The State of the Art Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market

Vasileios Laitsos (), Georgios Vontzos, Paschalis Paraschoudis, Eleftherios Tsampasis, Dimitrios Bargiotas () and Lefteri H. Tsoukalas
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Vasileios Laitsos: Department of Electrical and Computer Engineering, University of Thessaly, 383 34 Volos, Greece
Georgios Vontzos: Department of Electrical and Computer Engineering, University of Thessaly, 383 34 Volos, Greece
Paschalis Paraschoudis: Department of of Energy Systems, University of Thessaly, 415 00 Larisa, Greece
Eleftherios Tsampasis: Department of Digital Arts and Cinema, National and Kapodestrian University of Athens, 344 00 Psahna, Greece
Dimitrios Bargiotas: Department of Electrical and Computer Engineering, University of Thessaly, 383 34 Volos, Greece
Lefteri H. Tsoukalas: Center for Intelligent Energy Systems (CiENS), School of Nuclear Engineering, Purdue University, West Lafayette, IN 47906, USA

Energies, 2024, vol. 17, issue 22, 1-37

Abstract: In a modern and dynamic electricity market, ensuring reliable, sustainable and efficient electricity distribution is a pillar of primary importance for grid operation. The high penetration of renewable energy sources and the formation of competitive prices for utilities play a critical role in the wider economic development. Electricity load and price forecasting have been a key focus of researchers in the last decade due to the substantial economic implications for both producers, aggregators and end consumers. Many forecasting techniques and methods have emerged during this period. This paper conducts a extensive and analytical review of the prevailing load and electricity price forecasting methods in the context of the modern wholesale electricity market. The study is separated into seven main sections. The first section provides the key challenges and the main contributions of this study. The second section delves into the workings of the electricity market, providing a detailed analysis of the three markets that have evolved, their functions and the key factors influencing overall market dynamics. In the third section, the main methodologies of electricity load and price forecasting approaches are analyzed in detail. The fourth section offers a comprehensive review of the existing literature focusing on load forecasting, highlighting various methodologies, models and their applications in this field. This section emphasizes the advances that have been made in all categories of forecasting models and their practical application in different market scenarios. The fifth section focuses on electricity price forecasting studies, summarizing important research papers investigating various modeling approaches. The sixth section constitutes a fundamental discussion and comparison between the load- and price-focused studies that are analyzed. Finally, by examining both traditional and cutting-edge forecasting methods, this review identifies key trends, challenges and future directions in the field. Overall, this paper aims to provide an in-depth analysis leading to the understanding of the state-of-the-art models in load and price forecasting and to be an important resource for researchers and professionals in the energy industry. Based on the research conducted, there is an increasing trend in the use of artificial intelligence models in recent years, due to the flexibility and adaptability they offer for big datasets, compared to traditional models. The combination of models, such as ensemble methods, gives us very promising results.

Keywords: electricity load forecasting; electricity price forecasting; wholesale energy market; deep learning; machine learning; statistical models (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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