A statistical approach for hourly photovoltaic power generation modeling with generation locations without measured data

Jussi Ekström*, Matti Koivisto, John Millar, Ilkka Mellin, Matti Lehtonen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

22 Citations (Scopus)

Abstract

The use of solar energy is becoming increasingly widespread in many countries at the time of writing. Due to its stochastic nature, the increasing amount of solar generation in the generation mix has to be taken into account when planning electric power systems at both distribution and transmission system levels. The presented Monte Carlo simulation based statistical methodology is able to analyze photovoltaic generation scenarios comprising new generation locations without measured data from those locations. The introduced model is able to assess the spatial and temporal correlations between the generation locations in geographical areas of varying size and amount of installed photovoltaic generation. The model is verified against measured solar irradiance data from Finland. In addition, the paper couples a polycrystalline silicon photovoltaic panel power generation model with the statistical model and presents a case study to illustrate the applicability of the methodology for analyzing large scale solar generation.

Original languageEnglish
Pages (from-to)173-187
Number of pages15
JournalSolar Energy
Volume132
DOIs
Publication statusPublished - 1 Jul 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Monte Carlo simulation
  • Photovoltaic generation
  • Solar irradiance
  • Time-varying autoregressive model

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