A Review on Modeling Variable Renewable Energy: Complementarity and Spatial–Temporal Dependence

Anderson Mitterhofer Iung (), Fernando Luiz Cyrino Oliveira () and André Luís Marques Marcato
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Anderson Mitterhofer Iung: Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro 22451-040, Brazil
Fernando Luiz Cyrino Oliveira: Industrial Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro 22451-040, Brazil
André Luís Marques Marcato: Electrical Engineering Department, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora 36036-900, Brazil

Energies, 2023, vol. 16, issue 3, 1-24

Abstract: The generation from renewable sources has increased significantly worldwide, mainly driven by the need to reduce the global emissions of greenhouse gases, decelerate climate changes, and meet the environmental, social, and governance agenda (ESG). The main characteristics of variable renewable energy (VRE) are the stochastic nature, its seasonal aspects, spatial and time correlations, and the high variability in a short period, increasing the complexity of modeling, planning, operating, and the commercial aspects of the power systems. The research on the complementarity and dependence aspects of VREs is gaining importance, given the development of hybrid generation systems and an array of VREs generators spread over a large region, which could be compounded by different renewable sources, such as hydro, solar, and wind. This review is based on a systematic literature review, providing a comprehensive overview of studies that investigated applied methodologies and methods to address dependence and complementarity. It is a recent field of interest, as 60% of the articles were published in the last five years, a set of methods that have been employed to address this issue, from conventional statistics methods to artificial intelligence. The copulas technique appears as an important approach to modeling renewable energy interdependence. There is a gap in articles comparing the accuracy of the methods employed and the computational efforts.

Keywords: renewable energy; wind generation; hydro generation; solar generation; dependence; interdependence; correlation; scenario generation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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