2020 IEEE Power and Energy Conference at Illinois (PECI) 2020
DOI: 10.1109/peci48348.2020.9064636
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Sizing and Allocation of Distributed Energy Resources for Loss Reduction using Heuristic Algorithms

Abstract: Loss minimization in distribution networks (DN) is of great significance since the trend to the distributed generation (DG) requires the most efficient operating scenario possible for economic viability variations. Moreover, voltage instability in DNs is a critical phenomenon and can lead to a major blackout in the system. The decreasing voltage stability level restricts the increase of load served by distribution companies. DG can be used to improve DN capabilities and brings new opportunities to traditional … Show more

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Cited by 24 publications
(10 citation statements)
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“…Then it can dedicate the level of power exchange with the upstream grid for various hours. To implement such an intelligent autonomous mechanism, a smart environment is needed that is only feasible through IoT infrastructures [39]. The following flowchart concisely describes the proposed scheme.…”
Section: Energy Management Paradigm By Microgrid's Controllermentioning
confidence: 99%
“…Then it can dedicate the level of power exchange with the upstream grid for various hours. To implement such an intelligent autonomous mechanism, a smart environment is needed that is only feasible through IoT infrastructures [39]. The following flowchart concisely describes the proposed scheme.…”
Section: Energy Management Paradigm By Microgrid's Controllermentioning
confidence: 99%
“…The DC RNG used PV panels and an MPPT converter, which conditiones the panels' power and provides the maximum available power to the RNG. Different load models require different solar capacities [23]. In a zero net energy house, the solar capacity for each load model was obtained by matching the annual values of the generated and consumed energies, meaning that, the annual generated PV power should match the annual RNG's power consumption.…”
Section: Pvmentioning
confidence: 99%
“…There is a vast amount of literature on different optimization algorithms implemented for allocation of DGs. Several methods have recently been proposed which they are mostly meta-heuristic algorithms including ant lion [7], artificial bee colony [4], crow search algorithm [8], genetic algorithms [9], grey wolf algorithm [10], harmony search algorithm [11] , tabu search [3], whale optimization algorithm [12] and several variants of particle swarm optimization [13][14] [15]. There are also several deterministic algorithms such as analytical [16], efficient analytical method [17], MILP [18] and MINPL [19].…”
Section: Introductionmentioning
confidence: 99%