IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i15p3807-d1448593.html
   My bibliography  Save this article

A Multiparadigm Approach for Generation Dispatch Optimization in a Regulated Electricity Market towards Clean Energy Transition

Author

Listed:
  • Suroso Isnandar

    (School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung 40132, Indonesia
    Perusahaan Listrik Negara, PT PLN Persero, Jakarta 12160, Indonesia)

  • Jonathan F. Simorangkir

    (School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung 40132, Indonesia)

  • Kevin M. Banjar-Nahor

    (School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung 40132, Indonesia)

  • Hendry Timotiyas Paradongan

    (School of Business and Management, Bandung Institute of Technology, Bandung 40132, Indonesia)

  • Nanang Hariyanto

    (School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung 40132, Indonesia)

Abstract

In Indonesia, the power generation sector is the primary source of carbon emissions, largely due to the heavy reliance on coal-fired power plants, which account for 60% of electricity production. Reducing these emissions is essential to achieve national clean energy transition goals. However, achieving this initiative requires careful consideration, especially regarding the complex interactions among multiple stakeholders in the Indonesian electricity market. The electricity market in Indonesia is characterized by its non-competitive and heavily regulated structure. This market condition often requires the PLN, as the system operator, to address multi-objective and multi-constraint problems, necessitating optimization in the generation dispatch scheduling scheme to ensure a secure, economical, and low-carbon power system operation. This research introduces a multiparadigm approach for GS optimization in a regulated electricity market to support the transition to clean energy. The multiparadigm integrates multi-agent system and system dynamic paradigms to model, simulate, and quantitatively analyze the complex interactions among multiple stakeholders in the Indonesian regulated electricity market. The research was implemented on the Java–Madura–Bali power system using AnyLogic 8 University Researcher Software. The simulation results demonstrate that the carbon policy scheme reduces the system’s carbon emissions while increasing the system’s cost of electricity. A linear regression for sensitivity analysis was conducted to determine the relationship between carbon policies and the system’s cost of electricity. This research offers valuable insights for policymakers to develop an optimal, acceptable, and reasonable power system operation scheme for all stakeholders in the Indonesian electricity market.

Suggested Citation

  • Suroso Isnandar & Jonathan F. Simorangkir & Kevin M. Banjar-Nahor & Hendry Timotiyas Paradongan & Nanang Hariyanto, 2024. "A Multiparadigm Approach for Generation Dispatch Optimization in a Regulated Electricity Market towards Clean Energy Transition," Energies, MDPI, vol. 17(15), pages 1-28, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3807-:d:1448593
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/15/3807/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/15/3807/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dongfang Ren & Xiaopeng Guo, 2023. "Simulation modeling and analysis of carbon emission reduction potential of multi-energy generation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 11823-11845, October.
    2. Salkuti, Surender Reddy, 2019. "Day-ahead thermal and renewable power generation scheduling considering uncertainty," Renewable Energy, Elsevier, vol. 131(C), pages 956-965.
    3. Nemati, Mohsen & Braun, Martin & Tenbohlen, Stefan, 2018. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming," Applied Energy, Elsevier, vol. 210(C), pages 944-963.
    4. Wang, Tonghe & Hua, Haochen & Shi, Tianying & Wang, Rui & Sun, Yizhong & Naidoo, Pathmanathan, 2024. "A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy," Applied Energy, Elsevier, vol. 356(C).
    5. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    6. Sterman, John., 1994. "Learning in and about complex systems," Working papers 3660-94., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    7. Zhao Luo & Jinghui Wang & Ni Xiao & Linyan Yang & Weijie Zhao & Jialu Geng & Tao Lu & Mengshun Luo & Chenming Dong, 2022. "Low Carbon Economic Dispatch Optimization of Regional Integrated Energy Systems Considering Heating Network and P2G," Energies, MDPI, vol. 15(15), pages 1-14, July.
    8. Psarros, Georgios N. & Papathanassiou, Stavros A., 2023. "Generation scheduling in island systems with variable renewable energy sources: A literature review," Renewable Energy, Elsevier, vol. 205(C), pages 1105-1124.
    9. Trinadh Pamulapati & Muhammed Cavus & Ishioma Odigwe & Adib Allahham & Sara Walker & Damian Giaouris, 2022. "A Review of Microgrid Energy Management Strategies from the Energy Trilemma Perspective," Energies, MDPI, vol. 16(1), pages 1-34, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lu, Jinfeng & Dimov, Dimo, 2023. "A system dynamics modelling of entrepreneurship and growth within firms," Journal of Business Venturing, Elsevier, vol. 38(3).
    2. Day Yang Liu & Wen Chun Tsai & Pei Leen Liu & Chung Yi Fang, 2021. "Determinants of sales revenue in innovation diffusion effects of Taiwan sports lottery during the FIFA World Cup 2018," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 43-58, June.
    3. Hazhir Rahmandad & Nelson Repenning, 2016. "Capability erosion dynamics," Strategic Management Journal, Wiley Blackwell, vol. 37(4), pages 649-672, April.
    4. Katarzyna Tworek & Katarzyna Walecka-Jankowska & Anna Zgrzywa-Ziemak, 2019. "The role of information systems in shaping integrative logic for business sustainability," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(4), pages 125-146.
    5. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    6. Stadler, M. & Groissböck, M. & Cardoso, G. & Marnay, C., 2014. "Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel," Applied Energy, Elsevier, vol. 132(C), pages 557-567.
    7. Hui Wang & Yao Xu, 2024. "Optimized Decision-Making for Multi-Market Green Power Transactions of Electricity Retailers under Demand-Side Response: The Chinese Market Case Study," Energies, MDPI, vol. 17(11), pages 1-15, May.
    8. Aste, Niccolò & Del Pero, Claudio & Leonforte, Fabrizio & Manfren, Massimiliano, 2013. "A simplified model for the estimation of energy production of PV systems," Energy, Elsevier, vol. 59(C), pages 503-512.
    9. Yazdanie, Mashael & Densing, Martin & Wokaun, Alexander, 2017. "Cost optimal urban energy systems planning in the context of national energy policies: A case study for the city of Basel," Energy Policy, Elsevier, vol. 110(C), pages 176-190.
    10. Hao, Ran & Lu, Tianguang & Ai, Qian & Wang, Zhe & Wang, Xiaolong, 2020. "Distributed online learning and dynamic robust standby dispatch for networked microgrids," Applied Energy, Elsevier, vol. 274(C).
    11. Meri Duryan & Dragan Nikolik & Godefridus Merode & Leopold M. G. Curfs, 2015. "Reflecting on the efficacy of cognitive mapping for decision-making in intellectual disability care: a case study," International Journal of Health Planning and Management, Wiley Blackwell, vol. 30(2), pages 127-144, April.
    12. Marek Krok & Paweł Majewski & Wojciech P. Hunek & Tomasz Feliks, 2022. "Energy Optimization of the Continuous-Time Perfect Control Algorithm," Energies, MDPI, vol. 15(4), pages 1-13, February.
    13. Michiel Fremouw & Annamaria Bagaini & Paolo De Pascali, 2020. "Energy Potential Mapping: Open Data in Support of Urban Transition Planning," Energies, MDPI, vol. 13(5), pages 1-15, March.
    14. Sarah Cechvala & Brian Ganson, 2024. "Systems Perspectives on Business and Peace: The Contingent Nature of Business-Related Action with Respect to Peace Positive Impacts," Journal of Business Ethics, Springer, vol. 194(3), pages 523-544, October.
    15. Erik Pruyt & Jan H. Kwakkel, 2014. "Radicalization under deep uncertainty: a multi-model exploration of activism, extremism, and terrorism," System Dynamics Review, System Dynamics Society, vol. 30(1-2), pages 1-28, January.
    16. Sarah Gerritsen & Sophia Harré & David Rees & Ana Renker-Darby & Ann E. Bartos & Wilma E. Waterlander & Boyd Swinburn, 2020. "Community Group Model Building as a Method for Engaging Participants and Mobilising Action in Public Health," IJERPH, MDPI, vol. 17(10), pages 1-12, May.
    17. David C. Lane, 2012. "What Is a ‘Policy Insight’?," Systems Research and Behavioral Science, Wiley Blackwell, vol. 29(6), pages 590-595, November.
    18. Iván Barreda-Tarrazona & Nikolaos Georgantzís & Constantine Manasakis & Evangelos Mitrokostas & Emmanuel Petrakis, 2012. "Managerial compensation contracts in quantity-setting duopoly," Working Papers 2012/17, Economics Department, Universitat Jaume I, Castellón (Spain).
    19. Zhou, Yuekuan & Zheng, Siqian, 2020. "Multi-level uncertainty optimisation on phase change materials integrated renewable systems with hybrid ventilations and active cooling," Energy, Elsevier, vol. 202(C).
    20. Clarke, Will Challis & Brear, Michael John & Manzie, Chris, 2020. "Control of an isolated microgrid using hierarchical economic model predictive control," Applied Energy, Elsevier, vol. 280(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3807-:d:1448593. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.