scholarly journals Medium and long term wind power generation forecast based on OWA combined model and Markov chain

2021 ◽  
Vol 2005 (1) ◽  
pp. 012148
Author(s):  
Ze Gong ◽  
Qifeng Xu ◽  
Nan Xie
Keyword(s):  
Power Generation ◽  
Markov Chain ◽  
Wind Power ◽  
Wind Power Generation ◽  
Combined Model

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

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2442 ◽  
Author(s):  
Jussi Ekström ◽  
Matti Koivisto ◽  
Ilkka Mellin ◽  
Robert Millar ◽  
Matti Lehtonen
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Statistical Modeling ◽  
Renewable Energy Sources ◽  
Measurement Data ◽  
Wind Power Generation ◽  
System Level ◽  
Wind Generation ◽  
The Impact

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.

scholarly journals Wind Power Long-Term Scenario Generation Considering Spatial-Temporal Dependencies in Coupled Electricity Markets

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3427 ◽  
Author(s):  
Geovanny Marulanda ◽  
Antonio Bello ◽  
Jenny Cifuentes ◽  
Javier Reneses
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Time Scales ◽  
Electricity Markets ◽  
Distribution Functions ◽  
Wind Power Generation ◽  
Environmental Benefits ◽  
Different Time Scales ◽  
Temporal Dependencies

Wind power has been increasing its participation in electricity markets in many countries around the world. Due to its economical and environmental benefits, wind power generation is one of the most powerful technologies to deal with global warming and climate change. However, as wind power grows, uncertainty in power supply increases due to wind intermittence. In this context, accurate wind power scenarios are needed to guide decision-making in power systems. In this paper, a novel methodology to generate realistic wind power scenarios for the long term is proposed. Unlike most of the literature that tackles this problem, this paper is focused on the generation of realistic wind power production scenarios in the long term. Moreover, spatial-temporal dependencies in multi-area markets have been considered. The results show that capturing the dependencies at the monthly level could improve the quality of scenarios at different time scales. In addition, an evaluation at different time scales is needed to select the best approach in terms of the distribution functions of the generated scenarios. To evaluate the proposed methodology, several tests have been made using real data of wind power generation for Spain, Portugal and France.

Characterisation of long-term voltage stability with variable-speed wind power generation

2017 ◽  
Vol 11 (7) ◽  
pp. 1848-1855 ◽  
Author(s):  
Kanchana Amarasekara ◽  
Lasantha G. Meegahapola ◽  
Ashish P. Agalgaonkar ◽  
Sarath Perera
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Voltage Stability ◽  
Wind Power Generation ◽  
Variable Speed

scholarly journals Less Information, Similar Performance: Comparing Machine Learning-Based Time Series of Wind Power Generation to Renewables.ninja

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2277
Author(s):  
Johann Baumgartner ◽  
Katharina Gruber ◽  
Sofia G. Simoes ◽  
Yves-Marie Saint-Drenan ◽  
Johannes Schmidt
Keyword(s):  
Machine Learning ◽  
Power Generation ◽  
Time Series ◽  
Wind Power ◽  
Wind Power Generation ◽  
Location Information ◽  
Similar Performance ◽  
Input Dataset ◽  
Synthetic Time Series

Driven by climatic processes, wind power generation is inherently variable. Long-term simulated wind power time series are therefore an essential component for understanding the temporal availability of wind power and its integration into future renewable energy systems. In the recent past, mainly power curve-based models such as Renewables.ninja (RN) have been used for deriving synthetic time series for wind power generation, despite their need for accurate location information and bias correction, as well as their insufficient replication of extreme events and short-term power ramps. In this paper, we assessed how time series generated by machine learning models (MLMs) compare to RN in terms of their ability to replicate the characteristics of observed nationally aggregated wind power generation for Germany. Hence, we applied neural networks to one wind speed input dataset derived from MERRA2 reanalysis with no location information and two with additional location information. The resulting time series and RN time series were compared with actual generation. All MLM time series feature an equal or even better time series quality than RN, depending on the characteristics considered. We conclude that MLM models show a similar performance to RN, even when information on turbine locations and turbine types is unavailable.

scholarly journals Current Status and Prospective of Offshore Wind Power to Achieve Korean Renewable Energy 3020 Plan

2021 ◽  
Vol 43 (3) ◽  
pp. 196-205
Author(s):  
Minkyu Park ◽  
Seongjun Park ◽  
Byungcheol Seong ◽  
Yeonjeong Choi ◽  
Sokhee P. Jung
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Wind Power ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Offshore Wind Power ◽  
Wind Power Development

This review comprehensively reviewed floating offshore wind power generation technology, which is being newly developed as a mid- to long-term plan for wind energy. From the perspective of investment per megawatt (MW), offshore wind power is still about 50 percent more expensive than land wind power. Nevertheless, many advanced countries began to investigate the data because they wondered why they were immersed in development and investment, and why offshore wind facilities installed on the beach and floating offshore wind installed in the middle of the sea, unlike the land wind we knew. We looked at the basic principles of offshore wind power generation and the technologies used in facilities, and looked at the advantages and disadvantages of offshore wind power generation compared to land wind power generation, and what differences between fixed offshore wind farms and floating offshore wind farms. It is investigated whether it is a realistic plan to verify residents’ opposition to the installation of offshore wind power facilities, the possibility of commercialization such as high operational management costs, and the feasibility of installing facilities for renewable energy 3020 as mid- to long-term goals. In addition, it compares foreign cases with offshore wind power development complexes in Korea, marine wind power generation complexes in operation, and high wind power in Scotland, the first floating offshore wind power in Ulsan, Korea, to overcome difficulties in installing facilities and suggest directions for domestic offshore wind power development. In addition, in Korea, where there are not many countries suitable for wind power generation unlike overseas, it was decided to investigate whether floating offshore wind power could be the answer as planned. The reason why the government is pushing for investment in renewable energy such as solar power and wind power is because energy sources from the sun are eco-friendly. However, the U.S. and Europe, which started the wind power project early, are having difficulty in handling the wings of wind power generators. The energy source looked at the contradictions caused by environmental pollution in the treatment of waste, although it was environmentally friendly, and investigated how waste was treated and utilized overseas. Compared to other countries that entered the offshore wind power business earlier, domestic power generation projects are in their infancy and should focus on developing technology and co-prosperity with neighboring residents rather than on excessive expansion.

scholarly journals Multi-decadal offshore wind power variability can be mitigated through optimized European allocation

2020 ◽  
Author(s):  
Charlotte Neubacher ◽  
Jan Wohland ◽  
Dirk Witthaut
Keyword(s):  
Power Generation ◽  
Time Series ◽  
Wind Power ◽  
North Sea ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Offshore Wind Power ◽  
The North ◽  
The North Sea

<p>Wind power generation is a promising technology to reduce greenhouse gas emissions in line with the Paris Agreement.  In the recent years, the global offshore wind market grew around 30% per year but the full potential of this technology is still not fully exploited. In fact, offshore wind power has the potential to generate more than the worldwide energy demand of today. The high variability of wind on many different timescales does, however, pose serious technical challenges for system integration and system security.  With a few exceptions, little focus has been given to multi-decadal variability. Our research therefore focuses on timescales exceeding ten years.</p><p>Based on detrended wind data from the coupled centennial reanalysis CERA-20C, we calculate long-term offshore wind power generation time series across Europe and analyze their variability with a focus on the North Sea, the Mediterranean Sea and the Atlantic Ocean. Our approach is based on two independent spectral analysis methods, namely power spectral density and singular spectrum analysis. The latter is particularly well suited for relatively short and noisy time series. In both methods an AR(1)-process is considered as a realistic model for the noisy background. The analysis is complemented by computing the 20yr running mean to also gain insight into long term developments and quantify benefits of large-scale balancing.</p><p>We find strong indications for two significant multidecadal modes, which appear consistently independent of the statistical method and at all locations subject to our investigation. Moreover, we reveal potential to mitigate multidecadal offshore wind power generation variability via spatial balancing in Europe. In particular, optimized allocations off the Portuguese coast and in the North Sea allow for considerably more stable wind power generation on multi-decadal time scales.</p>

scholarly journals An Approach for Evaluating the Influence of Accessibility on Offshore Wind Power Generation

2017 ◽  
Author(s):  
Mian Du ◽  
Jun Yi ◽  
Peyman Mazidi ◽  
Lin Cheng ◽  
Jianbo Guo
Keyword(s):  
Power Generation ◽  
Markov Chain ◽  
Wind Power ◽  
Wind Farm ◽  
Weather Conditions ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Weather Data ◽  
Offshore Wind Power ◽  
Finite State

For offshore wind power generation, accessibility is one of the main factors that has great impact on operation and maintenance due to constraints on weather conditions for marine transportation. This paper presents a framework to explore the accessibility of an offshore site. At first, several maintenance types are defined and taken into account. Next, a data visualization procedure is introduced to provide an insight into the distribution of access periods over time. Then, a rigorous mathematical method based on finite state Markov chain is proposed to assess the accessibility of an offshore site from the maintenance perspective. A five-year weather data of a marine site is used to demonstrate the applicability and the outcomes of the proposed method. The main findings show that the proposed framework is effective in investigating the accessibility for different time scales and is able to catch the patterns of the distribution of the access periods. Moreover, based on the developed Markov chain, the average waiting time for a certain access period can be estimated. With more information on the maintenance of an offshore wind farm, the expected production loss due to time delay can be calculated.

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