A Statistical Model for Hourly Large-Scale Wind and Photovoltaic Generation in New Locations

Jussi Ekström, Matti Koivisto, Ilkka Mellin, Robert Millar, Matti Lehtonen

Research output: Contribution to journalArticleScientificpeer-review

28 Citations (Scopus)

Abstract

The analysis of large-scale wind and photovoltaic (PV) energy generation is of vital importance in power systems, where their penetration is high. This paper presents a modular methodology to assess the power generation and volatility of a system consisting of both PV plants (PVPs) and wind power plants (WPPs) in new locations. The methodology is based on statistical modeling of PV and WPP locations with a vector autoregressive model, which takes into account both the temporal correlations in individual plants and the spatial correlations between the plants. The spatial correlations are linked through distances between the locations, which allow the methodology to be used to assess scenarios with PVPs and WPPs in multiple locations without actual measurement data. The methodology can be applied by the transmission and distribution system operators when analyzing the effects and feasibility of new PVPs and WPPs in system planning. The model is verified against hourly measured wind speed and solar irradiance data from Finland. A case study assessing the impact of the geographical distribution of the PVPs and WPPs on aggregate power generation and its variability is presented.
Original languageEnglish
Pages (from-to)1383 - 1393
JournalIEEE Transactions on Sustainable Energy
Volume8
Issue number4
DOIs
Publication statusPublished - 15 Mar 2017
MoE publication typeA1 Journal article-refereed

Keywords

  • Monte Carlo simulation
  • photovoltaic (PV) power generation
  • renevable energy
  • vector autoregressive model
  • wind power generation

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