Search Results - (( loading optimization strategy algorithm ) OR ( time optimization method algorithm ))
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Optimal load management strategy for enhanced time of use (ETOU) electricity tariff in Peninsular Malaysia / Mohamad Fani Sulaima
Published 2020“…Particle swarm optimization (PSO), evolutionary particle swarm optimization (EPSO), and ant colony optimization (ACO) algorithms were applied to optimize the simultaneous LM strategies of peak clipping, valley filling and load shifting in order to minimize the energy consumption and maximum demand costs, and improve economic indexes such as load factor and building economic efficiency response. …”
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Optimal cost benefit of the EToU electricity tariff for a manufacturing operation by using optimization algorithm
Published 2021“…Optimization algorithm namely Ant Colony Optimization (ACO) is implemented and cases with and without implementation of algorithm are compared in order to idealize the load profile of DSM strategy. …”
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ETOU electricity tariff for manufacturing load shifting strategy using ACO algorithm
Published 2019“…Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. …”
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Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm
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Optimal penalty method in distribution service restoration using genetic algorithm
Published 2013“…The proposed technique is implemented to improve the penalty strategy to enhance the performance of algorithm and reduce the convergence iteration. …”
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Sliding mode controller optimization-based three-phase rectifier: review study
Published 2024“…Numerous control strategies are used to optimize the performance of the three-phase rectifier. …”
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A proposed genetic algorithm to optimize service restoration in electrical networks with respect to the probability of transformers failure
Published 2010“…In many researches a Genetic Algorithm is employed as a powerful tool to solve this multi-objective, multi-constraint optimization problem. …”
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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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An Optimal Load Shedding Methodology for Radial Power Distribution Systems to Improve Static Voltage Stability Margin using Gravity Search
Published 2014“…In this paper, an effective method is presented for estimating the optimal amount of load to be shed in a distribution system based on the gravitational search algorithm (GSA). …”
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…The results show proposed algorithm approximately solved problems averagely 22% better in terms of find feasible optimal solutions depends of various performance measures in 72.2% of computational time than other previous considered key algorithms.…”
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Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines
Published 2025“…This study introduces a novel approach for PID controller tuning in wind turbine systems using single-agent optimization methods, specifically the memory smoothed functional algorithm (MSFA) and norm-limited smoothed functional algorithm (NL-SFA). …”
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…Next PNN is used to classify load profile according to its group. Results obtained show that FCM algorithm can be used as the clustering method to obtained TLPs and PNN is proven to be reliable to allocate the measured load profiles accurately according to their type of consumers.…”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Optimal distribution system reconfiguration incorporating distributed generation based on simplified network approach / Mohammad Al Samman
Published 2020“…Since the NR problem contains a huge combinational search space, most researchers applied meta-heuristic methods to attain optimal NR solution. However, meta-heuristic methods do not always guarantee optimal solution and furthermore they consume huge processing time. …”
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Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System
Published 2020“…This research aimed to develop a Predictive Functional Control using Reduced-Order Observer (PFC-ROO) to reduce the complexity of the pneumatic system. An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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A novel MPPT approach for photovoltaic system using Pelican optimization and high-gain DC–DC converter
Published 2025“…Solar panels typically produce electrical outputs that vary in DC voltage, requiring a well-designed DC link interfacing circuit to ensure efficient energy transfer from the PV source to the load. In response to these needs, this study introduces the Pelican Optimization Algorithm (POA), a novel nature-inspired stochastic optimization technique designed to track the Maximum Power Point (MPP) of solar sources with high precision. …”
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Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context
Published 2018“…A part of the developed algorithm is used to deal with the optimal scheduling control while the other actuates the dynamic demand response based PV power forecasting. …”
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An improved hybrid method combined with a cloud-based supervisory control to facilitate smooth coordination under low-inertia grids
Published 2025“…The presented approach synthesizes the traditional droop control and the generalized cloud-based algorithm to address challenges related to dynamic load variations and intermittent renewable energy sources. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…Ultimately, this method improves the protection of project schedules, optimizes infrastructure utilization, and maximizes economic returns and strategic alignment in Malaysia's energy industry.…”
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