A multi-objective approach for renewable distributed generator unit’s placement considering generation and load uncertainties

Jayaram, Kinjarapu; Kollu, Ravindra; Prasad, K. R. K. V.; Murthy, K. V. S. Ramachandra

doi:10.1007/s40095-021-00438-5

Cited by 2 publications

(2 citation statements)

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“…It is evident that when it comes for reducing power losses and costs, the NSGA-III performs better than the PSO algorithm. The DERs of the MT type should be placed more advantageously in (15,33), FC units at (22,18), and the ideal location for PV is aboard busses (29,25,12,32). The findings demonstrate that, in terms of minimizing power loss, the DER placement determined by NSGA-III is superior to the position determined by PSO, where the objective power loss and cost of (102.6058 KW, and 168.7075 $/h) which are better than those obtained by PSO methods of (116.47 KW, 171.5268 $/h).…”

Section: Scenario 1 • Case 1(comparative Case)mentioning

confidence: 99%

“…In Maji, S et al [21], the authors offer a hybrid approach based on novel valueadaptive weight-aggregated (VAWA) Grey-wolf optimizer (GWO) to merge PV in the DN for boosting voltage, and reducing losses. The purpose of Jayaram, K et al [22] is to resolve the problem of allocation of the DERs in a DN, Deployment of DER units will offer technical benefits such as loss minimization, bus voltage profile improvement, line loading reduction, and ensure a more flexible solution of the Multi-objective Backtracking search algorithm (PMBSA) considering generation and load uncertainties. The goal of the study in Ref.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Planning of Renewable Energy Source with Different Load Models

saleh

2024

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this paper presents an optimization algorithm, named Non dominated Sorting Genetic Algorithm III (NSGA-III) method to identify the optimal allocation of hybrid distributed energy resources (DERs) including photovoltaic system (PV), micro-turbine (MT), and fuel cell (FC) in distribution system considering four different load models such as industrial, residential, commercial and constant load model. With increasing the integration of renewable energy resources, the uncertainties resulting from these sources posed a serious challenge to the operation of the network. To be closer to the reality, the network performance is analyzed considering the influence of the uncertainties produced from RES. Point Estimate Method (PEM) is used to model the uncertainties generated from renewable energy resources. The main aim of this paper is to maximize technical and economic benefits of DERs by minimizing various objective functions such as the total power loss, cost, and voltage deviation subject to different power system constraints. Multi-objective planning framework is appraised using two standards IEEE networks with various scenarios. Comparative analyses are conducted on standard distribution systems under different load model and mix of different types of DERs. Level diagram is implemented to analysis and compares the influence of different combinations of load models on the system performance. The obtained results show that, the system performance is greatly influenced by uncertainties accompanied with DER and power system itself. The suggested multi-objective planning frameworks shows high accuracy compared to other techniques applied in previous researches.

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