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Optimal allocation of wind and solar power based distributed generation: case study

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 14 No. 6 (2024)

DOI
10.11591/ijece.v14i6.pp6086-6093
ISSN
2722-2578, 2088-8708
Published
2024-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The main goal of the power system is to congregate the power demand within the power grid while maintaining economical operation, system security and minimal environmental impact. Due to the increasing demand for electrical energy, many problems have arisen with the power systems. These problems include excessive load, uneven system performance, unsatisfactory voltage profile, and an increase in network power losses. To address these issues, more generation sources and improved transmission capacity are required. In order to meet increasing electricity demand, it is more efficient to integrate a sufficient number of smaller generation units. Utilities and consumers can get the significant benefit from installation of distributed generation (DG), which reduces power losses, progress voltage profile, increases power quality and reliability, delays system updates, supports local reactive power, standby generation and peak limiting. This article aims to enrich the performance of the entire network through the best possible placement and penetration of wind energy and solar photovoltaic (PV) dispersed generation.

Collaboration network of the authors

2 authors · 1 co-authorship link

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  • KLS Gogte Institute of Technology
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 2026.
Metadata as oai_dc, converted from Crossref
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