Artificial Intelligence for Sustainable Energy Systems: Smart Grids, Homeostatic Control, and Distributed Resource Optimization

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 30 January 2026 | Viewed by 2167

Special Issue Editors


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Guest Editor
Faculty of Engineering, Universidad Finis Terrae, Santiago, Chile
Interests: sustainable energy systems; energy homeostasis; smart grid; electricity distribution service quality; distributed energy resources; energy management; power control systems

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Guest Editor
Department of Electrical Engineering, Parala Maharaja Engineering College, Odisha 761003, India
Interests: renewable energy automation; distribution systems; energy forecasting; machine learning; control and optimization; real-time monitoring

Special Issue Information

Dear Colleagues,

We are navigating very challenging times, where new and radical changes in technology are arising on all fronts. In a world of hyperconnectivity, ultra-fast sensing networks equipped with IoT, ubiquitous cloud computing integrated with various AI technologies, and enormous loads of data processing which increase every year, the need for ever greater amounts of electricity is growing and becoming a pressing constraint on industries in general. As a result, we require more reliable, resilient, and sustainable high-power transmission and distribution networks. To help advance this fast-paced, ambitious agenda and contribute to the modernization of electric power networks, researchers, like ourselves, and industry pundits, in general, are called to support key areas of the development of the Smart Grid and Sustainable Energy Systems (SES) agenda, such as Energy Homeostasis Management and Distributed Resources Optimization based on AI deployment. This agenda calls for new applications of technologies with an ever-present system engineering approach, where AI and energy management take the center stage. However, along with the Smart Grid and SES agenda, service quality issues are arising as a consequence of small- and medium-sized means of distributed generation connecting to the grid, as permitted by law. Hence, in addition to leveraging rapidly configurable, scalable, and deployable distributed energy resources (DERs) such as the microgrid and employing renewables, flexible loads, AI, IOT, and smart energy management systems for electric distribution companies, the issue of how to intervene in the grid and resolve service quality issues swiftly before the problem escalates remains. DG systems such as the Virtual Power Plant (VPP) play an important role in the integration of DER into electric power distribution networks so as to provide critical assistance to the grid in a particular location whenever necessary. Thus, this Special Issue is dedicated to these pressing issues, as we face an ever-growing demand for electric power, and aims to address potential regulatory changes and new, more advanced engineering solutions to negative impacts on the grid's service quality standards and worse yet—blackouts. This Special Issue is therefore dedicated to this important area of research, not only due to its direct link to the advancement of the Smart Grid and Sustainable Energy Systems, but also because of its economic and regulatory ramifications, which undoubtedly affect every sector of countries’ economies, in particular, the energy supply and the electric power distribution sector.

Dr. Fernando Yanine
Prof. Dr. Sarat Kumar Sahoo
Guest Editors

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Keywords

  • smart grid
  • microgrid on-grid
  • small means of distributed generation (PMGD)
  • electrical energy distribution
  • distributed energy resources (DER)
  • service quality standards
  • energy homeostasis
  • sustainable energy systems (SES)

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Published Papers (1 paper)

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Research

23 pages, 2365 KiB  
Article
What Is the Process? A Metamodel of the Requirements Elicitation Process Derived from a Systematic Literature Review
by Mauricio Hidalgo, Fernando Yanine, Rodrigo Paredes, Jonathan Frez and Mauricio Solar
Processes 2025, 13(1), 20; https://doi.org/10.3390/pr13010020 - 25 Dec 2024
Cited by 1 | Viewed by 1674
Abstract
Requirements elicitation is a fundamental process in software engineering, essential for aligning software products with user needs and project objectives. As software projects become more complex, effective elicitation methods are vital for capturing accurate and comprehensive requirements. Despite the variety of available elicitation [...] Read more.
Requirements elicitation is a fundamental process in software engineering, essential for aligning software products with user needs and project objectives. As software projects become more complex, effective elicitation methods are vital for capturing accurate and comprehensive requirements. Despite the variety of available elicitation methods, practitioners face persistent challenges such as capturing tacit knowledge, managing diverse stakeholder needs, and addressing ambiguities in requirements. Moreover, although elicitation is recognized as a core process for gathering and analyzing system objectives, there is a lack of a unified and systematic framework to guide practitioners—especially newcomers—through the activity. To address these challenges, we provide a comprehensive analysis of existing elicitation methods, aiming to contribute to better alignment between software products and project objectives, ultimately improving software engineering practices. We do so by performing a systematic literature review identifying crosscutting steps, common techniques, tools, and approaches that define the core activities of the elicitation process. We synthesize our findings into a metamodel that structures software elicitation processes. This review uncovers various elicitation methods—such as collaborative workshops, interviews, and prototyping—each demonstrating unique strengths in different project contexts. It also highlights significant limitations, including stakeholder misalignment and incomplete requirements capture, which continue to reduce the effectiveness of elicitation processes. Finally, our study seeks to contribute to understanding requirements elicitation methods by providing a comprehensive view of their current strengths and limitations through a metamodel enabling the structuring and optimization of elicitation processes. Full article
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