Article, 2024

Optimal sizing and siting of distributed generation systems incorporating reactive power tariffs via water flow optimization

Electric Power Systems Research, ISSN 1873-2046, 0378-7796, Volume 231, Page 110278, 10.1016/j.epsr.2024.110278

Contributors

Jahed, Younes Ghazagh [1] Mousavi, Seyyed Yousef Mousazadeh 0000-0003-2372-0089 (Corresponding author) [1] Golestan, Saeed 0000-0002-8568-1612 [2]

Affiliations

  1. [1] University of Mazandaran
  2. [NORA names: Iran; Asia, Middle East];
  3. [2] Aalborg University
  4. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Distributed generation (DG) systems are gaining popularity because they generate electricity closer to the point of consumption. This reduces transmission and distribution losses and enhances system reliability. For the efficient and cost-effective use of these systems, optimal sizing and siting of DGs is crucial. This paper introduces a Water Flow Optimization (WFO)-based method for the optimal placement and sizing of DG systems capable of injecting both active and reactive power simultaneously. This study assesses both the technical and economic facets of the system, taking into account power losses and the comprehensive annual economic costs, including capital investment, deployment, operation, and maintenance. A significant aspect of this research is the DG units' capability to enhance voltage and minimize losses, factoring in the reactive power tariff. The findings show that the WFO method surpasses other optimization techniques, such as particle swarm optimization, whale optimization algorithm, genetic algorithm and gray wolf optimization. Furthermore, the study emphasizes the cost advantages of injecting reactive power. The minimum annual economic losses (AEL) recorded in this study are $19,207 and $13,852 for IEEE-33 and IEEE-69 bus systems, respectively. In comparison, for DGs only injecting active power, the AEL increases to $24,749 and $41,381 for the corresponding systems.

Keywords

DG system, IEEE 69-bus system, IEEE-33, IEEE-69, WFO, active power, advantage, algorithm, annual economic cost, annual economic loss, aspects, bus system, capability, capital, capital investment, comparison, consumption, cost, cost advantage, cost-effective use, deployment, distributed generation, distribution, distribution losses, economic costs, economic facets, economic losses, electricity, enhanced system reliability, enhanced voltage, facets, findings, flow optimization, generation, generation system, genetic algorithm, grey wolf optimizer, injecting active power, injecting reactive power, investment, loss, maintenance, method, operation, optimal placement, optimal size, optimization, optimization algorithm, optimization techniques, particle swarm optimization, particles, placement, power, power tariff, reactive power, reduce transmission, reliability, research, significant aspect, sites, siting of distributed generation, size, study, swarm optimization, system, system reliability, tariff, technique, transmission, unit capabilities, use, voltage, water, water flow optimization, whale optimization algorithm, whales, wolf optimizer

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