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

Jussi Ekstrom; Matti Juhani Koivisto; Ilkka Mellin; John Millar; Matti Lehtonen

doi:10.1109/TSTE.2017.2682338

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

Jussi Ekstrom, Matti Juhani Koivisto, Ilkka Mellin, John Millar, Matti Lehtonen

Aalto University

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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 modelling 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 allows 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 analysing 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 language	English
Article number	7879358
Journal	I E E E Transactions on Sustainable Energy
Volume	8
Issue number	4
Number of pages	10
ISSN	1949-3029
DOIs	https://doi.org/10.1109/TSTE.2017.2682338
Publication status	Published - 2017

Bibliographical note

(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other work

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TSTE.2017.2682338

07879358Accepted author manuscript, 1.05 MB

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NSON-DK: North Sea Offshore Network - Denmark
Sørensen, P. E. S. (Project Coordinator), Das, K. (Project Participant), Koivisto, M. J. (Project Participant), Pade, L.-L. (Project Participant), Skytte, K. (Project Participant), Gea-Bermudez, J. (Project Participant), Papakonstantinou, A. (Project Participant), Boscán Flores, L. R. (Project Participant), Kanellas, P. (Project Participant), Plakas, K. (Project Participant), Kitzing, L. (Project Participant) & Bergaentzlé, C. M. (Project Participant)
01/04/2016 → 31/03/2020
Project: Research

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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 modelling 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 allows 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 analysing 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.",

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AU - Lehtonen, Matti

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

Abstract

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Projects

NSON-DK: North Sea Offshore Network - Denmark

Cite this