Together with his students from the National University of Singapore, a series of visualizations were developed and consolidated, from simple sorting algorithms to complex graph data structures.
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This paper presents a model and simulation of the primary wiring component of a microgrid, based on the electromagnetic simulation platform of the power system, PSCAD/EMTDC.
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This white paper focuses on tools that support design, planning and operation of microgrids (or aggregations of microgrids) for multiple needs and stakeholders (e.g., utilities, developers,
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These AI models maximize the use of renewable energy, reduce wastage, and improve microgrid resilience and responsiveness to supply and demand fluctuations. Experiments
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The integration of AI-driven models and algorithms into microgrid systems necessitates rigorous evaluation to ensure transparency, reliability, and interpretability.
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This review systematically examines the intersection of microgrid optimization and metaheuristic algorithms, focusing on the period from 2015 to 2025. We first trace the technological
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Microgrids (MGs) provide a promising solution by enabling localized control over energy generation, storage, and distribution. This paper presents a novel reinforcement learning (RL)-based
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In contrast to previous studies focusing solely on conventional optimization methods, this research explores the innovative application of AI techniques—Genetic Algorithm (GA), Ant Colony
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ABSTRACT The concept of microgrids (MGs) as compact power systems, incorporating distributed energy resources, generating units, storage systems, and loads, is widely acknowledged
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Deep Reinforcement Learning (DRL), a subset of artificial intelligence, holds the potential to revolutionize the control and management of microgrids. This systematic review aims to provide a
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