A Statistical Modeling Methodology for Long-Term Wind Generation and Power Ramp Simulations in New Generation Locations

Jussi Ekström, Matti Koivisto, Ilkka Mellin, Robert John Millar and Matti Lehtonen
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Jussi Ekström: Department of Electrical Engineering and Automation, Aalto University, FI-00076 AALTO, 02150 Espoo, Finland
Matti Koivisto: Department of Wind Energy, Technical University of Denmark (DTU), 4000 Roskilde, Denmark
Ilkka Mellin: Department of Mathematics and Systems Analysis, Aalto University, FI-00076 AALTO, 02150 Espoo, Finland
Robert John Millar: Department of Electrical Engineering and Automation, Aalto University, FI-00076 AALTO, 02150 Espoo, Finland
Matti Lehtonen: Department of Electrical Engineering and Automation, Aalto University, FI-00076 AALTO, 02150 Espoo, Finland

Energies, 2018, vol. 11, issue 9, 1-18

Abstract: In future power systems, a large share of the energy will be generated with wind power plants (WPPs) and other renewable energy sources. With the increasing wind power penetration, the variability of the net generation in the system increases. Consequently, it is imperative to be able to assess and model the behavior of the WPP generation in detail. This paper presents an improved methodology for the detailed statistical modeling of wind power generation from multiple new WPPs without measurement data. A vector autoregressive based methodology, which can be applied to long-term Monte Carlo simulations of existing and new WPPs, is proposed. The proposed model improves the performance of the existing methodology and can more accurately analyze the temporal correlation structure of aggregated wind generation at the system level. This enables the model to assess the impact of new WPPs on the wind power ramp rates in a power system. To evaluate the performance of the proposed methodology, it is verified against hourly wind speed measurements from six locations in Finland and the aggregated wind power generation from Finland in 2015. Furthermore, a case study analyzing the impact of the geographical distribution of WPPs on wind power ramps is included.

Keywords: Monte Carlo simulation; power ramps; renewable energy; vector autoregressive model; wind power 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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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