IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v111y2016icp513-524.html
   My bibliography  Save this article

MASCEM: Optimizing the performance of a multi-agent system

Author

Listed:
  • Santos, Gabriel
  • Pinto, Tiago
  • Praça, Isabel
  • Vale, Zita

Abstract

The electricity market sector has suffered massive changes in the last few decades. The worldwide electricity market restructuring has been conducted to potentiate the increase in competitiveness and thus decrease electricity prices. However, the complexity in this sector has grown significantly as well, with the emergence of several new types of players, interacting in a constantly changing environment. Several electricity market simulators have been introduced in recent years with the purpose of supporting operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents a new, enhanced version of MASCEM (Multi-Agent System for Competitive Electricity Markets), an electricity market simulator with over ten years of existence, which had to be restructured in order to be able to face the highly demanding requirements that the decision support in this field requires. This restructuring optimizes the performance of MASCEM, both in results and execution time.

Suggested Citation

  • Santos, Gabriel & Pinto, Tiago & Praça, Isabel & Vale, Zita, 2016. "MASCEM: Optimizing the performance of a multi-agent system," Energy, Elsevier, vol. 111(C), pages 513-524.
    • Handle: RePEc:eee:energy:v:111:y:2016:i:c:p:513-524
    DOI: 10.1016/j.energy.2016.05.127
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216307654
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.05.127?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Hongyan & Tesfatsion, Leigh, 2009. "Development of Open Source Software for Power Market Research: The AMES Test Bed," ISU General Staff Papers 200901010800001391, Iowa State University, Department of Economics.
    2. Canizes, Bruno & Soares, João & Faria, Pedro & Vale, Zita, 2013. "Mixed integer non-linear programming and Artificial Neural Network based approach to ancillary services dispatch in competitive electricity markets," Applied Energy, Elsevier, vol. 108(C), pages 261-270.
    3. Meeus, Leonardo & Purchala, Konrad & Belmans, Ronnie, 2005. "Development of the Internal Electricity Market in Europe," The Electricity Journal, Elsevier, vol. 18(6), pages 25-35, July.
    4. Pinto, T. & Morais, H. & Oliveira, P. & Vale, Z. & Praça, I. & Ramos, C., 2011. "A new approach for multi-agent coalition formation and management in the scope of electricity markets," Energy, Elsevier, vol. 36(8), pages 5004-5015.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Silva, Francisco & Teixeira, Brígida & Pinto, Tiago & Santos, Gabriel & Vale, Zita & Praça, Isabel, 2016. "Generation of realistic scenarios for multi-agent simulation of electricity markets," Energy, Elsevier, vol. 116(P1), pages 128-139.
    2. Veiga, Bruno & Santos, Gabriel & Pinto, Tiago & Faia, Ricardo & Ramos, Carlos & Vale, Zita, 2023. "Simulation tools for electricity markets considering power flow analysis," Energy, Elsevier, vol. 275(C).
    3. Gabriel Santos & Tiago Pinto & Isabel Praça & Zita Vale, 2016. "An Interoperable Approach for Energy Systems Simulation: Electricity Market Participation Ontologies," Energies, MDPI, vol. 9(11), pages 1-22, October.
    4. Chen, Peipei & Wu, Yi & Zou, Lele, 2019. "Distributive PV trading market in China: A design of multi-agent-based model and its forecast analysis," Energy, Elsevier, vol. 185(C), pages 423-436.
    5. Gabriel Santos & Pedro Faria & Zita Vale & Tiago Pinto & Juan M. Corchado, 2020. "Constrained Generation Bids in Local Electricity Markets: A Semantic Approach," Energies, MDPI, vol. 13(15), pages 1-27, August.
    6. Alfonso González-Briones & Fernando De La Prieta & Mohd Saberi Mohamad & Sigeru Omatu & Juan M. Corchado, 2018. "Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review," Energies, MDPI, vol. 11(8), pages 1-28, July.
    7. Claudio Monteiro & L. Alfredo Fernandez-Jimenez & Ignacio J. Ramirez-Rosado, 2020. "Predictive Trading Strategy for Physical Electricity Futures," Energies, MDPI, vol. 13(14), pages 1-24, July.
    8. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    9. Davarzani, Sima & Granell, Ramon & Taylor, Gareth A. & Pisica, Ioana, 2019. "Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    10. Hugo Morais & Tiago Pinto & Zita Vale, 2020. "Adjacent Markets Influence Over Electricity Trading—Iberian Benchmark Study," Energies, MDPI, vol. 13(11), pages 1-22, June.

    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. Pinto, Tiago & Vale, Zita & Sousa, Tiago M. & Praça, Isabel, 2015. "Negotiation context analysis in electricity markets," Energy, Elsevier, vol. 85(C), pages 78-93.
    2. Gabriel Santos & Tiago Pinto & Isabel Praça & Zita Vale, 2016. "An Interoperable Approach for Energy Systems Simulation: Electricity Market Participation Ontologies," Energies, MDPI, vol. 9(11), pages 1-22, October.
    3. Pinto, T. & Morais, H. & Oliveira, P. & Vale, Z. & Praça, I. & Ramos, C., 2011. "A new approach for multi-agent coalition formation and management in the scope of electricity markets," Energy, Elsevier, vol. 36(8), pages 5004-5015.
    4. Tiago Pinto & Zita Vale & Isabel Praça & E. J. Solteiro Pires & Fernando Lopes, 2015. "Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning," Energies, MDPI, vol. 8(9), pages 1-26, September.
    5. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    6. Veith, Stefan & Werner, Jörg R. & Zimmermann, Jochen, 2009. "Capital market response to emission rights returns: Evidence from the European power sector," Energy Economics, Elsevier, vol. 31(4), pages 605-613, July.
    7. Krishnamurthy, Dheepak & Li, Wanning & Tesfatsion, Leigh, 2016. "An 8-Zone Test System Based on ISO New England Data: Development and Application," ISU General Staff Papers 201601010800001449, Iowa State University, Department of Economics.
    8. Tadahiro Taniguchi & Koki Kawasaki & Yoshiro Fukui & Tomohiro Takata & Shiro Yano, 2015. "Automated Linear Function Submission-Based Double Auction as Bottom-up Real-Time Pricing in a Regional Prosumers’ Electricity Network," Energies, MDPI, vol. 8(7), pages 1-26, July.
    9. Li, Hongyan & Tesfatsion, Leigh, 2012. "Co-learning patterns as emergent market phenomena: An electricity market illustration," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 395-419.
    10. Goudarzi, Arman & Swanson, Andrew G. & Van Coller, John & Siano, Pierluigi, 2017. "Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators," Applied Energy, Elsevier, vol. 189(C), pages 667-696.
    11. Hosseini, Seyyed Ahmad & Toubeau, Jean-François & De Grève, Zacharie & Vallée, François, 2020. "An advanced day-ahead bidding strategy for wind power producers considering confidence level on the real-time reserve provision," Applied Energy, Elsevier, vol. 280(C).
    12. Adriaan Weijde & Benjamin Hobbs, 2011. "Locational-based coupling of electricity markets: benefits from coordinating unit commitment and balancing markets," Journal of Regulatory Economics, Springer, vol. 39(3), pages 223-251, June.
    13. Mauro Lafratta & Matthew Leach & Rex B. Thorpe & Mark Willcocks & Eve Germain & Sabeha K. Ouki & Achame Shana & Jacquetta Lee, 2021. "Economic and Carbon Costs of Electricity Balancing Services: The Need for Secure Flexible Low-Carbon Generation," Energies, MDPI, vol. 14(16), pages 1-21, August.
    14. Tiago Pinto & Mohammad Ali Fotouhi Ghazvini & Joao Soares & Ricardo Faia & Juan Manuel Corchado & Rui Castro & Zita Vale, 2018. "Decision Support for Negotiations among Microgrids Using a Multiagent Architecture," Energies, MDPI, vol. 11(10), pages 1-20, September.
    15. Kim, Seunghyok & Koo, Jamin & Lee, Chang Jun & Yoon, En Sup, 2012. "Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors," Energy, Elsevier, vol. 44(1), pages 126-134.
    16. Domanico, Fabio, 2007. "Concentration in the European electricity industry: The internal market as solution?," Energy Policy, Elsevier, vol. 35(10), pages 5064-5076, October.
    17. Roman Vavrek & Jana Chovancová, 2020. "Energy Performance of the European Union Countries in Terms of Reaching the European Energy Union Objectives," Energies, MDPI, vol. 13(20), pages 1-16, October.
    18. Hugo Morais & Tiago Pinto & Zita Vale, 2020. "Adjacent Markets Influence Over Electricity Trading—Iberian Benchmark Study," Energies, MDPI, vol. 13(11), pages 1-22, June.
    19. Van den Bergh, Kenneth & Bruninx, Kenneth & Delarue, Erik, 2018. "Cross-border reserve markets: network constraints in cross-border reserve procurement," Energy Policy, Elsevier, vol. 113(C), pages 193-205.
    20. Ricardo Faia & Tiago Pinto & Zita Vale & Juan Manuel Corchado, 2017. "An Ad-Hoc Initial Solution Heuristic for Metaheuristic Optimization of Energy Market Participation Portfolios," Energies, MDPI, vol. 10(7), pages 1-18, June.

    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:eee:energy:v:111:y:2016:i:c:p:513-524. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.