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Optimal allocation of distributed generation in meshed power networks: A metaheuristic approach

Muhammad Saad Khan, Danial Waheed, Sulman Shahzad, Suhail Afzal, Heybet Killic

2024IET Renewable Power Generation21 citationsDOIOpen Access PDF

Abstract

Abstract This paper introduces a novel metaheuristic technique, a COOT‐based algorithm, to determine the optimal Distributed Generation (DG) allocation within a loop‐configured network. This method significantly narrows the optimization gap by leveraging a COOT‐based algorithm, ensuring accelerated convergence and resultant global optima. The core incentive for employing this technique is to substantially mitigate power loss, curtail voltage deviation, and bolster system stability in a loop distribution network. To attain optimal outcomes, the elaborated COOT and improved grey wolf optimization improved grey wolf optimization (IGWO) algorithms were executed on IEEE bus‐33 and 69 mesh distribution networks (MDNs) under varying power factors. The derived mathematical results effectively underscore accomplishing the stipulated objectives: a marked reduction in voltage deviation and power loss coupled with an augmentation in system stability. Notably, at unity, incorporating DGs resulted in a paramount reduction in power loss, attaining a decrease of 78% and 85% for bus‐33 and 69 MDNs, respectively. Moreover, an impressive decrease in power loss by 94% and 98% was observed at the optimal power factor for both MDNs. A comparative evaluation of the results accentuates that the proposed COOT and IGWO algorithms eclipse other documented research in performance, showcasing superior efficiency on a techno‐economic basis.

Topics & Concepts

Mathematical optimizationMetaheuristicComputer scienceReduction (mathematics)Convergence (economics)Power lossBat algorithmPower (physics)VoltageElectric power systemAlgorithmMathematicsEngineeringParticle swarm optimizationEconomicsElectrical engineeringEconomic growthQuantum mechanicsGeometryPhysicsOptimal Power Flow DistributionMicrogrid Control and OptimizationElectric Power System Optimization