Crucially, a hardware prototype validates these strategies under real-world uncertainties, such as varying wind speed and solar insolation, demonstrating their effectiveness and feasibility for
Grid-connected microgrids are actors within the electricity grid that can contain local power sources and consumers. Reducing the mismatch between local power demand and supply in
In this work, we developed an optimized deep learning framework using the combined structure of Whale-Optimized Neuro-Fuzzy Classification for controlling electric vehicle charging
Abstract—This research introduces a holistic optimization framework designed to optimize the placement and energy management of electric vehicle (EV) charging stations within microgrids. The
Develop the next generation microgrids, smart grids, and electric vehicle charging infrastructure by modeling and simulating network architecture, performing system-level analysis, and developing
Electric vehicles (EVs) are rapidly emerging as a cornerstone of sustainable mobility, yet their integration into modern power systems demands intelligent charging solutions. This chapter
This study presented and simulated a proposed design for an intelligent control method for electric vehicle charging in microgrids (MGs). The proposed plan was studied and reviewed in
This paper proposes a novel Scalable Cloud-Based Continuous Monitoring Platform (SC-CMP) designed to support real-time optimization of microgrid operations, particularly in EV-dense
Abstract: Rapid growth in the deployment of electric vehicles (EVs) has fuelled the demand for sustainable, efficient, and intelligent charging infrastructures.
In order to improve the efficiency and stability of renewable energy sources and energy security in microgrids, this paper proposes an optimal campus microgrid design that includes EV
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