IDEAS home Printed from https://ideas.repec.org/a/hin/complx/7494313.html

Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration

Author

Listed:
  • Marc Deissenroth
  • Martin Klein
  • Kristina Nienhaus
  • Matthias Reeg

Abstract

The ongoing deployment of renewable energy sources (RES) calls for an enhanced integration of RES into energy markets, accompanied by a new set of regulations. In Germany, for instance, the feed-in tariff legislation for renewables has been successively replaced by first optional and then obligatory marketing of RES on competitive wholesale markets. This paper introduces an agent-based model that allows studying the impact of changing energy policy instruments on the economic performance of RES operators and marketers. The model structure, its components, and linkages are presented in detail; an additional case study demonstrates the capability of our sociotechnical model. We find that changes in the political framework cannot be mapped directly to RES operators as behaviour of intermediary market actors has to be considered as well. Characteristics and strategies of intermediaries are thus an important factor for successful RES marketing and further deployment. It is shown that the model is able to assess the emergence and stability of market niches.

Suggested Citation

  • Marc Deissenroth & Martin Klein & Kristina Nienhaus & Matthias Reeg, 2017. "Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration," Complexity, Hindawi, vol. 2017, pages 1-24, December.
    • Handle: RePEc:hin:complx:7494313
    DOI: 10.1155/2017/7494313
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2017/7494313.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2017/7494313.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/7494313?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
    ---><---

    References listed on IDEAS

    as
    1. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-371, May.
    2. G. Fagiolo & C. Birchenhall & P. Windrum, 2007. "Empirical Validation in Agent-based Models: Introduction to the Special Issue," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 189-194, October.
    3. Geels, Frank W., 2002. "Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study," Research Policy, Elsevier, vol. 31(8-9), pages 1257-1274, December.
    4. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    5. Weiss, Olga & Bogdanov, Dmitry & Salovaara, Kaisa & Honkapuro, Samuli, 2017. "Market designs for a 100% renewable energy system: Case isolated power system of Israel," Energy, Elsevier, vol. 119(C), pages 266-277.
    6. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    7. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2014. "Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response," Applied Energy, Elsevier, vol. 126(C), pages 297-306.
    8. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-411, May.
    9. Li, Gong & Shi, Jing, 2012. "Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions," Applied Energy, Elsevier, vol. 99(C), pages 13-22.
    10. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    11. Bale, Catherine S.E. & Varga, Liz & Foxon, Timothy J., 2015. "Energy and complexity: New ways forward," Applied Energy, Elsevier, vol. 138(C), pages 150-159.
    12. De Giorgi, Maria Grazia & Ficarella, Antonio & Tarantino, Marco, 2011. "Error analysis of short term wind power prediction models," Applied Energy, Elsevier, vol. 88(4), pages 1298-1311, April.
    13. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo, 2008. "The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany," Energy Policy, Elsevier, vol. 36(8), pages 3076-3084, August.
    14. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    15. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    16. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    17. Yousefi, Shaghayegh & Moghaddam, Mohsen Parsa & Majd, Vahid Johari, 2011. "Optimal real time pricing in an agent-based retail market using a comprehensive demand response model," Energy, Elsevier, vol. 36(9), pages 5716-5727.
    18. van der Veen, Reinier A.C. & Abbasy, Alireza & Hakvoort, Rudi A., 2012. "Agent-based analysis of the impact of the imbalance pricing mechanism on market behavior in electricity balancing markets," Energy Economics, Elsevier, vol. 34(4), pages 874-881.
    19. W. Brian Arthur, 1994. "Inductive Reasoning, Bounded Rationality and the Bar Problem," Working Papers 94-03-014, Santa Fe Institute.
    20. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    21. Richstein, Jörn C. & Chappin, Emile J.L. & de Vries, Laurens J., 2014. "Cross-border electricity market effects due to price caps in an emission trading system: An agent-based approach," Energy Policy, Elsevier, vol. 71(C), pages 139-158.
    22. Sorda, G. & Sunak, Y. & Madlener, R., 2013. "An agent-based spatial simulation to evaluate the promotion of electricity from agricultural biogas plants in Germany," Ecological Economics, Elsevier, vol. 89(C), pages 43-60.
    23. Wassermann, Sandra & Reeg, Matthias & Nienhaus, Kristina, 2015. "Current challenges of Germany’s energy transition project and competing strategies of challengers and incumbents: The case of direct marketing of electricity from renewable energy sources," Energy Policy, Elsevier, vol. 76(C), pages 66-75.
    24. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    25. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    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. Ulrich J. Frey & Martin Klein & Kristina Nienhaus & Christoph Schimeczek, 2020. "Self-Reinforcing Electricity Price Dynamics under the Variable Market Premium Scheme," Energies, MDPI, vol. 13(20), pages 1-19, October.
    2. Chun Wei & Xiangzhi Xu & Youbing Zhang & Xiangshan Li, 2019. "A Survey on Optimal Control and Operation of Integrated Energy Systems," Complexity, Hindawi, vol. 2019, pages 1-14, December.
    3. Rémi Delage & Toshihiko Nakata, 2022. "Multivariate Empirical Mode Decomposition and Recurrence Quantification for the Multiscale, Spatiotemporal Analysis of Electricity Demand—A Case Study of Japan," Energies, MDPI, vol. 15(17), pages 1-17, August.
    4. Kyungjin Yoo & Seth Blumsack, 2018. "The Political Complexity of Regional Electricity Policy Formation," Complexity, Hindawi, vol. 2018, pages 1-18, December.
    5. Li, Pei-Hao & Barazza, Elsa & Strachan, Neil, 2022. "The influences of non-optimal investments on the scale-up of smart local energy systems in the UK electricity market," Energy Policy, Elsevier, vol. 170(C).
    6. Majidi, Hassan & Hayati, Mohammad Mohsen & Breyer, Christian & Mohammadi-ivatloo, Behnam & Honkapuro, Samuli & Karjunen, Hannu & Laaksonen, Petteri & Sihvonen, Ville, 2025. "Overview of energy modeling requirements and tools for future smart energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    7. Mason, Karl & Qadrdan, Meysam & Jenkins, Nicholas, 2021. "Investing in generation and storage capacity in a liberalised electricity market: An agent based approach," Applied Energy, Elsevier, vol. 294(C).
    8. Aco Benović & Miroslav Miškić & Vladan Pantović & Slađana Vujičić & Dejan Vidojević & Mladen Opačić & Filip Jovanović, 2025. "Assessment of the Impact of Solar Power Integration and AI Technologies on Sustainable Local Development: A Case Study from Serbia," Sustainability, MDPI, vol. 17(15), pages 1-23, July.
    9. Torralba-Díaz, Laura & Schimeczek, Christoph & Kochems, Johannes & Hufendiek, Kai, 2024. "Iterative coupling of a fundamental electricity market model and an agent-based simulation model to reduce the efficiency gap," Energy, Elsevier, vol. 310(C).
    10. Sergio Velázquez Medina & José A. Carta & Ulises Portero Ajenjo, 2019. "Performance Sensitivity of a Wind Farm Power Curve Model to Different Signals of the Input Layer of ANNs: Case Studies in the Canary Islands," Complexity, Hindawi, vol. 2019, pages 1-11, March.
    11. Fraunholz, Christoph & Kraft, Emil & Keles, Dogan & Fichtner, Wolf, 2021. "Advanced price forecasting in agent-based electricity market simulation," Applied Energy, Elsevier, vol. 290(C).
    12. Laura Torralba-Díaz & Christoph Schimeczek & Matthias Reeg & Georgios Savvidis & Marc Deissenroth-Uhrig & Felix Guthoff & Benjamin Fleischer & Kai Hufendiek, 2020. "Identification of the Efficiency Gap by Coupling a Fundamental Electricity Market Model and an Agent-Based Simulation Model," Energies, MDPI, vol. 13(15), pages 1-19, July.
    13. Nitsch, Felix & Deissenroth-Uhrig, Marc & Schimeczek, Christoph & Bertsch, Valentin, 2021. "Economic evaluation of battery storage systems bidding on day-ahead and automatic frequency restoration reserves markets," Applied Energy, Elsevier, vol. 298(C).
    14. Anwar, Muhammad Bashar & Stephen, Gord & Dalvi, Sourabh & Frew, Bethany & Ericson, Sean & Brown, Maxwell & O’Malley, Mark, 2022. "Modeling investment decisions from heterogeneous firms under imperfect information and risk in wholesale electricity markets," Applied Energy, Elsevier, vol. 306(PA).
    15. Barazza, Elsa & Strachan, Neil, 2020. "The impact of heterogeneous market players with bounded-rationality on the electricity sector low-carbon transition," Energy Policy, Elsevier, vol. 138(C).
    16. Maciej Ławryńczuk, 2018. "Towards Reduced-Order Models of Solid Oxide Fuel Cell," Complexity, Hindawi, vol. 2018, pages 1-18, July.
    17. Amir Ali Safaei Pirooz & Mohammad J. Sanjari & Young-Jin Kim & Stuart Moore & Richard Turner & Wayne W. Weaver & Dipti Srinivasan & Josep M. Guerrero & Mohammad Shahidehpour, 2023. "Adaptation of High Spatio-Temporal Resolution Weather/Load Forecast in Real-World Distributed Energy-System Operation," Energies, MDPI, vol. 16(8), pages 1-16, April.

    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. Furtado, Bernardo Alves & Eberhardt, Isaque Daniel Rocha, 2015. "Modelo espacial simples da economia: uma proposta teórico-metodológica [A simple spatial economic model: a proposal]," MPRA Paper 67005, University Library of Munich, Germany.
    2. Bernardo Alves Furtado & Isaque Daniel Rocha Eberhardt, 2016. "A Simple Agent-Based Spatial Model of the Economy: Tools for Policy," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-12.
    3. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    4. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    5. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2020. "Climate change and green transitions in an agent-based integrated assessment model," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    6. Niamir, Leila & Filatova, Tatiana & Voinov, Alexey & Bressers, Hans, 2018. "Transition to low-carbon economy: Assessing cumulative impacts of individual behavioral changes," Energy Policy, Elsevier, vol. 118(C), pages 325-345.
    7. Li, Pei-Hao & Barazza, Elsa & Strachan, Neil, 2022. "The influences of non-optimal investments on the scale-up of smart local energy systems in the UK electricity market," Energy Policy, Elsevier, vol. 170(C).
    8. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2019. "A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda," Contributions of the Institute for Infrastructure and Resources Management 01/2019, University of Leipzig, Institute for Infrastructure and Resources Management.
    9. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    10. Auke Hoekstra & Maarten Steinbuch & Geert Verbong, 2017. "Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation," Complexity, Hindawi, vol. 2017, pages 1-23, December.
    11. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046, January.
    12. Nan Lu, 2018. "La modélisation de l’indice CAC 40 avec un modèle basé agent," Erudite Ph.D Dissertations, Erudite, number ph18-02 edited by François Legendre, December.
    13. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    14. Klaus Wersching, 2010. "Schumpeterian Competition, Technological Regimes and Learning through Knowledge Spillover," Post-Print hal-00849408, HAL.
    15. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    16. Santiago J. Gangotena, 2017. "Dynamic coordinating non-equilibrium," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 30(1), pages 51-82, March.
    17. Tesfatsion, Leigh, 2017. "Modeling Economic Systems as Locally-Constructive Sequential Games," ISU General Staff Papers 201704300700001022, Iowa State University, Department of Economics.
    18. Adão, Luiz F.S. & Silveira, Douglas & Ely, Regis A. & Cajueiro, Daniel O., 2022. "The impacts of interest rates on banks’ loan portfolio risk-taking," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    19. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    20. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:7494313. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.