A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis

In the generation of operating system planning, saving utility cost (SUC) is customarily implemented to attain the forecasted optimal economic benefits in a generating system associated with renewable energy integration. In this paper, an improved approach for the probabilistic peak-shaving techniqu...

Full description

Bibliographic Details
Published in:Energies
Main Author: Mohammed D.S.S.; Othman M.M.; Elbarsha A.
Format: Article
Language:English
Published: MDPI AG 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089995616&doi=10.3390%2fen13123252&partnerID=40&md5=f55150e221c58a43bffbc1419d2ee00f
id 2-s2.0-85089995616
spelling 2-s2.0-85089995616
Mohammed D.S.S.; Othman M.M.; Elbarsha A.
A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
2020
Energies
13
12
10.3390/en13123252
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089995616&doi=10.3390%2fen13123252&partnerID=40&md5=f55150e221c58a43bffbc1419d2ee00f
In the generation of operating system planning, saving utility cost (SUC) is customarily implemented to attain the forecasted optimal economic benefits in a generating system associated with renewable energy integration. In this paper, an improved approach for the probabilistic peak-shaving technique (PPS) based on computational intelligence is proposed to increase the SUCvalue. Contrary to the dispatch processing of the PPS technique, which mainly relies on the dispatching of each limited energy unit in sequential order, a modified artificial bee colony with a new searching mechanism (MABC-NSM) is proposed. The SUC is originated from the summation of the Saving Energy Cost and Saving Expected Cycling Cost of the generating system. In addition, further investigation for obtaining the optimal value of the SUC is performed between the SUC determined directly and indirectly estimated by referring to the energy reduction of thermal units (ERTU). Comparisons were made using MABC-NSM and a standard artificial bee colony and verified on the modified IEEE RTS-79 with different peak load demands. A compendium of the results has shown that the proposed method is constituted with robustness to determine the global optimal values of the SUC either obtained directly or by referring to the ERTU. Furthermore, SUC increments of 7.26% and 5% are achieved for 2850 and 3000 MW, respectively. © 2020 by the authors.
MDPI AG
19961073
English
Article
All Open Access; Gold Open Access; Green Open Access
author Mohammed D.S.S.; Othman M.M.; Elbarsha A.
spellingShingle Mohammed D.S.S.; Othman M.M.; Elbarsha A.
A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
author_facet Mohammed D.S.S.; Othman M.M.; Elbarsha A.
author_sort Mohammed D.S.S.; Othman M.M.; Elbarsha A.
title A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
title_short A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
title_full A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
title_fullStr A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
title_full_unstemmed A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
title_sort A modified artificial bee colony for probabilistic peak shaving technique in generators operation planning: Optimal cost-benefit analysis
publishDate 2020
container_title Energies
container_volume 13
container_issue 12
doi_str_mv 10.3390/en13123252
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089995616&doi=10.3390%2fen13123252&partnerID=40&md5=f55150e221c58a43bffbc1419d2ee00f
description In the generation of operating system planning, saving utility cost (SUC) is customarily implemented to attain the forecasted optimal economic benefits in a generating system associated with renewable energy integration. In this paper, an improved approach for the probabilistic peak-shaving technique (PPS) based on computational intelligence is proposed to increase the SUCvalue. Contrary to the dispatch processing of the PPS technique, which mainly relies on the dispatching of each limited energy unit in sequential order, a modified artificial bee colony with a new searching mechanism (MABC-NSM) is proposed. The SUC is originated from the summation of the Saving Energy Cost and Saving Expected Cycling Cost of the generating system. In addition, further investigation for obtaining the optimal value of the SUC is performed between the SUC determined directly and indirectly estimated by referring to the energy reduction of thermal units (ERTU). Comparisons were made using MABC-NSM and a standard artificial bee colony and verified on the modified IEEE RTS-79 with different peak load demands. A compendium of the results has shown that the proposed method is constituted with robustness to determine the global optimal values of the SUC either obtained directly or by referring to the ERTU. Furthermore, SUC increments of 7.26% and 5% are achieved for 2850 and 3000 MW, respectively. © 2020 by the authors.
publisher MDPI AG
issn 19961073
language English
format Article
accesstype All Open Access; Gold Open Access; Green Open Access
record_format scopus
collection Scopus
_version_ 1820775463461584896