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[HTML][HTML] Smart cities: Fusion-based intelligent traffic congestion control system for vehicular networks using machine learning techniques
Smart cities have been developed over the past decade, and reducing traffic congestion has
been the top concern in smart city development. Short delays in communication between …
been the top concern in smart city development. Short delays in communication between …
Fusion-based supply chain collaboration using machine learning techniques
Supply Chain Collaboration is the network of various entities that work cohesively to make
up the entire process. The supply chain organizations' success is dependent on integration …
up the entire process. The supply chain organizations' success is dependent on integration …
[HTML][HTML] Power distribution system planning framework (A comprehensive review)
R Dashti, M Rouhandeh - Energy strategy reviews, 2023 - Elsevier
In this paper, we present a comprehensive and innovative framework for optimizing planning
in power distribution systems. Firstly, we introduce various types of planning involved in …
in power distribution systems. Firstly, we introduce various types of planning involved in …
Profit maximization of retailers with intermittent renewable sources and energy storage systems in deregulated electricity market with modern optimization techniques …
The impact of integrating hybrid (wind and solar) renewable energy sources with energy
storage devices in Micro-grid (MG) operations under the deregulated electricity market is …
storage devices in Micro-grid (MG) operations under the deregulated electricity market is …
Optimal allocation of renewable distributed generations using heuristic methods to minimize annual energy losses and voltage deviation index
In this paper, two metaheuristic methods, genetic algorithm and particle swarm optimization,
are proposed to determine the optimal locations, sizes, and power factors of single and …
are proposed to determine the optimal locations, sizes, and power factors of single and …
[PDF][PDF] Smart energy management system using machine learning
Energy management is an inspiring domain in develo** of renewable energy sources.
However, the growth of decentralized energy production is revealing an increased …
However, the growth of decentralized energy production is revealing an increased …
Multi-objective optimal siting and sizing of distributed generators and shunt capacitors considering the effect of voltage-dependent nonlinear load models
Load modeling is essential to distribution system analysis, planning, and control. Therefore,
in this work, effect of non-linear load models has been considered for the optimal site and …
in this work, effect of non-linear load models has been considered for the optimal site and …
Boosting prairie dog optimizer for optimal planning of multiple wind turbine and photovoltaic distributed generators in distribution networks considering different …
Deploying distributed generators (DGs) supplied by renewable energy resources poses a
significant challenge for efficient power grid operation. The proper sizing and placement of …
significant challenge for efficient power grid operation. The proper sizing and placement of …
[HTML][HTML] An improved hybrid approach for the simultaneous allocation of distributed generators and time varying loads in distribution systems
Distributed Generation (DG) studies are generally conducted considering a single type of
DG units integrated with the Distribution System (DS). However, these studies may not …
DG units integrated with the Distribution System (DS). However, these studies may not …
Techno-economic and environmental assessments of optimal planning of waste-to-energy based CHP-DG considering load growth on a power distribution network
Load growth puts pressure on existing electric infrastructure and impacts on the system's
performance parameters which may necessitate network expansion. Conventionally, electric …
performance parameters which may necessitate network expansion. Conventionally, electric …