Rethinking Renewable Energy Management Using Intelligent Decision Support Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".
Deadline for manuscript submissions: closed (1 January 2023) | Viewed by 3200
Special Issue Editors
Interests: intelligent healthcare systems; Internet of Things for Cardiovascular; patient monitoring; medical signal processing
Interests: optical telecommunications; wireless Communications; diffraction; fiber components; RFID; information processing; data protection; deep learning
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Special Issue Information
Dear Colleagues,
Over recent decades, renewable energy sources (RES) and energy production have increased. Consequently, renewable energy sources are seen to boost economic strength while also reducing fossil fuel consumption. However, it is evident to users that the ultimate decision-making system in selecting a REMS project facility is complex, encompassing a variety of factors at many levels such as commercial, technological, and environment. Various strategies aimed at increasing the usage of renewable energy management systems (REMS) to use all these RES effectively have received much attention. Artificial intelligence (AI) approaches are critical in today's energy systems. In specific energy systems, an intelligent method is a unique approach. Because of the development's multiple non-homogeneous forms of energy, it promotes the widespread usage of RES. Decision support systems (DSS) are now a well-established part of regular knowledge management. Computer system enhanced complexity and Intelligent ability creates many to an excellent platform for such complicated organizational necessities that appear to be suitable for tackling today's decision-making problem. The most common issues addressed by DSS in the REMS are energy transportation, power generation, energy consumption, energy demand, developing energy systems, the effect of pollution, and others. Researchers can see that more advanced DSS, particularly in the sector of REMS, use multi-criteria decision-making (MCDM) methodologies to gather and evaluate input information and generate outcomes, so DSS involves extra intelligent techniques and methods that could include a group of decision-makers in arbitrary, active, and dispersed surroundings. The RES sector presents major new issues for data analysis in the intelligent decisions support system (IDSS). Researchers provide an intelligent RE-DSS structure within that research to assist DSS in developing intelligent REMS. Future progress in RE-DSS includes the participation of an entire RES Information System that must protect most RES field incidents such as Fuel Efficiency, Performance Improvement, and semantic and syntactic, an effort to help decision-makers conscious of parts of the DSS that they would not have used before, as well as operated reliability analysis. The domain of multiple REMS objectives and strategies to promote would be represented using ontologies, a method for semantics. When implementing new energy sources or scaling the energy system, AI provides the process with more dependability and versatility. Energy management can be regarded as a promise to use energy effectively and sustainably in an intelligent environment. From a range of disciplinary perspectives, we invite papers that rethinking renewable energy management using intelligent decision support systems overarching.
Dr. Muhammad Ibrahim
Prof. Dr. Habib Hamam
Guest Editors
Manuscript Submission Information
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Keywords
- energy management
- AI
- intelligent decision support systems
