Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison

Zuluaga, Carlos D.; López, Mariano Jiménez; Giraldo, Eduardo

doi:10.1016/j.apenergy.2015.07.043

Cited by 154 publications

(59 citation statements)

References 40 publications

(50 reference statements)

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“…It is due to their endlessness and cleanness. In WECSs, wind speed is key information to be known in real time . Unfortunately, it is not easy to measure it with enough precision for control systems.…”

Section: Introductionmentioning

confidence: 99%

A novel nonlinear observer‐based LQ control system design for wind energy conversion systems with single measurement

Duc

2019

Wind Energy

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The issue of tracking the optimal power for wind energy conversion systems (WECSs) via regulating the rotor speed of the generator is taken into account in this study. Additionally, a novel polynomial observer is proposed for estimating not only aerodynamic torque in WECSs but also d‐axis and electromagnetic torque. Therefore, in this new approach, only the rotor speed of the generator is required to be measured instead of measuring all state variables. With the new observer form, the aerodynamic torque does not need to satisfy any constraints, which are mandatory in the previous methods. It should be noted that this methodology has not been investigated for the WECSs in any previous papers. To design a complete control system, a linear optimal control method cooperated with the polynomial observer is employed to track the optimal trajectory of a generator. Moreover, in this paper, the permanent magnet synchronous generator is used. In addition, on the basis of the Lyapunov theory and sum‐of‐square (SOS) technique, the conditions for observer synthesis are derived in the main theorems. Finally, the simulation results are provided to prove the effectiveness and merit of the proposed method.

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Section: Introductionmentioning

confidence: 99%

A novel nonlinear observer‐based LQ control system design for wind energy conversion systems with single measurement

Duc

2019

Wind Energy

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“…The utilization of wind energy for electric power systems offers an alternative to decrease the dependence on fuel-based energy, effectively alleviating the environmental pressure [1]. However, the exponential development of wind power creates a number of challenges for wind industry dramatically [2].…”

Section: Introductionmentioning

confidence: 99%

A Least Squares Support Vector Machine Optimized by Cloud-Based Evolutionary Algorithm for Wind Power Generation Prediction

Peng

2016

Energies

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Accurate wind power generation prediction, which has positive implications for making full use of wind energy, seems still a critical issue and a huge challenge. In this paper, a novel hybrid approach has been proposed for wind power generation forecasting in the light of Cloud-Based Evolutionary Algorithm (CBEA) and Least Squares Support Vector Machine (LSSVM). In order to improve the forecasting precision, a two-way comparison approach is conducted to preprocess the original wind power generation data. The pertinent parameters of LSSVM are optimized by using CBEA to verify the learning and generalization abilities of the LSSVM model. The experimental results indicate that the forecasting performance of the proposed model is better than the single LSSVM model and all of the other models for comparison. Moreover, the paired-sample t-test is employed to cast light on the applicability of the developed model.

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“…Saberivahidaval and Hajjam [9] studied a comparison between performances of different neural networks for wind speed forecasting. Zuluaga et al [10] presented short-term wind speed prediction based on robust Kalman filtering. Based on support vector regression, a hybrid methodology for wind speed forecasting was presented by Santamaria-Bonfil et al [11].…”

Section: Introductionmentioning

confidence: 99%

Zaman Serisi Analiz Metotları Kullanılarak Rüzgâr Hızının Tahmin Edilmesi

Akcan

2017

Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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As a natural, non-consumable, clean and sustainable energy resource, wind energy is becoming crucial throughout the world. Forecasting wind speed is noteworthy to design and install wind power stations. In this study, several time series analysis methods for wind energy were compared considering long-termmonthly-average wind speed data between the years of 1960 and 2014 at nine meteorological stations throughout five geographical areas in Turkey. The low performance measure values seen in results indicate that the methods used in this study can be forecast for wind speed. Keywords

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Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison

Cited by 154 publications

References 40 publications

A novel nonlinear observer‐based LQ control system design for wind energy conversion systems with single measurement

A novel nonlinear observer‐based LQ control system design for wind energy conversion systems with single measurement

A Least Squares Support Vector Machine Optimized by Cloud-Based Evolutionary Algorithm for Wind Power Generation Prediction

Zaman Serisi Analiz Metotları Kullanılarak Rüzgâr Hızının Tahmin Edilmesi

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