Rüzgâr Gücü Tahminlerinin Önemi: Türkiye Elektrik Piyasasında Bir Uygulama

Karık, Fatih; Sözen, Adnan; Izgeç, Muhammed Mustafa

doi:10.2339/politeknik.369038

Cited by 6 publications

(3 citation statements)

References 2 publications

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“…Wind energy prediction models are used in power systems planning, reserve planning, maintenance and repair planning, and bidding in the electricity market. Thanks to prediction models, power plants can increase their revenues by reducing prediction errors in the day-ahead market, thus reducing energy imbalances in the electricity market and consequently, costs (Karık et al, 2017). Especially, short-term wind prediction play an important role in day-ahead electricity trade, planning the day-ahead electricity system, determining the required reserve amount, and making unit commitment decisions (Kerem, 2018).…”

Section: Figure 1 Installed Wind Power Plants By Yearsmentioning

confidence: 99%

Short-Term Wind Power Prediction Approach Based On Bayesian Optimization and Ensemble Learning

Yazici¹,

Boran²

2021

Journal of Intelligent Systems: Theory and Applications

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In wind energy studies, predicting the short-term energy generation amount for wind power plants and determining the production offer to be placed on the market play an important role. In this study an hourly short-term wind power estimation of a wind turbine located in Turkey with an installed power of 3600 kW has been made. Estimation results were evaluated on a seasonal and annual basis. New hybrid models have been developed for short-term wind power prediction, consisting of Bayesian Optimization (BO), Support Vector Regression (SVR), Gaussian Process Regression (GPR), Decision Tree (DT), stacking, and bagging algorithms. In the proposed prediction approach, it is aimed to reduce prediction errors by combining different regression algorithms with the BO method and ensemble algorithms. Unlike other wind prediction studies, BO was used for the first time in the hyperparameter selection of the regression algorithms selected as the basic learner in the study. Bayesian optimized decision tree (BO-DT) with the lowest error values among the base learners, and Bayesian optimized gaussian process regression (BO-GPR) combined with bagging and stacking. The efficiency of ensemble learning algorithms was measured by the statistical measurement methods Normalized Absolute Mean Error (NMAE), Normalized Root of Mean Squares Error (NRMSE), and determination coefficient (R 2 ). According to the results, the bagging method created with the BO-DT took the annual average NRMSE, NMAE, R 2 criteria of 11.045%, 4.880%, 0.899, respectively, and the model with the best performance was selected in terms of both annual and seasonal results.

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Section: Figure 1 Installed Wind Power Plants By Yearsmentioning

confidence: 99%

Short-Term Wind Power Prediction Approach Based On Bayesian Optimization and Ensemble Learning

Yazici¹,

Boran²

2021

Journal of Intelligent Systems: Theory and Applications

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“…birçok nedeni olabilir. Kaynak nedenler araştırılmalı ve iyileştirme yöntemleri geliştirilerek otoriteye sunulmalıdır [5].…”

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“…Görüldüğü üzere toplam kapasitenin gelişime paralel olarak, rüzgar santralleri başta olmak üzere, yenilenebilir kaynaklı üretimde büyük bir kapasite artışı söz konusudur (Şekil 3) [4]. Bu da kapasitenin artışında, küresel fosil yakıt rezervlerin azalması ve çevresel kaygılar bu konuda ön plana çıkmaktadır [5]. Yenilenebilir kaynaklı üretimin sisteme dâhil olması süreci, 5346 sayılı Yenilenebilir Enerji Kaynaklarının Elektrik Enerjisi Üretimi Amaçlı Kullanımına İlişkin Kanun ile hız kazanmıştır.…”

Section: Introductionunclassified

Türkiye Yenilenebilir Enerji Kapasitesi Devreye Alma İşleminin Darboğaz Analizi

Izgeç¹

2020

Fırat Üniversitesi Mühendislik Bilimleri Dergisi

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Son yıllarda Dünyada olduğu gibi Türkiye'de de yenilenebilir enerji kaynaklarının kullanımına yönelim ivme kazanmıştır. Bu kaynakların üretime geçme sürelerinin uzun olduğu bilinmektedir. Çalışmanın amacı, santrallerin devreye alma süresi verilerini kullanarak detaylı bir analiz yapmak ve süreçlerde gerçekten sorun olup olmadığını tespit etmektir. Sorunların neler olduğu, başka bir çalışma konusu olarak önerilmektedir. Devreye alma sürelerinin hızlanması konusunda ise saha tecrübeleri göz önünde bulundurularak genel çözüm önerileri yapılmıştır. İrdelenen süreçler, tesisin devreye alınmasına kadar olan süreçlerdir ve işletme koşulları ile ilgili bilgi içermemektedir. Ayrıca; çalışmada ticari bilgi kabul edilecek veriler gölgelenmiş ve yorumdan kaçınılmıştır.

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Wind turbine inspection with drone: Advantages and disadvantages

TANRIVERDİ¹,

Karakuş

ULUKAN³

2023

Journal of Energy Systems

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The facilities on wind energy generation are increasingly finding usage areas in line with the ecologically friendly energy generation approach. One of the important activities of wind power generation facilities, which have high investment cost, low operating cost and low environmental impact is the maintenance and repair of wind turbines. A preventive maintenance approach is dominant to reduce maintenance times and eliminate lost time in wind turbines. Damage inspection of turbines has been evolved from tower crane access, rope access, camera viewing, and other applications to image with manual drones over the years. However, when these methods are evaluated within the framework of criteria such as cost, performance, occupational safety and data reliability, they are still insufficient and the need for inspection with autonomous drones arises. The advantages and disadvantages of autonomous drones used in the determination of damage in wind turbines are analyzed and the results are considered to contribute to the practitioners operating in the sector and academicians working in the field.

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Rüzgâr Gücü Tahminlerinin Önemi: Türkiye Elektrik Piyasasında Bir Uygulama

Cited by 6 publications

References 2 publications

Short-Term Wind Power Prediction Approach Based On Bayesian Optimization and Ensemble Learning

Short-Term Wind Power Prediction Approach Based On Bayesian Optimization and Ensemble Learning

Türkiye Yenilenebilir Enerji Kapasitesi Devreye Alma İşleminin Darboğaz Analizi

Wind turbine inspection with drone: Advantages and disadvantages

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