In addition, the proposed approach provides the optimization of supply and demand sides.
📌 3 Key Takeaways
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Objective & Hypothesis:An electric power network can be evolved into smart grids, which are measured by providing energy efficiency and improving the available resources.
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Key Findings & Data:With the development of software and hardware elements, the decision-making mechanism of existing smart grids is transformed into more robust uninterrupted and economical energy management systems.
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Conclusion & Impact:In addition, the proposed approach provides the optimization of supply and demand sides.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Cognitive Management · Electric Power Price Management System · Cognitive Network System
Abstract
An electric power network can be evolved into smart grids, which are measured by providing energy efficiency and improving the available resources. With the development of software and hardware elements, the decision-making mechanism of existing smart grids is transformed into more robust uninterrupted and economical energy management systems. In this study, a cognitive-based algorithm using dynamic energy management flexibility, storage and energy management algorithm and cloud computing architecture is proposed. Using this approach, an uninterrupted and economical energy management system can be planned. In addition, the proposed approach provides the optimization of supply and demand sides.
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