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Dergiler / International Advanced Researches and Engineering Journal / 2021 / Cilt: 5 - Sayı: 2

Prediction of market-clearing price using neural networks based methods and boosting algorithms

Aslı Boru İPEK
Sayfa
240–246
Yayın Tarihi
2022-10-19
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Hence, producers and consumers can use these methods to determine the bidding strategies and to maximize their profits.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:The development of Turkey's industry is contributing to a significant rise in electrical energy demand.
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Temel Bulgular & Veri:Various performance metrics are employed to evaluate the prediction performance of proposed methods.
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Sonuç & Katkı:Hence, producers and consumers can use these methods to determine the bidding strategies and to maximize their profits.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:ANN · Boosting algorithms · Market-clearing price

Abstract

The development of Turkey's industry is contributing to a significant rise in electrical energy demand. Also, electricity is one of the critical elements in the household sectors. Therefore, the planning and managing of electrical energy is of great importance to support economic growth. In addition, effective prediction of market-clearing prices (MCP) is critical topic to meet the increasing energy demand and provide basis for decision making process. In this paper, MCP is predicted using artificial neural network (ANN), convolutional neural network (CNN), and also three boosting algorithms including extreme gradient boosting (XGBoost), categorical boosting (CatBoost), and adaptive boosting (AdaBoost). Various performance metrics are employed to evaluate the prediction performance of proposed methods. The results showed that proposed methods provide reasonable prediction results for energy sector. Hence, producers and consumers can use these methods to determine the bidding strategies and to maximize their profits.

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Bu Makaleye Atıf Yap

İPEK, A. B. (2022). Prediction of market-clearing price using neural networks based methods and boosting algorithms. International Advanced Researches and Engineering Journal, Cilt: 5 - Sayı: 2, 240–246. https://ajindex.com/articles/539275

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