Can machine learning reduce volatility in electricity markets? Lessons from the economic calculation debate

Economic Affairs, Год журнала: 2025, Номер 45(1), С. 62 - 77

Опубликована: Фев. 1, 2025

Abstract The knowledge problem and volatility in electricity markets have long been central to policy debates energy markets. This study examines the successes limitations of machine learning addressing these issues, contributing existing literature. Machine has shown promise tackling specific technical aspects power markets, but its shortcomings forecasting customer behaviour managing decentralised, renewable‐driven systems highlight need for further refinement. While offers potential reducing certain market volatility, it is not a comprehensive solution broader challenges faced by market.

Язык: Английский

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Comprehensive Analysis of Energy Demand Prediction Using Advanced Machine Learning Techniques

E3S Web of Conferences, Год журнала: 2025, Номер 616, С. 02027 - 02027

Опубликована: Янв. 1, 2025

Energy prediction plays a critical role in maximizing energy usage, reducing costs, and improving the effectiveness of power systems. Machine learning (ML) techniques are increasingly potent for analyzing intricate patterns consumption providing precise forecasts—both crucial effective management. This study examines application ML forecasting focusing on two techniques: Long Short-Term Memory (LSTM) Support Vector Machines (SVM). LSTM models, known their ability to capture complex patterns, evaluated time-series data prediction. SVM, supervised algorithm, is analyzed its performance under varying conditions. The compares predictive accuracy, computational efficiency, generalization capabilities these models using metrics like R 2 , RMSE, MAE. Results indicate that excels with large datasets non-linear while SVM smaller sensitivity outliers. analysis provides insights into selecting appropriate specific characteristics requirements.

Язык: Английский

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AI, Ethics, and Hate Speech

Advances in social networking and online communities book series, Год журнала: 2025, Номер unknown, С. 409 - 432

Опубликована: Фев. 7, 2025

Hate speech is a serious social problem, disrupts order, impairs individual well-being, and threatens democracy, emonize individuals or groups based on attributes like race, religion,caste ethnicity, gender sexual orientation, appears in many forms: spoken language, written materials, symbols online posts. With the advent of media, reach impact hate has increased exponentially, making it an ever-pressing issue digital age included legislative measures, education awareness campaigns, increasing prevalence harmful content led to exploration artificial intelligence (AI) as tool be used detect mitigate online. The paper conclude that preserves ethical concepts design implementation AI-driven systems. It points policies empower responsible innovation without undermining fundamental democratic values. Through creating inclusive spaces advocating for rights freedoms developing socially responsible, inclusivity respect liberties

Язык: Английский

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Application of Artificial Intelligence and Machine Learning in Assessing Solar Energy Potential

Опубликована: Март 21, 2025

Язык: Английский

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AI and ML for Energy Management

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 109 - 134

Опубликована: Апрель 11, 2025

The rising international energy consumption and the necessity of looking for environment-friendly solutions have necessitated use technology such as AI ML management. This paper provides a state-of-art review in efficiency microgrid systems, smart grid, renewable industries, buildings. enable predictive modeling, realtime optimization, advanced control methodologies that enhance efficiency, operation cost facilitate integration systems. outlines some important like reinforcement learning, deep learning optimization algorithms systems their limitations data quality, model interpretability scalability. results imply is crucial determining direction future management ensuring sustainability process.

Язык: Английский

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Analyzing Energy Consumption in IoT, Fog, and Blockchain Ecosystems

Advances in environmental engineering and green technologies book series, Год журнала: 2025, Номер unknown, С. 127 - 166

Опубликована: Апрель 4, 2025

The rise of Internet Things (IoT) devices, fog computing, and blockchain technologies has reshaped modern distributed systems, but energy consumption poses a critical challenge. This chapter explores patterns in IoT, fog, ecosystems, emphasizing the importance efficiency. It discusses interplay between these usage IoT network protocols, cloud edge computing impacts, needs challenges nodes. also examines implications consensus mechanisms like proof-of-work proof-of-stake, sustainable energy-efficient strategies such as machine learning. Real-world examples highlight successful deployments smart cities green systems. concludes by stressing need for practices designing implementing digital future.

Язык: Английский

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An Overview of the Implications of Artificial Intelligence (AI) in Sixth Generation (6G) Communication Network

Research Briefs on Information and Communication Technology Evolution, Год журнала: 2023, Номер 9, С. 120 - 146

Опубликована: Ноя. 2, 2023

The 6G communication network is anticipated to be a cutting-edge next-generation that will enhance the value of intelligent Internet Things (IoT). emergence many domains within artificial intelligence (AI) has paved way for significant opportunities in development technology. These include enhancement human intelligence, integration various devices and systems through Everything (IoE), improvements quality experiences, enhancements overall life. AI networking technology bring about transformative shift, transitioning from focus on interconnected paradigm centered around systems. This article provides an overview extent which poised revolutionize technologies. study primarily concerned with implementation appropriate applications address needs challenges. Furthermore, this research highlights significance potential provide emerging

Язык: Английский

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A Comprehensive Review on Deep Learning Applications in Advancing Biodiesel Feedstock Selection and Production Processes

SSRN Electronic Journal, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Язык: Английский

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A review of agroforestry as a sustainable and resilient agriculture

Journal of Agriculture Sustainability and Environment, Год журнала: 2023, Номер 2(1), С. 49 - 72

Опубликована: Май 26, 2023

The agricultural sector is confronted with the formidable challenge of providing sustenance for a global population 9 billion individuals by year 2050, all while mitigating adverse ecological and societal impacts. An attempt to address this difficulty has been made through implementation organic farming practices, which have yielded predominantly favorable results. Nevertheless, there are still certain obstacles that need be addressed. Organic practices exhibit lower yields compared conventional methods, concerns persist regarding greenhouse gas emissions fertilizer leaching. This paper provides an overview existing agriculture systems proposes agroforestry, deliberate integration trees shrubs crops or livestock, may represent promising avenue advancing sustainable agriculture. Agroforestry possesses capacity sustain productivity concurrently provide many ecosystem services use nature-inspired methods. study presents prevalent methods products associated also highlighting positive environmental social impacts it brings about. present aims examine encountered in agroforestry suggest potential strategies policy modification could enhance uptake such among farmers. findings review indicate emerges as very effective land strategy addressing both food security degradation concerns.

Язык: Английский

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Wissensmanagement für Wartung und Instandhaltung im Verteilnetz – Konzeption eines Assistenzsystems basierend auf einem Large Language Model

HMD Praxis der Wirtschaftsinformatik, Год журнала: 2024, Номер 61(4), С. 911 - 926

Опубликована: Май 14, 2024

Zusammenfassung Verteilnetzbetreiber in Deutschland stehen vor großen Herausforderungen bei dem Management ihres unternehmensspezifischen Wissens: Mitarbeiterengpässe durch den demographischen Wandel, Wissen ist nur implizit vorhanden und nicht Wissensmanagementsystemen digitalisiert, teilweise gibt es gar keine Wissensmanagementsysteme oder Konzepte das Verteilnetz wird immer komplexer. Verbunden mit zunehmender Belastung von zentralen Komponenten im die Energiewende bedarf neuer Lösungen, besonders für wissensintensiven Wartungs- Instandhaltungsprozesse. Generative Artificial Intelligence als aufstrebende Technologie, insb. Large Language Models, zeigt hier erste Erfolge Anleitung, Entscheidungsunterstützung Wissenstransfer. Aufbauend auf Design Science Research Forschungsparadigma diesem Beitrag ein ganzheitlicher Ansatz des Wissensmanagements konzipiert, welcher zentrale Komponente einem Assistenzsystem basiert. Ein Model generiert Hilfestellungen Netzmonteure während der Wartung Instandhaltung Basis Anleitungen. Neben Konzeption dieser auch erarbeitete Strategie zur Demonstration zukünftigen Evaluation Ergebnisse. Der liefert neuartiges Konzept basierter Assistenzsysteme zum Wissensmanagement zudem nachgelagerte Schritte auf, einer Markteinführung notwendig sind.

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