days, and the computational time, with respect to the entire year data, was reduced from hours to a few seconds. The results demonstrated that the Averaging method is suitable when there is low variability in the time series data; but, when the time series presents high stochastic variability (e.g., consideration of wind energy), the OPT method presented better performance. Also, a new method has been developed for the selection of representative days by combining the k-Medoids and OPT methods, although its implementation requires additional computational effort.

Idioma: Inglés

DOI: 10.1016/j.renene.2019.11.048

Año: 2020

Publicado en: Renewable Energy 151 (2020), 488-502
ISSN: 0960-1481

Factor impacto JCR: 8.001 (2020)

Categ. JCR: GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY rank: 7 / 44 = 0.159 (2020) - Q1 - T1
Categ. JCR: ENERGY & FUELS rank: 16 / 114 = 0.14 (2020) - Q1 - T1

Factor impacto SCIMAGO: 1.825 - Renewable Energy, Sustainability and the Environment (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T55-17R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/ENE2017-87711-R

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Máquinas y Motores Térmi. (Dpto. Ingeniería Mecánica)