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Efficient Generation Capacity Allocation of Electric Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (20 December 2020) | Viewed by 2235

Special Issue Editor


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Guest Editor
Department of Electrical and Computer Engineering, University of Patras, Rio Campus, 26504 Patras, Greece
Interests: optimization tools for the design and operation of electricity systems; the extension of optimal power flow tools; methods of increasing generation absorption capacity of power systems and plug-n-play smart grid converters
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Special Issue Information

Dear Colleagues,

I am the Guest Editor for the Special Issue “Efficient Generation Capacity Allocation of Electric Power Systems” of the open-access journal Energies, and I would like to invite you to contribute an article to this Special Issue on your current research.

Generation expansion planning is practically still done in a heuristic manner by system operators. That was sufficient when there were only a few candidate locations for new capacities, because a small number of power flows for the suggested expansion options was enough to determine if the future system will respect system constraints. However, as distributed generation increases with the RES “frenzy”, the candidate locations become numerous. Thus, a more concise method is needed to coordinate the allocation of new capacities on the network in order to exploit the existing network capabilities to the “maximum”. This “maximum” is also redefined today, as traditional constraints (voltage limits, line thermal limits, etc.) are now expanded to power quality and security issues.

What we are seeking for this Special Issue is novel, effective allocation methods of new generation capacity under those new terms. I believe your research could be of great importance for the scientific community in this field and providing it in an open-access format will certainly maximize its value.

Prof. Dr. Panagis N. Vovos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Network headroom
  • Power generation economics
  • Investments
  • Renewable energy generation
  • Capacity planning

Published Papers (1 paper)

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Research

23 pages, 3532 KiB  
Article
A Modified Artificial Bee Colony for Probabilistic Peak Shaving Technique in Generators Operation Planning: Optimal Cost–Benefit Analysis
by Daw Saleh Sasi Mohammed, Muhammad Murtadha Othman and Ahmed Elbarsha
Energies 2020, 13(12), 3252; https://doi.org/10.3390/en13123252 - 23 Jun 2020
Viewed by 1945
Abstract
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 [...] Read more.
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 SUC value. 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. Full article
(This article belongs to the Special Issue Efficient Generation Capacity Allocation of Electric Power Systems)
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