Influence of rainfall on wind power generation in Northeast Brazil

Wind power has been emerging as one of the main renewable energy sources in Northeast Brazil, which concentrates 87% of the country’s installed wind capacity, especially in recent years, due to water scarcity and its seasonal energy complementarity to hydraulic generation. The objective of this article is to present a method to evaluate the influence of rainfall on the behavior of wind power generation, considering rainfall anomaly index and extreme climatic indices of precipitation. We utilized daily rainfall data from cities located near wind farms CE1 and CE2 in the state of Ceará — Aracati, in the 1974-2016 period, and Trairi, in the 1976-2016 period —, as well as daily wind power generation data for the same period, provided by the Electric System National Operator (ONS). The RClimdex software was used to calculate 11 indices of climatic extremes dependent on rainfall. The capacity factor for wind power generation was calculated for the period from 2011 to 2016 for the CE1 and CE2 wind farms. The application of this method found an inversely proportional relation between rainfall anomaly index (RAI) and the wind power capacity factor, with a decrease in total rainfall and a greater number of consecutive dry days and concentrated rain in the short term. From 2012 to 2016, the rainfall anomaly index was negative. However, wind power factors were higher than in 2011. The developed methodology can be applied to other wind farms, contributing to the medium and long term energy planning of the National Interconnected System.

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Power Electronics for Grid Integration of Wind Power Generation System

Journal of Communications Technology Electronics and Computer Science ◽

10.22385/jctecs.v9i0.129 ◽

2016 ◽

Vol 9 ◽

pp. 10 ◽

Cited By ~ 2

Author(s):

Michael S Okundamiya

Keyword(s):

Power Generation ◽

Wind Energy ◽

Power Electronics ◽

Wind Power ◽

Renewable Energy Sources ◽

Wind Power Generation ◽

Generation System ◽

Electricity Grid ◽

Power Generation System ◽

Promising Source

The rising demands for a sustainable energy system have stimulated global interests in renewable energy sources. Wind is the fastest growing and promising source of renewable power generation globally. The inclusion of wind power into the electric grid can severely impact the monetary cost, stability and quality of the grid network due to the erratic nature of wind. Power electronics technology can enable optimum performance of the wind power generation system, transferring suitable and applicable energy to the electricity grid. Power electronics can be used for smooth transfer of wind energy to electricity grid but the technology for wind turbines is influenced by the type of generator employed, the energy demand and the grid requirements. This paper investigates the constraints and standards of wind energy conversion technology and the enabling power electronic technology for integration to electricity grid.

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

Energies ◽

10.3390/en11092442 ◽

2018 ◽

Vol 11 (9) ◽

pp. 2442 ◽

Cited By ~ 3

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.

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A secondary option market design for reserve procurement by renewable energy sources.

10.32920/ryerson.14647647.v1 ◽

2021 ◽

Author(s):

Reza Ghaffari

Keyword(s):

Power Generation ◽

Power Systems ◽

Real Time ◽

Wind Power ◽

Large Scale ◽

Renewable Energy Sources ◽

Wind Power Generation ◽

Reliable Operation ◽

Actual Load ◽

Balancing Services

Wind power generation is uncertain and intermittent accentuating variability. Currently in many power systems worldwide, the total generation-load unbalance caused by mismatch between forecast and actual wind power output is handled by automatic governor control and real-time 5-minute balancing markets, which are operated by the independent system operators for maintaining reliable operation of power systems. Mechanisms such as automatic governor control and real-time 5-minute balancing markets are in place to correct the mismatch between the load forecast and the actual load. They are not designed to address increased uncertainty and variability introduced by large-scale wind power or solar power generation expected in the future. Thus, large-scale wind power generation with increased uncertainty and intermittency causing variability poses a techno-economic challenge of sourcing least cost load balancing services (reserve).

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The Impact of Imperfect Weather Forecasts on Wind Power Forecasting Performance: Evidence from Two Wind Farms in Greece

Energies ◽

10.3390/en13081880 ◽

2020 ◽

Vol 13 (8) ◽

pp. 1880 ◽

Cited By ~ 1

Author(s):

Evangelos Spiliotis ◽

Fotios Petropoulos ◽

Konstantinos Nikolopoulos

Keyword(s):

Power Generation ◽

Wind Power ◽

Renewable Energy Sources ◽

Stress Test ◽

Wind Farms ◽

Weather Variables ◽

Test Analysis ◽

Weather Forecasts ◽

Forecasting Performance ◽

The Impact

Weather variables are an important driver of power generation from renewable energy sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the power generation forecasts. In this study, we explore the impact of imperfect weather forecasts on two classes of forecasting methods (statistical and machine learning) for the case of wind power generation. We perform a stress test analysis to measure the robustness of different methods on the imperfect weather input, focusing on both the point forecasts and the 95% prediction intervals. The results indicate that different methods should be considered according to the uncertainty characterizing the weather forecasts.

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Two methods for estimating limits to large-scale wind power generation

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1408251112 ◽

2015 ◽

Vol 112 (36) ◽

pp. 11169-11174 ◽

Cited By ~ 32

Author(s):

Lee M. Miller ◽

Nathaniel A. Brunsell ◽

David B. Mechem ◽

Fabian Gans ◽

Andrew J. Monaghan ◽

...

Keyword(s):

Power Generation ◽

Kinetic Energy ◽

Wind Power ◽

Energy Flux ◽

Wind Turbines ◽

Large Scale ◽

Wind Farms ◽

Wind Power Generation ◽

Flux Method ◽

Free Atmosphere

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 105 km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m−2, whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m−2, with VKE capturing this combination in a comparatively simple way.

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Impacts of Integration of Wind Farms on Power System Transient Stability

Applied Sciences ◽

10.3390/app8081289 ◽

2018 ◽

Vol 8 (8) ◽

pp. 1289 ◽

Cited By ~ 11

Author(s):

Shiwei Xia ◽

Qian Zhang ◽

S.T. Hussain ◽

Baodi Hong ◽

Weiwei Zou

Keyword(s):

Power Generation ◽

Wind Speed ◽

Power System ◽

Wind Power ◽

Transient Stability ◽

Wind Farms ◽

Wind Power Generation ◽

Wind Generation ◽

System Operation ◽

Power System Operation

To compensate for the ever-growing energy gap, renewable resources have undergone fast expansions worldwide in recent years, but they also result in some challenges for power system operation such as the static security and transient stability issues. In particular, as wind power generation accounts for a large share of these renewable energy and reduces the inertia of a power network, the transient stability of power systems with high-level wind generation is decreased and has attracted wide attention recently. Effectively analyzing and evaluating the impact of wind generation on power transient stability is indispensable to improve power system operation security level. In this paper, a Doubly Fed Induction Generator with a two-lumped mass wind turbine model is presented firstly to analyze impacts of wind power generation on power system transient stability. Although the influence of wind power generation on transient stability has been comprehensively studied, many other key factors such as the locations of wind farms and the wind speed driving the wind turbine are also investigated in detail. Furthermore, how to improve the transient stability by installing capacitors is also demonstrated in the paper. The IEEE 14-bus system is used to conduct these investigations by using the Power System Analysis Tool, and the time domain simulation results show that: (1) By increasing the capacity of wind farms, the system instability increases; (2) The wind farm location and wind speed can affect power system transient stability; (3) Installing capacitors will effectively improve system transient stability.

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