Search Results - (( storage optimization method algorithm ) OR ( using optimization based algorithm ))*
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Optimization algorithms for energy storage integrated microgrid performance enhancement
Published 2023“…Controllers; Electric power transmission; Electric power utilization; Energy management systems; Energy resources; Energy storage; Iterative methods; Learning algorithms; Microgrids; Operating costs; Particle swarm optimization (PSO); Scheduling; Scheduling algorithms; Stochastic systems; Storage management; Two term control systems; Charge-discharge; Day-ahead; Distributed Energy Resources; Microgrid; Optimization algorithms; Optimized controllers; Optimized scheduling; Performance enhancements; Scheduling controllers; Storage systems; Energy management…”
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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications
Published 2023“…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
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Grey Wolf Optimizer Based Battery Energy Storage System Sizing for Economic Operation of Microgrid
Published 2023Conference Paper -
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin
Published 2023“…The aim of study is to determine the maximum and minimum of functions, which are often used in decision making. The nonlinear conjugate gradient (CG) method recently is the most used iterative methods for solving optimizing problems because it requires less storage and easy for implementation. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm
Published 2023Article -
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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Optimizing lossless compression by normalized data length in Huffman Algorithm
Published 2022“…The proposed new algorithm has more optimal CR than the various variants of the Huffman-based lossless application. …”
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Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty
Published 2024“…The RUL prediction uncertainty with a 95% confidence interval (CI) is also analyzed. The GSA algorithm optimizes the hyperparameters of the LSTM network to construct an optimal model. …”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…However, their performances are not well optimized. This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. …”
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Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty
Published 2025“…Moreover, the LSTM model hyperparameters are optimized using the GSA optimization technique. To evaluate the robustness of the proposed method, 15 prediction samples are generated to calculate the uncertainty levels (95% CI) of the predicted RUL. …”
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Quasi-Newton methods based on ordinary differential equation approach for unconstrained nonlinear optimization
Published 2014“…Fundamentally this is a gradient system based on the first order optimality conditions of the optimization problem. …”
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Long-term optimal planning of distributed generations and battery energy storage systems towards high integration of green energy considering uncertainty and demand response progra...
Published 2025“…Scenario reduction through the Backward Reduction Algorithm (BRA) manages computational complexity. To solve the proposed model, a hybrid approach combining Non-Dominated Sorting Genetic Algorithm II (NSGAII) and Multi-Objective Particle Swarm Optimization (MOPSO) is employed. …”
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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar
Published 2017“…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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