Next Article in Journal
Correlations to Predict Elemental Compositions and Heating Value of Torrefied Biomass
Next Article in Special Issue
Designing, Developing, and Implementing a Forecasting Method for the Produced and Consumed Electricity in the Case of Small Wind Farms Situated on Quite Complex Hilly Terrain
Previous Article in Journal
Effect of Ice Shedding on Discharge Characteristics of an Ice-Covered Insulator String during AC Flashover
Previous Article in Special Issue
Primary Frequency Controller with Prediction-Based Droop Coefficient for Wind-Storage Systems under Spot Market Rules
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessFeature PaperArticle
Energies 2018, 11(9), 2442; https://doi.org/10.3390/en11092442

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

1
Department of Electrical Engineering and Automation, Aalto University, FI-00076 AALTO, 02150 Espoo, Finland
2
Department of Wind Energy, Technical University of Denmark (DTU), 4000 Roskilde, Denmark
3
Department of Mathematics and Systems Analysis, Aalto University, FI-00076 AALTO, 02150 Espoo, Finland
*
Author to whom correspondence should be addressed.
Received: 23 August 2018 / Revised: 10 September 2018 / Accepted: 11 September 2018 / Published: 14 September 2018
(This article belongs to the Special Issue Solar and Wind Energy Forecasting)
Full-Text   |   PDF [2829 KB, uploaded 14 September 2018]   |  

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. View Full-Text
Keywords: Monte Carlo simulation; power ramps; renewable energy; vector autoregressive model; wind power generation Monte Carlo simulation; power ramps; renewable energy; vector autoregressive model; wind power generation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Ekström, J.; Koivisto, M.; Mellin, I.; Millar, R.J.; Lehtonen, M. A Statistical Modeling Methodology for Long-Term Wind Generation and Power Ramp Simulations in New Generation Locations. Energies 2018, 11, 2442.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top