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A Modified Artificial Bee Colony for Probabilistic Peak Shaving Technique in Generators Operation Planning: Optimal Cost–Benefit Analysis

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  • Daw Saleh Sasi Mohammed

    (Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam, Selangor 40450, Malaysia
    Department of Electrical and Electronic Engineering, Bright Star University, Brega 858, Libya)

  • Muhammad Murtadha Othman

    (Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam, Selangor 40450, Malaysia)

  • Ahmed Elbarsha

    (Department of Electrical and Electronic Engineering, Bright Star University, Brega 858, Libya)

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 (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.

Suggested Citation

  • Daw Saleh Sasi Mohammed & Muhammad Murtadha Othman & Ahmed Elbarsha, 2020. "A Modified Artificial Bee Colony for Probabilistic Peak Shaving Technique in Generators Operation Planning: Optimal Cost–Benefit Analysis," Energies, MDPI, vol. 13(12), pages 1-23, June.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3252-:d:375488
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    References listed on IDEAS

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    1. Denny, Eleanor & O'Malley, Mark, 2009. "The impact of carbon prices on generation-cycling costs," Energy Policy, Elsevier, vol. 37(4), pages 1204-1212, April.
    2. Uddin, Moslem & Romlie, Mohd Fakhizan & Abdullah, Mohd Faris & Abd Halim, Syahirah & Abu Bakar, Ab Halim & Chia Kwang, Tan, 2018. "A review on peak load shaving strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3323-3332.
    3. Yan Li & Ming Zhou & Dawei Wang & Yuehui Huang & Zifen Han, 2017. "Universal Generating Function Based Probabilistic Production Simulation Approach Considering Wind Speed Correlation," Energies, MDPI, vol. 10(11), pages 1-15, November.
    4. Aghahosseini, Arman & Bogdanov, Dmitrii & Barbosa, Larissa S.N.S. & Breyer, Christian, 2019. "Analysing the feasibility of powering the Americas with renewable energy and inter-regional grid interconnections by 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 187-205.
    5. Brouwer, Anne Sjoerd & van den Broek, Machteld & Zappa, William & Turkenburg, Wim C. & Faaij, André, 2016. "Least-cost options for integrating intermittent renewables in low-carbon power systems," Applied Energy, Elsevier, vol. 161(C), pages 48-74.
    6. Clauser, Christoph & Ewert, Markus, 2018. "The renewables cost challenge: Levelized cost of geothermal electric energy compared to other sources of primary energy – Review and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3683-3693.
    7. Liao, Gwo-Ching, 2011. "A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power," Energy, Elsevier, vol. 36(2), pages 1018-1029.
    8. Elliston, Ben & MacGill, Iain & Diesendorf, Mark, 2013. "Least cost 100% renewable electricity scenarios in the Australian National Electricity Market," Energy Policy, Elsevier, vol. 59(C), pages 270-282.
    9. Antimo Barbato & Antonio Capone, 2014. "Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey," Energies, MDPI, vol. 7(9), pages 1-38, September.
    10. Xuanhu He & Wei Wang & Jiuchun Jiang & Lijie Xu, 2015. "An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow," Energies, MDPI, vol. 8(4), pages 1-26, March.
    11. Arman Aghahosseini & Dmitrii Bogdanov & Christian Breyer, 2017. "A Techno-Economic Study of an Entirely Renewable Energy-Based Power Supply for North America for 2030 Conditions," Energies, MDPI, vol. 10(8), pages 1-28, August.
    12. Safdarnejad, Seyed Mostafa & Hedengren, John D. & Baxter, Larry L., 2016. "Dynamic optimization of a hybrid system of energy-storing cryogenic carbon capture and a baseline power generation unit," Applied Energy, Elsevier, vol. 172(C), pages 66-79.
    13. Frei, Fanny & Sinsel, Simon R. & Hanafy, Ahmed & Hoppmann, Joern, 2018. "Leaders or laggards? The evolution of electric utilities’ business portfolios during the energy transition," Energy Policy, Elsevier, vol. 120(C), pages 655-665.
    14. Yifang Tang & Zhiqiang Liu & Lan Li, 2019. "Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System," Energies, MDPI, vol. 12(24), pages 1-17, December.
    15. Suman Bhullar & Smarajit Ghosh, 2018. "Optimal Integration of Multi Distributed Generation Sources in Radial Distribution Networks Using a Hybrid Algorithm," Energies, MDPI, vol. 11(3), pages 1-15, March.
    16. Zhu, Kai & Li, Xueqiang & Campana, Pietro Elia & Li, Hailong & Yan, Jinyue, 2018. "Techno-economic feasibility of integrating energy storage systems in refrigerated warehouses," Applied Energy, Elsevier, vol. 216(C), pages 348-357.
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