☆ 4.5 Review

A Review on Wind Power Forecasting Regarding Impacts on the System Operation, Technical Challenges, and Applications

ENERGY TECHNOLOGY (2022)

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Article Energy & Fuels

A refined wind farm parameterization for the weather research and forecasting model

Chunlei Wu et al.

Summary: The refined wind farm parameterization has limited impact on the flow field, but the average power generation becomes more scattered and is notably decreased by nearly 7% due to the reduced variable air density. Meanwhile, the REWS slightly increases the power estimation by around 1.1%. Both REWS and variable air density can decrease the estimation uncertainty of the average power induced by complex atmospheric stability.

APPLIED ENERGY (2022)

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Article Engineering, Electrical & Electronic

Analysis of bidirectional 15 MW current source DC/DC converter for series-connected superconducting-based 1 GW/100 kV offshore wind farm

Peng Li et al.

Summary: This paper introduces a feasibility study on the design of DC/DC converters for a wind farm with series connections, where multiple series strings can be connected in parallel to increase power capacity. The advantages of using superconducting cable technology in wind power systems to reduce transmission losses are also examined.

ELECTRIC POWER SYSTEMS RESEARCH (2022)

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Article Thermodynamics

A high-accuracy hybrid method for short-term wind power forecasting

Sahra Khazaei et al.

Summary: This article proposes a high-accuracy hybrid approach for short-term wind power forecasting using historical data of wind farm and Numerical Weather Prediction (NWP) data, including three stages: wind direction forecasting, wind speed forecasting, and wind power forecasting. The method involves outlier detection, decomposition of time series, feature selection, and prediction using Multilayer Perceptron (MLP) neural network, with evaluation showing very high accuracy when tested with data from the Sotavento wind farm in Spain.

ENERGY (2022)

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Article Thermodynamics

Regional wind power probabilistic forecasting based on an improved kernel density estimation, regular vine copulas, and ensemble learning

Weichao Dong et al.

Summary: This paper proposes a regional wind power probabilistic forecasting model based on IKDE, regular vine copulas, and ensemble learning, aiming to improve the prediction accuracy of wind power generation through optimizing marginal PDF and joint distribution functions. In addition, the introduction of the MD-MTD method for prediction improvement with insufficient data has been validated, demonstrating that the proposed model performs well in wind power generation prediction.

ENERGY (2022)

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Article Thermodynamics

A data-driven deep sequence-to-sequence long-short memory method along with a gated recurrent neural network for wind power forecasting

Tanveer Ahmad et al.

Summary: Large amounts of wind power generation have significant impacts on energy markets and market design, requiring high-quality wind data series for robust policy advice. The use of the deep STSR-LSTM model for wind power forecasting overcomes challenges in model optimization and data processing capabilities, resulting in higher forecast accuracy.

ENERGY (2022)

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Article Thermodynamics

Multi-step wind speed forecasting and Hurst analysis using novel hybrid secondary decomposition approach

Cem Emeksiz et al.

Summary: A hybrid model combining CEEMDAN, LMD, Hurst, and BPNN is proposed for wind speed prediction, showing better accuracy compared to traditional methods with a decrease in MAPE values by 41.16% and 78.80%.

ENERGY (2022)

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Article Engineering, Electrical & Electronic

Value of integrated electricity and heat scheduling with considering TSO-DSO cooperation

Mahdi Habibi et al.

Summary: This study evaluates an integrated model for scheduling electricity and heat, considering TSO-DSO cooperation to increase operational efficiency and facilitate energy trading between systems. The proposed model successfully reduces operational costs and energy prices compared to isolated scheduling of energy systems, while also enhancing energy transactions between market parties.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2022)

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Article Engineering, Electrical & Electronic

An adaptive droop control strategy with smooth rotor speed recovery capability for type III wind turbine generators

Dejian Yang et al.

Summary: This paper presents an adaptive droop control scheme for DFIGs, which can improve frequency nadir, prevent DFIGs from stalling, and minimize the second drop in frequency under various conditions. Simulation results confirm the effectiveness of the proposed control scheme.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2022)

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Article Engineering, Electrical & Electronic

Multi objective control scheme on DFIG wind turbine integrated with energy storage system and FACTS devices: Steady-state and transient operation improvement

Reza Hemmati et al.

Summary: This paper introduces a novel control scheme for doubly-fed induction generators (DFIG) wind turbines, which integrates additional equipment to achieve multiple objectives such as voltage compensation, fluctuations damping, frequency regulation, and increased resilience. By designing separate control loops on DFIG, battery, and TCRTSC, and operating them coordinately, the proposed multi-purpose control plan optimally utilizes the designated components to efficiently achieve all the objectives.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2022)

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Article Green & Sustainable Science & Technology

Financing wind energy projects: An extended theory of planned behavior approach to explain private households' wind energy investment intentions in Germany

Johannes Gamel et al.

Summary: Individuals' intentions to invest in wind energy are influenced by subjective norms, perceived behavioral control, consumption profile, and investor experience, while attitudes towards wind energy investments are not a significant predictor of investment intentions. Adding consumption profile and investor profile constructs to the theoretical model can increase the share of explained variance of behavioral intention.

RENEWABLE ENERGY (2022)

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Article Green & Sustainable Science & Technology

Large-scale wind farm control using distributed economic model predictive scheme

Xiaobing Kong et al.

Summary: A distributed economic model predictive control strategy is proposed for large-scale wind farms, integrating power tracking and economic optimization into one optimal control framework, ensuring accurate tracking of reference power and global economic optimality.

RENEWABLE ENERGY (2022)

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Article Automation & Control Systems

A time series model based on hybrid-kernel least-squares support vector machine for short-term wind power forecasting

Min Ding et al.

Summary: The paper introduces a time series model based on hybrid-kernel least-squares support vector machine for short-term wind power prediction, involving processes of decomposition, classification, and reconstruction. By decomposing and classifying wind power time series, establishing support vector machine models with three different kernels, optimizing parameters, and reconstructing outputs, the model outperforms benchmark models in predicting wind power.

ISA TRANSACTIONS (2021)

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Article Energy & Fuels

Two-stage ADMM-based distributed optimal reactive power control method for wind farms considering wake effects

Zhenming Li et al.

Summary: This study proposes a two-stage reactive power optimization method based on the ADMM algorithm for optimal reactive power dispatch in wind farm-integrated distribution systems. By considering distributed reactive power flow optimization and wake effect, the proposed method improves grid voltage stability with increasing wind penetration.

GLOBAL ENERGY INTERCONNECTION-CHINA (2021)

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Article Energy & Fuels

Real-time electricity price forecasting of wind farms with deep neural network transfer learning and hybrid datasets

Haolin Yang et al.

Summary: The study investigates the impact of transfer learning on price prediction DNN representations, showing that it improves accuracy. The GRU-TL architecture, pre-trained on a hybrid dataset, outperforms statistical and deep learning benchmarks. Transfer learning enables the pre-trained DNN representation to learn target dataset features more accurately.

APPLIED ENERGY (2021)

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Article Computer Science, Artificial Intelligence

A regional pretraining-classification-selection forecasting system for wind power point forecasting and interval forecasting

Jianzhou Wang et al.

Summary: Wind power forecasting is crucial for power market transactions and system operation. The proposed system in the paper has shown accurate and reliable results in experiments, providing useful references for wind producers and managers.

APPLIED SOFT COMPUTING (2021)

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Article Engineering, Electrical & Electronic

Forecasting conditional extreme quantiles for wind energy

Carla Goncalves et al.

Summary: The translation discusses the challenges of non-parametric methods in forecasting extreme events due to data scarcity and the application of extreme value theory to address this issue, showing superior performance in wind power plant data.

ELECTRIC POWER SYSTEMS RESEARCH (2021)

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Article Green & Sustainable Science & Technology

A new hybrid multi-criteria decision-making approach for location selection of sustainable offshore wind energy stations: A case study

Mohamed Abdel-Basset et al.

Summary: This study proposes a new hybrid methodology that combines AHP and PROMETHEE-II methods for the selection of offshore wind power station location in a neutrosophic environment, addressing some shortcomings of traditional MCDM methods in this field and providing rigorous methodological support for offshore wind power station site selection.

JOURNAL OF CLEANER PRODUCTION (2021)

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Article Engineering, Electrical & Electronic

Security constrained unit commitment with continuous time-varying reserves

Elis Nycander et al.

Summary: This paper introduces a security constrained unit commitment with continuous intra-hour time-varying reserves, showing the effectiveness of this approach in ensuring N-1 security. The use of continuous time-varying reserves reduces costs and optimizes units' flexibility while maintaining N-1 security at all times. The power-based formulation enhances system security compared to the energy-based formulation, whether reserves are fixed or co-optimized in real time.

ELECTRIC POWER SYSTEMS RESEARCH (2021)

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Article Engineering, Electrical & Electronic

Intraday wind power forecasting employing feedback mechanism

Akshita Gupta et al.

Summary: The rapid expansion of Renewable Energy Sources (RES) worldwide, particularly solar and wind energy, has led to concerns regarding their intermittency and unpredictability at the grid level. This study focuses on intraday wind power forecasting using the Wavelet-ARIMA model to improve accuracy and reliability.

ELECTRIC POWER SYSTEMS RESEARCH (2021)

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Article Thermodynamics

A center-of-concentrated-based prediction interval for wind power forecasting

Hao-Han Tsao et al.

Summary: This paper presents a neural network-based method for constructing prediction interval of wind power forecasting systems to address issues such as assumptions of data distribution, large computational complexity, and difficult computation in traditional methods. Simulation results comparing different neural networks and heuristic optimizations demonstrate the effectiveness and feasibility of the proposed method.

ENERGY (2021)

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Article Thermodynamics

Data-augmented sequential deep learning for wind power forecasting

Hao Chen et al.

Summary: Accurate wind power forecasting is crucial in wind parks. Deep learning is increasingly used due to its ability to handle big data, but in-situ measured wind data are expensive and correlations between steps are often ignored. This study applies data augmentation to wind power forecasting and develops deep learning networks to improve forecasting accuracy.

ENERGY CONVERSION AND MANAGEMENT (2021)

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Article Thermodynamics

A novel decomposition-ensemble prediction model for ultra-short-term wind speed

Zhongda Tian et al.

Summary: A novel wind speed prediction model based on empirical mode decomposition and improved sparrow search algorithm optimized reinforced LSTM was proposed. Through optimization, prediction, and superimposition steps, the model achieved the best prediction performance and accuracy.

ENERGY CONVERSION AND MANAGEMENT (2021)

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Article Thermodynamics

Optimal techno-economic design of hybrid PV/wind system comprising battery energy storage: Case study for a remote area

D. Emad et al.

Summary: This study proposes a generalized mathematical model to optimize PV/wind/battery systems for remote areas, considering the challenges of energy cost and intermittent renewable energy sources. Utilizing the grey wolf optimizer (GWO), the research achieves optimal solutions with a 17% reduction in energy cost. The GWO shows better convergence trends and statistical measures compared to other meta-heuristic algorithms like PSO.

ENERGY CONVERSION AND MANAGEMENT (2021)

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Article Thermodynamics

Multi-degree-of-freedom high-efficiency wind power generation system and its optimal regulation based on short-term wind forecasting

Weichao Dong et al.

Summary: The study introduces a multi-DoF wind power generation system based on short-term wind forecasting, with a novel control strategy and a permanent-magnet synchronous wind generator replacing the yaw system in traditional wind turbines, improving operation modes and significantly increasing efficiency.

ENERGY CONVERSION AND MANAGEMENT (2021)

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Review Green & Sustainable Science & Technology

Review on optimisation methods of wind farm array under three classical wind condition problems

F. Azlan et al.

Summary: The arrangement of wind turbines in clusters can lead to decreased power generation and increased blade loads. Therefore, wind farm layout optimisation is crucial for maximizing power output. Current research focuses on maximizing energy yield and minimizing investment, with little comparison between methodologies.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

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Article Green & Sustainable Science & Technology

Wind power forecasting - A data-driven method along with gated recurrent neural network

Adam Kisvari et al.

Summary: A novel data-driven approach for wind power forecasting, integrating feature engineering and gated recurrent deep learning models, shows high predictive accuracy at lower computational costs. The Gated Recurrent Unit (GRU) outperforms the Long Short-term Memory (LSTM) algorithm, providing faster training process and less sensitivity to noise.

RENEWABLE ENERGY (2021)

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Article Computer Science, Information Systems

Investigation on stability of delayed T-S fuzzy interconnected systems via decentralized memory-based sampled-data control and validation through interconnected power systems with DFIG-based wind turbines

Lakshmanan Shanmugam et al.

Summary: This study investigates the stability of nonlinear interconnected systems with time-delays by designing a decentralized memory-based sampled-data control, and applies it to power systems with DFIG-based wind turbines. Through constructing Lyapunov-Krasovskii functional and utilizing linear matrix inequalities, delay-dependent stability conditions are derived to ensure the effective stabilization of the interconnected systems. Experimental results confirm the effectiveness of the derived theoretical conditions under the designed controller.

INFORMATION SCIENCES (2021)

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Article Energy & Fuels

A novel hybrid model based on Bernstein polynomial with mixture of Gaussians for wind power forecasting

Yingchao Dong et al.

Summary: This study proposes a new hybrid forecasting model that decomposes wind power time series and combines Gaussian mixture with Bernstein polynomial model to achieve accurate and stable wind power forecasting. Experimental results demonstrate that the hybrid model has higher accuracy and stability compared to other popular models.

APPLIED ENERGY (2021)

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Article Computer Science, Artificial Intelligence

Modes decomposition forecasting approach for ultra-short-term wind speed

Zhongda Tian

Summary: This paper proposes a forecasting approach for ultra-short-term wind speed based on adaptive variational mode decomposition and weighted combination models, aiming to improve prediction accuracy by optimizing the weight coefficients of multiple models. The proposed approach shows promising prediction performance on measured data.

APPLIED SOFT COMPUTING (2021)

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Article Thermodynamics

Short-term predictions of multiple wind turbine power outputs based on deep neural networks with transfer learning

Xin Liu et al.

Summary: This paper proposes a novel deep and transfer learning framework (DETL) for developing data-driven wind power prediction models. DETL separates data into source and target domains, extracts features, and trains prediction models efficiently.

ENERGY (2021)

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Article Green & Sustainable Science & Technology

Very short-term forecasting of wind power generation using hybrid deep learning model

Md Alamgir Hossain et al.

Summary: In this paper, a novel hybrid deep learning model is proposed to improve the prediction accuracy of very short-term wind power generation. The hybrid model shows superior performance in accuracy over other forecasting models.

JOURNAL OF CLEANER PRODUCTION (2021)

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Article Engineering, Multidisciplinary

Design and validation of an adaptive low-power detection algorithm for three-cup anemometer

Yongqing Bai et al.

Summary: An adaptive low-power detection algorithm for a cup anemometer has been designed, utilizing a normal distribution model for signal processing to improve performance and achieve low power consumption, with experiments showing low mean velocity error.

MEASUREMENT (2021)

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Article Green & Sustainable Science & Technology

Wind energy harnessing on tall buildings in urban environments

Petar Skvorc et al.

Summary: Wind energy harnessing on tall buildings in urban environments is a rapidly developing renewable energy technology. This technology is influenced by terrain type, local wind characteristics, urban environment, and building architecture. The study outlines key points related to urban wind energy harnessing by critically assessing existing literature, highlighting the importance of urban wind environment, wind resource assessment, and wind-turbine design, with a case study analyzing the combined influence of these features. Vertical axis wind turbines are generally more efficient in turbulent flow and less noisy, making them a better choice for tall buildings in urban environments, although there are also successful examples of horizontal axis wind turbines.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

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Article Green & Sustainable Science & Technology

Wind power 24-h ahead forecast by an artificial neural network and an hybrid model: Comparison of the predictive performance

Emanuele Ogliari et al.

Summary: With the continuous expansion of global wind energy installed capacity, there is a growing demand for reliable wind power forecasting methods. The study shows that data-driven approaches outperform traditional physical models in daily wind power prediction.

RENEWABLE ENERGY (2021)

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Article Green & Sustainable Science & Technology

Getting more with less? Why repowering onshore wind farms does not always lead to more wind power generation-A German case study

Jan Frederick Unnewehr et al.

Summary: The best wind locations are often occupied by old, less efficient turbines, leading to the importance of repowering. However, changing social acceptance and land use restrictions are limiting the available area for repowering. A study in Germany shows that under regional criteria, repowering would decrease operating capacity and annual energy yield by roughly 40% compared to the status quo.

RENEWABLE ENERGY (2021)

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Article Green & Sustainable Science & Technology

A novel forecasting model for wind speed assessment using sentinel family satellites images and machine learning method

M. Majidi Nezhad et al.

Summary: Wind energy production in near and offshore farms is on the rise due to new technologies and decreased economic costs. Satellite data is used for wind speed mapping, and artificial intelligence methods are increasingly being used for predicting wind energy production, with a new forecasting model integrating Sentinel satellite imagery analysis and machine learning methods showing higher accuracy than other models.

RENEWABLE ENERGY (2021)

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Article Green & Sustainable Science & Technology

Feature extraction of meteorological factors for wind power prediction based on variable weight combined method

Peng Lu et al.

Summary: A novel combined approach for wind power prediction is proposed in this paper, which utilizes NWP data and historical wind power to improve accuracy through feature extraction, ELM and LSSVM model design, and parameter optimization. The proposed method achieves higher accuracy in various error metrics compared to other benchmark prediction models.

RENEWABLE ENERGY (2021)

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Article Thermodynamics

Probabilistic estimation model of power curve to enhance power output forecasting of wind generating resources

Eunjeong Yun et al.

Summary: This paper proposes a probabilistic power curve estimation method to enhance power output forecasting of wind generating resources, utilizing probabilistic methods and spatial interpolation techniques to improve accuracy.

ENERGY (2021)

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Article Thermodynamics

An extended new approach for forecasting short-term wind power using modified fuzzy wavelet neural network: A case study in wind power plant

Saeid Jafarzadeh Ghoushchi et al.

Summary: This article aims to predict the power output of a wind power plant using an extended fuzzy wavelet neural network (FWNN), which combines Particle Swarm Optimization (PSO) and Gradient Descent algorithms for higher precision and efficiency. The method proved to be more efficient and precise compared to conventional prediction methods for short-term wind power forecasting.

ENERGY (2021)

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Article Computer Science, Hardware & Architecture

Optimization of wind power plant sizing and placement by the application of multi-objective genetic algorithm (GA) in Madhya Pradesh, India

Manoj Verma et al.

Summary: This paper proposes an optimization technique to estimate the optimal size of wind power plants in different districts of Madhya Pradesh, India, and suggests constructing small wind power plants in each district to reduce dependence on the grid. The multi-objective problem is solved via the genetic algorithm, aiming to minimize the RMS value of demand inaccuracy while considering the cost of power generated.

SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS (2021)

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Article Construction & Building Technology

Forecasting high penetration of solar and wind power in the smart grid environment using robust ensemble learning approach for large-dimensional data

Tanveer Ahmad et al.

Summary: The study introduces an ensemble-based k-nearest neighbor algorithm for wind and solar power forecasting, utilizing a deep architecture to enhance modeling complexity and accuracy. Validation of the algorithm's accuracy is achieved through forecasts in different climate areas and experimental setups.

SUSTAINABLE CITIES AND SOCIETY (2021)

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Review Green & Sustainable Science & Technology

Decision-making methodologies in offshore wind power investments: A review

Qian Liu et al.

Summary: This paper conducts a systematic literature review of methodologies commonly used in offshore wind power investment decision-making. The classification and analysis of these methods from recent years aim to provide broad, systematic approaches and tools, while also emphasizing recommendations for method selection in different situations.

JOURNAL OF CLEANER PRODUCTION (2021)

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Article Energy & Fuels

Integral sliding mode control for DFIG based WECS with MPPT based on artificial neural network under a real wind profile

Hamid Chojaa et al.

Summary: A robust integral sliding mode control (ISMC) with Lyapunov function was proposed for controlling the active and reactive powers of a doubly fed induction generator (DFIG) based wind turbine, achieving high dynamic performances. Through a robust MPPT algorithm with mechanical speed control and artificial Neural Network Controller (ANNC), the system operated around an optimal rotational speed to extract maximum power. The effectiveness and robustness of the control methods were demonstrated through testing in MATLAB/Simulink environment, showing superior performance in dynamic response, total harmonic distortion, reference tracking ability, etc.

ENERGY REPORTS (2021)

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Article Energy & Fuels

Condition monitoring and performance forecasting of wind turbines based on denoising autoencoder and novel convolutional neural networks

Xiongjie Jia et al.

Summary: With the increasing proportion of wind power in the grid, the monitoring and maintenance of wind turbines are becoming more important. This study presents a data-driven modelling framework based on deep learning for effective monitoring of wind turbines and prediction of performance, which is validated through experiments.

ENERGY REPORTS (2021)

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Article Energy & Fuels

A combination forecasting model of wind speed based on decomposition

Zhongda Tian et al.

Summary: This paper proposes a novel wind speed combination forecasting model based on decomposition, which addresses the issue of wind power output instability by introducing variational mode decomposition algorithm and echo state network. The developed forecasting model shows higher prediction accuracy and is capable of reflecting the change laws of wind speed correctly.

ENERGY REPORTS (2021)

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Article Energy & Fuels

Promoted supercapacitor control scheme based on robust fractional-order super-twisting sliding mode control for dynamic voltage restorer to enhance FRT and PQ capabilities of DFIG-based wind turbine

Ali Darvish Falehi et al.

Summary: This study focuses on the fault ride-through capability and power quality issues of doubly-fed induction generators (DFIG) according to grid code requirements. Two innovative technologies are proposed: a new multilevel inverter and a robust fractional-order super-twisting sliding mode controller. These technologies can enhance the compensation capability of the dynamic voltage restorer (DVR) and improve the FRT and PQ capabilities of DFIG wind turbines.

JOURNAL OF ENERGY STORAGE (2021)

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Article Green & Sustainable Science & Technology

Land suitability assessment for wind farms through best-worst method and GIS in Balikesir province of Turkey

Emre Tercan

Summary: This study developed an ecomentalist land suitability model based on GIS-BWM to identify optimal locations for wind farms and evaluate existing planning preferences. The findings show that environmental conditions, land use features, and disaster conditions were not fully considered in a certain percentage of real planning preferences.

SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS (2021)

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Article Chemistry, Physical

Wind power production from very large offshore wind farms

Sara C. Pryor et al.

Summary: The study shows that offshore wind energy lease areas along the U.S. east coast have a great potential for power production, but this is reduced by wake effects. The wake effects can extend up to 90 km under certain flow conditions, and the area with a velocity deficit is 2.6 times larger than the footprint of the lease areas.

JOULE (2021)

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Article Economics

Efficient spatial distribution of wind power plants given environmental externalities due to turbines and grids

Kristine Grimsrud et al.

Summary: This paper proposes an environmental taxation scheme that can effectively achieve spatial distribution of new wind power production, reducing social costs. The analysis shows that implementing a tax scheme can lower the environmental and social costs of wind power production in Norway, and that the environmental costs associated with turbines and power lines are crucial for effective spatial allocation.

ENERGY ECONOMICS (2021)

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Article Multidisciplinary Sciences

Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid

Danilo P. E. Silva et al.

Summary: This article discusses the use of weather and power data to solve the economic dispatch problem of a microgrid, utilizing hybrid model predictive control with weather data from automatic stations. It provides five datasets for each weather station, including weather data downloaded from the National Meteorological Institute website, processed weather data, and files containing measured and forecasted power information.

DATA IN BRIEF (2021)

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Article Energy & Fuels

Multi-Objective Optimization and Dispatch of Distributed Energy Resources for Renewable Power Utilization Considering Time-of-Use Tariff

Qinhao Xing et al.

Summary: This paper proposes an optimization and dispatch model of an aggregation of Distributed Energy Resources for multi-objective optimization, considering day-ahead demand forecast, wind and solar generation forecast, electric vehicles charging routines, energy storage and DC power flow constraints. The model simultaneously optimizes operating cost, renewable energy utilization, and revenues of storages and electric vehicles through min-max unification method. The study demonstrates the model's ability to reconcile all participants in the system, with sensitivity analysis done on the impact of initial states of storages on resource owners' revenues.

FRONTIERS IN ENERGY RESEARCH (2021)

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Article Energy & Fuels

Multi-step short-term wind speed prediction based on integrated multi-model fusion

Zhongda Tian et al.

Summary: The proposed wind speed prediction approach is based on mode decomposition and multi-model fusion, utilizing support vector machine and stochastic configuration network for prediction models, with parameter optimization using particle swarm optimization algorithm. Results show improved accuracy compared to state-of-the-art models, demonstrating the effectiveness of the integrated multi-model fusion approach in enhancing wind speed prediction.

APPLIED ENERGY (2021)

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Article Computer Science, Artificial Intelligence

Short-term wind power prediction based on EEMD-LASSO-QRNN model

Yaoyao He et al.

Summary: The study proposes a novel wind power forecasting method based on EEMD and LASSO-QRNN model, integrating various technologies to enhance the accuracy and robustness of wind power prediction, successfully demonstrating superiority on multiple datasets.

APPLIED SOFT COMPUTING (2021)

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Article Computer Science, Hardware & Architecture

Optimal speed-torque control of doubly-fed induction motors: Analytical and graphical analysis

Mouna Zerzeri et al.

Summary: This paper proposes an optimized control approach of a Doubly-Fed Induction Motor (DFIM) based on a field weakening algorithm, achieving nearly doubled torque-speed operation region. By investigating the active power distribution law between the stator and rotor sides, a Stator Flux Oriented Control and decoupled control between torque and flux are implemented. Integration of a Sliding Mode Flux Observer ensures sensorless command and enhances performance in achieving maximum torque in a wide speed range.

COMPUTERS & ELECTRICAL ENGINEERING (2021)

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Article Automation & Control Systems

Exact output regulation for wind turbine active power control

Mostafa Karimpour et al.

Summary: This paper investigates the application of a classical control methodology known as exact output regulation to improve wind turbine output power regulation. By designing torque and pitch control input signals using wind preview information, the method shows potential to enhance wind turbine capability for frequency regulation services.

CONTROL ENGINEERING PRACTICE (2021)

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Article Engineering, Electrical & Electronic

Nonlinear rotor side converter control of DFIG based wind energy system

Ravi Patel et al.

Summary: This study introduces an alternative approach to controlling the rotor side converter of a doubly-fed induction generator based wind energy conversion system using command-filtered integral backstepping principle. The proposed controller shows superior performance compared to classical controllers and effectively stabilizes the rotor speed.

ELECTRIC POWER SYSTEMS RESEARCH (2021)

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Article Engineering, Electrical & Electronic

Novel multilevel STATCOM for power system stability enhancement on DFIG-based wind farms

R. S. Camargo et al.

Summary: This study introduces an evaluation of a multilevel topology based on SDC-CHB for supporting DFIG wind farm operation, tested on the Hydro-Quebec system, showing improved power system stability and quality. The proposed topology demonstrates enhanced performance compared to classical multilevel converters for DFIG fault ride-through.

ELECTRIC POWER SYSTEMS RESEARCH (2021)

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Article Energy & Fuels

A Machine Learning-Based Gradient Boosting Regression Approach for Wind Power Production Forecasting: A Step towards Smart Grid Environments

Upma Singh et al.

Summary: This study compares five optimized robust regression machine learning methods for improving the forecasting accuracy of short-term wind energy generation in Turkish wind farms. Results demonstrate that the algorithm incorporating gradient boosting machine regression shows superior forecasting performance.

ENERGIES (2021)

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Article Thermodynamics

An improved deep belief network based hybrid forecasting method for wind power

Shuai Hu et al.

Summary: This paper presents a hybrid forecasting method combining PCA and DBN to improve the accuracy of wind power generation forecasting. The proposed improved DBN and wind speed correction model demonstrated an average increase in forecasting accuracy of 15.8975% and 29.3725%, respectively, compared to traditional methods.

ENERGY (2021)

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Article Thermodynamics

Hourly day-ahead wind power forecasting at two wind farms in northeast Brazil using WRF model

William Duarte Jacondino et al.

Summary: The study investigated the impact of different physics parameterization on wind speed forecasting in two onshore wind farms in Brazil. The findings suggest that specific model forecast settings perform better, with the TKE closure scheme showing superior performance.

ENERGY (2021)

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Article Thermodynamics

Methodological framework for short-and medium-term energy, solar and wind power forecasting with stochastic-based machine learning approach to monetary and energy policy applications

Tanveer Ahmad et al.

Summary: The study proposes a Gaussian stochastic-based machine learning process model for short/medium-term energy, solar, and wind power forecasts, demonstrating promising accuracy and reliability through multiple experimental steps and various methods for validation.

ENERGY (2021)

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Article Engineering, Civil

Approach for Short-Term Traffic Flow Prediction Based on Empirical Mode Decomposition and Combination Model Fusion

Zhongda Tian

Summary: This paper proposes a novel short-term traffic flow prediction approach based on empirical mode decomposition and combination model fusion, which outperforms state-of-the-art prediction methods or models in short-term traffic flow prediction according to experimental results.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021)

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Article Engineering, Electrical & Electronic

Short term load forecasting with markovian switching distributed deep belief networks

Yi Dong et al.

Summary: In this study, a novel distributed deep belief networks (DDBN) method is proposed for accurate short-term load forecasting. By using a designed consensus procedure and a Markovian switching topology, the method enhances both network reliability and forecasting accuracy.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2021)

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Article Environmental Sciences

Changes in flight paths of large-bodied birds after construction of large terrestrial wind turbines

Ole R. Therkildsen et al.

Summary: The study tracked the flight trajectories of large-bodied birds near wind turbines and found that these birds made significant vertical and horizontal adjustments after the turbines were constructed, reducing the risk of collision with the turbines. This has implications for current collision risk models used to predict avian turbine collision rates.

JOURNAL OF ENVIRONMENTAL MANAGEMENT (2021)

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Review Green & Sustainable Science & Technology

Offshore wind turbine operations and maintenance: A state-of-the-art review

Zhengru Ren et al.

Summary: Operations and maintenance of offshore wind turbines (OWTs) are essential for the development of offshore wind farms. Maintenance, in particular, plays a crucial role in the overall cost of energy due to practical constraints and high costs associated with offshore operations. The impact of maintenance on the life cycle of offshore wind farms is complex and uncertain, with maintenance strategies significantly affecting efficiency, profitability, safety, and sustainability. Onsite maintenance involves intricate marine operations that rely on practical factors for efficiency and safety, while potential negative environmental impacts also need to be considered.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

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Article Energy & Fuels

Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks

Yuhao Nie et al.

Summary: The study aims to address the imbalance in sky image datasets for PV output prediction, showing that resampling and data augmentation can effectively enhance model performance for now-casting tasks but have limited impact on forecasting tasks.

SOLAR ENERGY (2021)

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Article Automation & Control Systems

Approach for short-term wind power prediction via kernel principal component analysis and echo state network optimized by improved particle swarm optimization algorithm

Zhongda Tian

Summary: This paper proposes a novel wind power prediction approach based on kernel principal component analysis and an improved particle swarm optimization algorithm for optimizing the echo state network. The method reduces input variables, improves network stability, and shows good prediction performance compared to other state-of-the-art models.

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL (2021)

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Article Green & Sustainable Science & Technology

A new ANN model for hourly solar radiation and wind speed prediction: A case study over the north & south of the Arabian Peninsula

Bashar Shboul et al.

Summary: A new technique based on FBANN model was developed to predict both hourly solar radiation and wind speed simultaneously, achieving high levels of accuracy with R values exceeding 0.96 and MAPE not exceeding 3% across all investigated locations in the Northern and Southern regions of the Arabian Peninsula.

SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS (2021)

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Proceedings Paper Automation & Control Systems

Application of Neural Network Fitting for Pitch Angle Control of Small Wind Turbines

Mohamed E. M. Salem et al.

Summary: In this study, a small pitch-controlled wind turbine model was designed, constructed and tested in a wind tunnel. The use of a linkage mechanism and a DC servo-motor to control the pitch angle proved to be efficient and convenient for small wind turbines. A neural network fitting function was employed to achieve power output control at wind speeds above the rated speed, successfully meeting the required power curve.

IFAC PAPERSONLINE (2021)

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Proceedings Paper Materials Science, Multidisciplinary

Wind power forecasting based on time series model using deep machine learning algorithms

V. Chandran et al.

Summary: Wind energy is a sustainable and renewable energy source, but wind power plants face challenges. By using deep learning algorithms to predict short-term wind power generation, the study demonstrates that machine learning models can be effectively applied in new geographical areas.

MATERIALS TODAY-PROCEEDINGS (2021)

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Article Multidisciplinary Sciences

Operational planning steps in smart electric power delivery system

M. Jayachandran et al.

Summary: This paper reviews advanced technologies and control approaches for power grids, including distributed energy storage control, electric vehicle charging technologies, power system frequency stability techniques, information management and security in the smart grid, and future research trends in smart grids. These technologies aim to achieve reliable, resilient, and stable operation of the cyber-physical power system, ultimately paving the way for clean energy technology and the restructuring of conventional power systems into robust smart distribution grids.

SCIENTIFIC REPORTS (2021)

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Article Multidisciplinary Sciences

Two -stage short -term wind power forecasting algorithm using different feature models

Jiancheng Qin et al.

Summary: The study developed four deep neural networks for learning wind power data features in the first stage, proposed a new moving window-based algorithm, and investigated the model extrapolation issue in the second stage. Experimental results showed that the model with single-input-multiple-output structure outperformed existing models in wind power forecasting.

FUNDAMENTAL RESEARCH (2021)

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Article Energy & Fuels

Short-Term Building Electrical Energy Consumption Forecasting by Employing Gene Expression Programming and GMDH Networks

Kasim Zor et al.

ENERGIES (2020)

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Article Thermodynamics

Using atmospheric inputs for Artificial Neural Networks to improve wind turbine power prediction

Jordan Nielson et al.

ENERGY (2020)

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Article Thermodynamics

Medium-term wind power forecasting based on multi-resolution multi-learner ensemble and adaptive model selection

Chao Chen et al.

ENERGY CONVERSION AND MANAGEMENT (2020)

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Article Engineering, Civil

Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting

Ganggang Zuo et al.

JOURNAL OF HYDROLOGY (2020)

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Article Engineering, Multidisciplinary

Novel wind measurement via thermoelectric anemometer

Nataporn Korprasertsak et al.

MEASUREMENT (2020)

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Article Energy & Fuels

A prediction approach using ensemble empirical mode decomposition-permutation entropy and regularized extreme learning machine for short-term wind speed

Zhongda Tian et al.

WIND ENERGY (2020)

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Article Energy & Fuels

A Comprehensive Wind Power Forecasting System Integrating Artificial Intelligence and Numerical Weather Prediction

Branko Kosovic et al.

ENERGIES (2020)

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Article Engineering, Multidisciplinary

Short-term wind speed prediction based on LMD and improved FA optimized combined kernel function LSSVM

Zhongda Tian

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

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Article Green & Sustainable Science & Technology

Wind turbine power output very short-term forecast: A comparative study of data clustering techniques in a PSO-ANFIS model

Paul A. Adedeji et al.

JOURNAL OF CLEANER PRODUCTION (2020)

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Review Engineering, Industrial

Bayesian Network Modelling for the Wind Energy Industry: An Overview

Tosin Adedipe et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2020)

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Review Green & Sustainable Science & Technology

Wind Generation Forecasting Methods and Proliferation of Artificial Neural Network: A Review of Five Years Research Trend

Muhammad Shahzad Nazir et al.

SUSTAINABILITY (2020)

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Article Computer Science, Hardware & Architecture

Grid connected wind energy system through a back-to-back converter

Ahmed Tahir et al.

COMPUTERS & ELECTRICAL ENGINEERING (2020)

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Review Energy & Fuels

A Critical Review of Wind Power Forecasting Methods-Past, Present and Future

Shahram Hanifi et al.

ENERGIES (2020)

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Article Thermodynamics

A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets

Gholamreza Memarzadeh et al.

ENERGY CONVERSION AND MANAGEMENT (2020)

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Article Green & Sustainable Science & Technology

Data-driven weather forecasting models performance comparison for improving offshore wind turbine availability and maintenance

Ravi Kumar Pandit et al.

IET RENEWABLE POWER GENERATION (2020)

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Article Green & Sustainable Science & Technology

Study on environment-concerned short-term load forecasting model for wind power based on feature extraction and tree regression

Jicheng Liu et al.

JOURNAL OF CLEANER PRODUCTION (2020)

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Article Automation & Control Systems

Backtracking search optimization algorithm-based least square support vector machine and its applications

Zhongda Tian

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

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Article Green & Sustainable Science & Technology

Prediction of offshore wind farm power using a novel two-stage model combining kernel-based nonlinear extension of the Arps decline model with a multi-objective grey wolf optimizer

Hongfang Lu et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)

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Article Green & Sustainable Science & Technology

Forecasting energy consumption and wind power generation using deep echo state network

Huanling Hu et al.

RENEWABLE ENERGY (2020)

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Article Green & Sustainable Science & Technology

Uncertain wind power forecasting using LSTM-based prediction interval

Abhishek Banik et al.

IET RENEWABLE POWER GENERATION (2020)

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Article Mathematics, Interdisciplinary Applications

Preliminary Research of Chaotic Characteristics and Prediction of Short-Term Wind Speed Time Series

Zhongda Tian

INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS (2020)

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Article Engineering, Electrical & Electronic

Real-time emergency demand response strategy for optimal load dispatch of heat and power micro-grids

Hongbo Cui et al.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2020)

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Article Engineering, Electrical & Electronic

On the development of organized nodal local energy markets and a framework for the TSO-DSO coordination

Alex Papalexopoulos et al.

ELECTRIC POWER SYSTEMS RESEARCH (2020)

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Article Thermodynamics

A novel deep learning intelligent clustered hybrid models for wind speed and power forecasting

Hamed H. H. Aly

ENERGY (2020)

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Article Engineering, Electrical & Electronic

Componentnet: Processing U- and V-components for spatio-Temporal wind speed forecasting

Bruno Quaresma Bastos et al.

ELECTRIC POWER SYSTEMS RESEARCH (2020)

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Review Thermodynamics

A review on multi-objective optimization framework in wind energy forecasting techniques and applications

Hui Liu et al.

ENERGY CONVERSION AND MANAGEMENT (2020)

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Article Geography

Mapping the subaquatic animals in the Aquatocene: Offshore wind power, the materialities of the sea and animal soundscapes

Chi-Mao Wang et al.

POLITICAL GEOGRAPHY (2020)

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Article Economics

The role of feed-in tariff in the curtailment of wind power in China

Fang Xia et al.

ENERGY ECONOMICS (2020)

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Review Computer Science, Interdisciplinary Applications

Current advances and approaches in wind speed and wind power forecasting for improved renewable energy integration: A review

Madasthu Santhosh et al.

ENGINEERING REPORTS (2020)

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Review Engineering, Multidisciplinary

Wind Power Forecasting Methods Based on Deep Learning: A Survey

Xing Deng et al.

CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES (2020)

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Article Computer Science, Information Systems

Reactive Voltage Partitioning Method for the Power Grid With Comprehensive Consideration of Wind Power Fluctuation and Uncertainty

Xu Zhang et al.

IEEE ACCESS (2020)

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Article Computer Science, Artificial Intelligence

Short-term prediction of wind power using a hybrid pseudo-inverse Legendre neural network and adaptive firefly algorithm

S. P. Mishra et al.

NEURAL COMPUTING & APPLICATIONS (2019)

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Review Engineering, Industrial

Maintenance optimization and inspection planning of wind energy assets: Models, methods and strategies

Mahmood Shafiee et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

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Article Computer Science, Artificial Intelligence

Short-term wind power prediction based on improved small-world neural network

Shuang-Xin Wang et al.

NEURAL COMPUTING & APPLICATIONS (2019)

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Article Energy & Fuels

Short-term wind speed prediction based on improved PSO algorithm optimized EM-ELM

Zhongda Tian et al.

ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS (2019)

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Article Automation & Control Systems

Real-time Neural Input-Output Feedback Linearization control of DFIG based wind turbines in presence of grid disturbances

Larbi Djilali et al.

CONTROL ENGINEERING PRACTICE (2019)

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Review Green & Sustainable Science & Technology

A review on the selected applications of forecasting models in renewable power systems

Adil Ahmed et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2019)

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Article Energy & Fuels

Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network

Shuang Han et al.

APPLIED ENERGY (2019)

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Review Energy & Fuels

Modeling wind power investments, policies and social benefits for deregulated electricity market - A review

Lakshmi Chinmoy et al.

APPLIED ENERGY (2019)

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Article Meteorology & Atmospheric Sciences

Improving WRF model turbine-height wind-speed forecasting using a surrogate- based automatic optimization method

Zhenhua Di et al.

ATMOSPHERIC RESEARCH (2019)

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Review Thermodynamics

Deterministic wind energy forecasting: A review of intelligent predictors and auxiliary methods

Hui Liu et al.

ENERGY CONVERSION AND MANAGEMENT (2019)

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Article Thermodynamics

Wind power forecasting based on daily wind speed data using machine learning algorithms

Halil Demolli et al.

ENERGY CONVERSION AND MANAGEMENT (2019)

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Article Green & Sustainable Science & Technology

Seasonal forecasts of wind power generation

Ll. Lledo et al.

RENEWABLE ENERGY (2019)

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Article Engineering, Multidisciplinary

Calculating reserve power requirements from wind-power forecasts

Aoran Xu et al.

JOURNAL OF ENGINEERING-JOE (2019)

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Article Computer Science, Information Systems

Current Perspective on the Accuracy of Deterministic Wind Speed and Power Forecasting

Muhammad Uzair Yousuf et al.

IEEE ACCESS (2019)

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Article Computer Science, Information Systems

Data Mining-Based Upscaling Approach for Regional Wind Power Forecasting: Regional Statistical Hybrid Wind Power Forecast Technique (RegionalSHWIP)

Mehmet Baris Ozkan et al.

IEEE ACCESS (2019)

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Article Energy & Fuels

A survey of artificial neural network in wind energy systems

Alberto Pliego Marugan et al.

APPLIED ENERGY (2018)

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Article Meteorology & Atmospheric Sciences

Evaluating anemometer drift: A statistical approach to correct biases in wind speed measurement

Cesar Azorin-Molina et al.

ATMOSPHERIC RESEARCH (2018)

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Article Energy & Fuels

Research and Application of a Hybrid Wind Energy Forecasting System Based on Data Processing and an Optimized Extreme Learning Machine

Rui Wang et al.

ENERGIES (2018)

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Article Thermodynamics

Short-term power output forecasting of hourly operation in power plant based on climate factors and effects of wind direction and wind speed

Mojtaba Dadkhah et al.

ENERGY (2018)

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Article Economics

DSO-TSO cooperation issues and solutions for distribution grid congestion management

Samson Yemane Hadush et al.

ENERGY POLICY (2018)

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Article Energy & Fuels

Conceptual framework for introducing incentive-based demand response programs for retail electricity markets

Rajeev Alasseri et al.

ENERGY STRATEGY REVIEWS (2018)

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Article Computer Science, Artificial Intelligence

Short-term wind speed and wind power prediction using hybrid empirical mode decomposition and kernel ridge regression

Jyotirmayee Naik et al.

APPLIED SOFT COMPUTING (2018)

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Article Environmental Sciences

Response to Noise Emitted by Wind Farms in People Living in Nearby Areas

Malgorzata Pawlaczyk-Luszczynska et al.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2018)

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Article Computer Science, Hardware & Architecture

Microgrid protection under wind speed intermittency using extreme learning machine

Murli Manohar et al.

COMPUTERS & ELECTRICAL ENGINEERING (2018)

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Article Thermodynamics

Micro-siting optimization of a wind farm built in multiple phases

Mengxuan Song et al.

ENERGY (2017)

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Article Green & Sustainable Science & Technology

Short-term wind forecast of a data assimilation/weather forecasting system with wind turbine anemometer measurement assimilation

William Y. Y. Cheng et al.

RENEWABLE ENERGY (2017)

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Article Energy & Fuels

Optimal Maintenance Management of Offshore Wind Farms

Alberto Pliego Marugan et al.

ENERGIES (2016)

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Article Engineering, Electrical & Electronic

Improving Large Scale Day-Ahead Security Constrained Unit Commitment Performance

Yonghong Chen et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2016)

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Review Green & Sustainable Science & Technology

Wind speed and solar irradiance forecasting techniques for enhanced renewable energy integration with the grid: a review

Edward Baleke Ssekulima et al.

IET RENEWABLE POWER GENERATION (2016)

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Review Green & Sustainable Science & Technology

The role of communications and standardization in wind power applications - A review

S. M. Alizadeh et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2016)

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Review Green & Sustainable Science & Technology

Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models

Jianzhou Wang et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2016)

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Article Green & Sustainable Science & Technology

Machine learning ensembles for wind power prediction

Justin Heinermann et al.

RENEWABLE ENERGY (2016)

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Article Green & Sustainable Science & Technology

Wind turbine power curve modelling using artificial neural network

Francis Pelletier et al.

RENEWABLE ENERGY (2016)

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Article Green & Sustainable Science & Technology

Quantifying the Economic and Grid Reliability Impacts of Improved Wind Power Forecasting

Qin Wang et al.

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2016)

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Article Thermodynamics

Aggregated wind power generation probabilistic forecasting based on particle filter

Pai Li et al.

ENERGY CONVERSION AND MANAGEMENT (2015)

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Article Thermodynamics

Prospects of solar photovoltaic-micro-wind based hybrid power systems in western Himalayan state of Himachal Pradesh in India

Sunanda Sinha et al.

ENERGY CONVERSION AND MANAGEMENT (2015)

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Article Automation & Control Systems

Seasonal Analysis and Prediction of Wind Energy Using Random Forests and ARX Model Structures

Yujie Lin et al.

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2015)

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Review Green & Sustainable Science & Technology

Reviews on uncertainty analysis of wind power forecasting

Jie Yan et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2015)

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Article Green & Sustainable Science & Technology

Wind speed prediction in the mountainous region of India using an artificial neural network model

P. Ramasamy et al.

RENEWABLE ENERGY (2015)

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Article Green & Sustainable Science & Technology

Direct torque control of multilevel SVPWM inverter in variable speed SCIG-based wind energy conversion system

H. Merabet Boulouiha et al.

RENEWABLE ENERGY (2015)

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Article Computer Science, Interdisciplinary Applications

Grey Wolf Optimizer

Seyedali Mirjalili et al.

ADVANCES IN ENGINEERING SOFTWARE (2014)

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Article Engineering, Electrical & Electronic

Optimal Prediction Intervals of Wind Power Generation

Can Wan et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2014)

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Article Engineering, Electrical & Electronic

Variational Mode Decomposition

Konstantin Dragomiretskiy et al.

IEEE TRANSACTIONS ON SIGNAL PROCESSING (2014)

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Review Green & Sustainable Science & Technology

Wind power potential assessment of 12 locations in western Himalayan region of India

S. S. Chandel et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2014)

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Review Green & Sustainable Science & Technology

Review on probabilistic forecasting of wind power generation

Yao Zhang et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2014)

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Article Green & Sustainable Science & Technology

An ARMAX model for forecasting the power output of a grid connected photovoltaic system

Yanting Li et al.

RENEWABLE ENERGY (2014)

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Article Computer Science, Artificial Intelligence

Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals

Hao Quan et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2014)

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Article Engineering, Electrical & Electronic

Hybrid Forecasting Model for Very-Short Term Wind Power Forecasting Based on Grey Relational Analysis and Wind Speed Distribution Features

Jie Shi et al.

IEEE TRANSACTIONS ON SMART GRID (2014)

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Article Engineering, Civil

Wind power prediction based on numerical and statistical models

Christos Stathopoulos et al.

JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS (2013)

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Review Green & Sustainable Science & Technology

On the management of wind power intermittency

Ehsan Rahimi et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2013)

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Article Green & Sustainable Science & Technology

Wind control centres: State of the art

Jose-Maria Gallardo-Calles et al.

RENEWABLE ENERGY (2013)

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Article Green & Sustainable Science & Technology

Back-to-back five-level converters for wind energy conversion system with DC-bus imbalance minimization

Farid Merahi et al.

RENEWABLE ENERGY (2013)

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Article Computer Science, Information Systems

Optimization of Wind Farm Turbine Layout Including Decision Making Under Risk

Javier Serrano Gonzalez et al.

IEEE SYSTEMS JOURNAL (2012)

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Article Engineering, Electrical & Electronic

Probabilistic Wind Power Forecasting Using Radial Basis Function Neural Networks

George Sideratos et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2012)

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Review Green & Sustainable Science & Technology

Evaluation of hybrid forecasting approaches for wind speed and power generation time series

Jing Shi et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2012)

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Article Green & Sustainable Science & Technology

Performance evaluation and accuracy enhancement of a day-ahead wind power forecasting system in China

Pan Zhao et al.

RENEWABLE ENERGY (2012)

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Article Green & Sustainable Science & Technology

Design of wind farm layout using ant colony algorithm

Yunus Eroglu et al.

RENEWABLE ENERGY (2012)

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Review Green & Sustainable Science & Technology

Current methods and advances in forecasting of wind power generation

Aoife M. Foley et al.

RENEWABLE ENERGY (2012)

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Article Energy & Fuels

Optimal turbine spacing in fully developed wind farm boundary layers

Johan Meyers et al.

WIND ENERGY (2012)

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Article Green & Sustainable Science & Technology

AWNN-Assisted Wind Power Forecasting Using Feed-Forward Neural Network

Kanna Bhaskar et al.

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2012)

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Article Energy & Fuels

Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

C. Gallego et al.

APPLIED ENERGY (2011)

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Article Energy & Fuels

ARMA based approaches for forecasting the tuple of wind speed and direction

Ergin Erdem et al.

APPLIED ENERGY (2011)

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Article Thermodynamics

Assessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods

Maria Grazia De Giorgi et al.

ENERGY (2011)

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Article Thermodynamics

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

H. M. I. Pousinho et al.

ENERGY CONVERSION AND MANAGEMENT (2011)

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Article Engineering, Civil

Simulating impacts of wind farms on local hydrometeorology

Somnath Baidya Roy

JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS (2011)

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Article Green & Sustainable Science & Technology

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

J. P. S. Catalao et al.

RENEWABLE ENERGY (2011)

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Article Green & Sustainable Science & Technology

Overall design optimization of wind farms

J. Serrano Gonzalez et al.

RENEWABLE ENERGY (2011)

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Article Green & Sustainable Science & Technology

Seeding evolutionary algorithms with heuristics for optimal wind turbines positioning in wind farms

B. Saavedra-Moreno et al.

RENEWABLE ENERGY (2011)

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Article Green & Sustainable Science & Technology

Wind Power Prediction by a New Forecast Engine Composed of Modified Hybrid Neural Network and Enhanced Particle Swarm Optimization

Nima Amjady et al.

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2011)

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Article Energy & Fuels

On comparing three artificial neural networks for wind speed forecasting

Gong Li et al.

APPLIED ENERGY (2010)

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Article Chemistry, Physical

Linear and non-linear control of wind farms. Contribution to the grid stability

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