Literature Review: Quantification of Loss and Emission Reductions in Distributed Generation Optimization
DOI:
https://doi.org/10.29103/jreece.v6i1.25820Keywords:
Radial Distribution Networks, Particle Swarm Optimization, Distributed Generation, Controllable Power Factor, Voltage StabilityAbstract
The integration of Distributed Generation (DG) into modern power distribution networks plays a vital role in enhancing operational efficiency and driving global decarbonization targets. However, capturing the full technical and environmental advantages of DG requires precise multi-objective optimization. This study presents a systematic literature review aimed at evaluating, synthesizing, and quantifying the methodologies used for power loss minimization and carbon emission reductions within radial distribution networks. Adhering to the PRISMA 2020 framework, a rigorous bibliometric and content analysis was performed using Publish or Perish (PoP) and VOSviewer. Out of 323 initially screened articles indexed in the Scopus database from 2017 to 2025, 112 peer-reviewed papers met the strict inclusion criteria and were comprehensively analyzed. The synthesis reveals that optimal DG placement utilizing swarm intelligence techniques—predominantly Particle Swarm Optimization (PSO) and Genetic Algorithms (GA)—consistently achieves substantial improvements, yielding active power loss reductions between 40% and 94% and annual greenhouse gas emission mitigations ranging from 25% to 65%. Bibliometric mapping highlights a mature focus on voltage profile enhancement and network reconfiguration, while critical gaps remain in standardizing dynamic hosting capacity and life-cycle assessment (LCA) frameworks for emissions. Although simulation-based optimization models show high technical maturity, they still require real-world validation. Future research must prioritize dynamic operational strategies under stochastic renewable uncertainty to bridge this implementation gap.
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