EVALUATION OF FORECASTING METHODS FOR PHOTOVOLTAIC SYSTEMS IN TERMS OF ACCURACY AND COMPUTATIONAL REQUIREMENTS: EVALUATION OF FORECASTING METHODS FOR PHOTOVOLTAIC SYSTEMS IN TERMS OF ACCURACY AND COMPUTATIONAL REQUIREMENTS

Iliyana Ivanova

doi:10.46687/jsar.v29i1.471

Authors

Iliyana Ivanova DEPARTMENT OF COMMUNICATION AND COMPUTER ENGINEERING AND SECURITY TECHNOLOGIES, FACULTY OF TECHNICAL SCIENCES, KONSTANTIN PRESLAVSKY UNIVERSITY OF SHUMEN, SHUMEN 9712,115, UNIVERSITETSKA STR., E-MAIL: i.s.ivanova@shu.bg

DOI:

https://doi.org/10.46687/jsar.v29i1.471

Keywords:

Photovoltaic system, Forecasting, Machine learning, Statistical models, Hybrid methods

Abstract

Forecasting photovoltaic (PV) production is an essential component for the successful integration of renewable energy into electricity grids. In this paper, four main groups of methods are evaluated: statistical, physical, machine learning-based, and hybrid. An analysis is made in terms of accuracy, computational complexity and applicability using an evaluation scale. The results show that hybrid models appear particularly promising, as they combine the main strengths of the other approaches.

Author Biography

Iliyana Ivanova, DEPARTMENT OF COMMUNICATION AND COMPUTER ENGINEERING AND SECURITY TECHNOLOGIES, FACULTY OF TECHNICAL SCIENCES, KONSTANTIN PRESLAVSKY UNIVERSITY OF SHUMEN, SHUMEN 9712,115, UNIVERSITETSKA STR., E-MAIL: i.s.ivanova@shu.bg

DEPARTMENT OF COMMUNICATION AND COMPUTER ENGINEERING AND SECURITY TECHNOLOGIES, FACULTY OF TECHNICAL SCIENCES, KONSTANTIN PRESLAVSKY UNIVERSITY OF SHUMEN, SHUMEN 9712,115, UNIVERSITETSKA STR., E-MAIL: i.s.ivanova@shu.bg

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EVALUATION OF FORECASTING METHODS FOR PHOTOVOLTAIC SYSTEMS IN TERMS OF ACCURACY AND COMPUTATIONAL REQUIREMENTS