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An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
Published 2022“…Therefore, it is imperative to account for these adverse effects of the integration of DERs on the distribution network and minimize their impact when calculating the Hosting Capacity (HC). Two algorithms are presented in this study derived from a novel modified iterative method and a novel Repeated Particle Swarm Optimization (RPSO) method for determining the HC for multiple DER units simultaneously or a single DER unit integrating into radial or mesh networks. …”
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Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm
Published 2023“…The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO, particle swarm optimization (PSO), and salp swarm algorithm (SSA). …”
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Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg...
Published 2023“…The performance of the IFLA when applied to EH coordinated scheduling and management problems with the aim of profit maximization is compared with the conventional FLA, particle swarm optimization (PSO), and manta ray foraging optimization (MRFO) methods. …”
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On-site workshop investment problem: A novel mathematical approach and solution procedure
Published 2023“…Computational experiments show that the proposed method has solved most of the instances of the addressed problem to optimality and outperformed the existing metaheuristics, e.g., Simulated Annealing (SA) and Particle Swarm Optimization (PSO). …”
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A new bi-objective model of the urban public transportation hub network design under uncertainty
Published 2019“…Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. …”
