Effects of Changing Consumer Demand on Distributed Generation and Grid Optimization

Integrating Distributed Generations (DGs) within adaptive power grids is a highly effective approach to reducing electricity losses and minimizing generation and switching costs in contemporary electric systems. The efficiency of these strategies is heavily influenced by consumer load profiles, which significantly affect energy losses, generation expenses, and overall purchasing costs. This connection underscores the crucial role of consumer load variations in determining electricity losses, operational expenditures, and energy pricing, thereby impacting the network’s topology and the optimal placement of DGs. Considering load variability in DG placement within reconfigurable networks adds considerable computational complexity, resulting in extended processing times. Ignoring these variations, however, can lead to inaccurate estimations of losses and costs. This research examines how consumer load variations affect the allocation of DG and the reconfiguration strategies of distribution grids. Utilizing the Mathematical Programming Language (AMPL) as a traditional optimization tool, the study evaluates the proposed model across diverse distribution networks. The simulation results demonstrate that while consumer load variations do not change the total number of DG units required, they significantly influence the optimal locations, switching combinations, and total grid costs. From an energy policy perspective, these findings emphasize the need for utility operators to incorporate consumer load dynamics into their strategies. This integration ensures better alignment with regulatory frameworks that promote efficient energy.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3573588
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
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article

Effects of Changing Consumer Demand on Distributed Generation and Grid Optimization

Amir Bagheri, Augustine Awaafo, Francisco Jurado, Alireza Soleimani et al.
IEEE Access
Power Systems and Renewable Energy
article

Effects of Changing Consumer Demand on Distributed Generation and Grid Optimization

Amir Bagheri, Augustine Awaafo, Francisco Jurado, Alireza Soleimani, Anna Pinnarelli, Meisam Mahdavi
article en

Abstract

Integrating Distributed Generations (DGs) within adaptive power grids is a highly effective approach to reducing electricity losses and minimizing generation and switching costs in contemporary electric systems. The efficiency of these strategies is heavily influenced by consumer load profiles, which significantly affect energy losses, generation expenses, and overall purchasing costs. This connection underscores the crucial role of consumer load variations in determining electricity losses, operational expenditures, and energy pricing, thereby impacting the network’s topology and the optimal placement of DGs. Considering load variability in DG placement within reconfigurable networks adds considerable computational complexity, resulting in extended processing times. Ignoring these variations, however, can lead to inaccurate estimations of losses and costs. This research examines how consumer load variations affect the allocation of DG and the reconfiguration strategies of distribution grids. Utilizing the Mathematical Programming Language (AMPL) as a traditional optimization tool, the study evaluates the proposed model across diverse distribution networks. The simulation results demonstrate that while consumer load variations do not change the total number of DG units required, they significantly influence the optimal locations, switching combinations, and total grid costs. From an energy policy perspective, these findings emphasize the need for utility operators to incorporate consumer load dynamics into their strategies. This integration ensures better alignment with regulatory frameworks that promote efficient energy.

IEEE AccessVol. 13
Universidade de Brasília (BR), Universidad de Jaén (ES), University of Energy and Natural Resources (GH), University of Calabria (IT), University of Zanjan (IR)
Affordable and clean energy
Openalex Percentile: Top 91%
Power Systems and Renewable Energy
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