IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i10p1449-d112722.html
   My bibliography  Save this article

A Scatter Search Heuristic for the Optimal Location, Sizing and Contract Pricing of Distributed Generation in Electric Distribution Systems

Author

Listed:
  • Andrés Felipe Pérez Posada

    (Celsia S.A. E.S.P., Carrera 43A No. 1sur-143, Medellín 050022, Colombia)

  • Juan G. Villegas

    (Supply Chains Management and Innovation Research Group (INCAS), Department of Industrial Engineering, Universidad de Antioquia, 67th Street, No. 53-108, Medellín 050110, Colombia)

  • Jesús M. López-Lezama

    (Research Group in Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia, 67th Street, No. 53-108, Medellín 050110, Colombia)

Abstract

In this paper we present a scatter search (SS) heuristic for the optimal location, sizing and contract pricing of distributed generation (DG) in electric distribution systems. The proposed optimization approach considers the interaction of two agents: (i) the potential investor and owner of the DG, and (ii) the Distribution Company (DisCo) in charge of the operation of the network. The DG owner seeks to maximize his profits from selling energy to the DisCo, while the DisCo aims at minimizing the cost of serving the network demand, while meeting network constraints. To serve the expected demand the DisCo is able to purchase energy, through long-term bilateral contracts, from the wholesale electricity market and from the DG units within the network. The interaction of both agents leads to a bilevel programming problem that we solve through a SS heuristic. Computational experiments show that SS outperforms a genetic algorithm hybridized with local search both in terms of solution quality and computational time.

Suggested Citation

  • Andrés Felipe Pérez Posada & Juan G. Villegas & Jesús M. López-Lezama, 2017. "A Scatter Search Heuristic for the Optimal Location, Sizing and Contract Pricing of Distributed Generation in Electric Distribution Systems," Energies, MDPI, vol. 10(10), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1449-:d:112722
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/10/1449/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/10/1449/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marti, Rafael & Laguna, Manuel & Glover, Fred, 2006. "Principles of scatter search," European Journal of Operational Research, Elsevier, vol. 169(2), pages 359-372, March.
    2. Colmenar-Santos, Antonio & Reino-Rio, Cipriano & Borge-Diez, David & Collado-Fernández, Eduardo, 2016. "Distributed generation: A review of factors that can contribute most to achieve a scenario of DG units embedded in the new distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1130-1148.
    3. Hyun-Koo Kang & Il-Yop Chung & Seung-Il Moon, 2015. "Voltage Control Method Using Distributed Generators Based on a Multi-Agent System," Energies, MDPI, vol. 8(12), pages 1-17, December.
    4. Prakash, Prem & Khatod, Dheeraj K., 2016. "Optimal sizing and siting techniques for distributed generation in distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 111-130.
    5. Hao Bai & Shihong Miao & Pipei Zhang & Zhan Bai, 2015. "Reliability Evaluation of a Distribution Network with Microgrid Based on a Combined Power Generation System," Energies, MDPI, vol. 8(2), pages 1-26, February.
    6. Hao Liang & Weihua Zhuang, 2014. "Stochastic Modeling and Optimization in a Microgrid: A Survey," Energies, MDPI, vol. 7(4), pages 1-24, March.
    7. Anna Rita Di Fazio & Mario Russo & Sara Valeri & Michele De Santis, 2016. "Sensitivity-Based Model of Low Voltage Distribution Systems with Distributed Energy Resources," Energies, MDPI, vol. 9(10), pages 1-16, October.
    8. Yazhou Jiang & Chen-Ching Liu & Yin Xu, 2016. "Smart Distribution Systems," Energies, MDPI, vol. 9(4), pages 1-20, April.
    9. Zsolt Ugray & Leon Lasdon & John Plummer & Fred Glover & James Kelly & Rafael Martí, 2007. "Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization," INFORMS Journal on Computing, INFORMS, vol. 19(3), pages 328-340, August.
    10. Colak, Ilhami & Sagiroglu, Seref & Fulli, Gianluca & Yesilbudak, Mehmet & Covrig, Catalin-Felix, 2016. "A survey on the critical issues in smart grid technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 396-405.
    11. Beasley, J. E. & Chu, P. C., 1996. "A genetic algorithm for the set covering problem," European Journal of Operational Research, Elsevier, vol. 94(2), pages 392-404, October.
    12. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
    13. de Athayde Costa e Silva, Marsil & Klein, Carlos Eduardo & Mariani, Viviana Cocco & dos Santos Coelho, Leandro, 2013. "Multiobjective scatter search approach with new combination scheme applied to solve environmental/economic dispatch problem," Energy, Elsevier, vol. 53(C), pages 14-21.
    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. Pavlos S. Georgilakis, 2020. "Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Researc," Energies, MDPI, vol. 13(1), pages 1-37, January.
    2. Matheus Diniz Gonçalves-Leite & Edgar Manuel Carreño-Franco & Jesús M. López-Lezama, 2023. "Impact of Distributed Generation on the Effectiveness of Electric Distribution System Reconfiguration," Energies, MDPI, vol. 16(17), pages 1-20, August.
    3. Hun Mun & Byunghoon Moon & Soojin Park & Yongbeum Yoon, 2021. "A Study on the Economic Feasibility of Stand-Alone Microgrid for Carbon-Free Island in Korea," Energies, MDPI, vol. 14(7), pages 1-16, March.
    4. Luis A. Gallego Pareja & Jesús M. López-Lezama & Oscar Gómez Carmona, 2023. "A MILP Model for Optimal Conductor Selection and Capacitor Banks Placement in Primary Distribution Systems," Energies, MDPI, vol. 16(11), pages 1-21, May.
    5. Luis A. Gallego Pareja & Jesús M. López-Lezama & Oscar Gómez Carmona, 2022. "A Mixed-Integer Linear Programming Model for the Simultaneous Optimal Distribution Network Reconfiguration and Optimal Placement of Distributed Generation," Energies, MDPI, vol. 15(9), pages 1-26, April.
    6. José R. Ortiz-Castrillón & Sergio D. Saldarriaga-Zuluaga & Nicolás Muñoz-Galeano & Jesús M. López-Lezama & Santiago Benavides-Córdoba & Juan B. Cano-Quintero, 2023. "Optimal Sliding-Mode Control of Semi-Bridgeless Boost Converters Considering Power Factor Corrections," Energies, MDPI, vol. 16(17), pages 1-24, August.
    7. Wallisson C. Nogueira & Lina P. Garcés Negrete & Jesús M. López-Lezama, 2023. "Optimal Allocation and Sizing of Distributed Generation Using Interval Power Flow," Sustainability, MDPI, vol. 15(6), pages 1-24, March.

    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. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    2. Gianpiero Colangelo & Gianluigi Spirto & Marco Milanese & Arturo de Risi, 2021. "Progresses in Analytical Design of Distribution Grids and Energy Storage," Energies, MDPI, vol. 14(14), pages 1-43, July.
    3. Kakran, Sandeep & Chanana, Saurabh, 2018. "Smart operations of smart grids integrated with distributed generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 524-535.
    4. Anestis, Anastasiadis & Georgios, Vokas, 2019. "Economic benefits of Smart Microgrids with penetration of DER and mCHP units for non-interconnected islands," Renewable Energy, Elsevier, vol. 142(C), pages 478-486.
    5. Ehsan, Ali & Yang, Qiang, 2018. "Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques," Applied Energy, Elsevier, vol. 210(C), pages 44-59.
    6. Luis Fernando Grisales-Noreña & Daniel Gonzalez Montoya & Carlos Andres Ramos-Paja, 2018. "Optimal Sizing and Location of Distributed Generators Based on PBIL and PSO Techniques," Energies, MDPI, vol. 11(4), pages 1-27, April.
    7. Mehigan, L. & Deane, J.P. & Gallachóir, B.P.Ó. & Bertsch, V., 2018. "A review of the role of distributed generation (DG) in future electricity systems," Energy, Elsevier, vol. 163(C), pages 822-836.
    8. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
    9. Gustavo L. Aschidamini & Gederson A. da Cruz & Mariana Resener & Maicon J. S. Ramos & Luís A. Pereira & Bibiana P. Ferraz & Sérgio Haffner & Panos M. Pardalos, 2022. "Expansion Planning of Power Distribution Systems Considering Reliability: A Comprehensive Review," Energies, MDPI, vol. 15(6), pages 1-29, March.
    10. Panagiotis Michalitsakos & Lucian Mihet-Popa & George Xydis, 2017. "A Hybrid RES Distributed Generation System for Autonomous Islands: A DER-CAM and Storage-Based Economic and Optimal Dispatch Analysis," Sustainability, MDPI, vol. 9(11), pages 1-16, November.
    11. Pesaran H.A., Mahmoud & Nazari-Heris, Morteza & Mohammadi-Ivatloo, Behnam & Seyedi, Heresh, 2020. "A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks," Energy, Elsevier, vol. 209(C).
    12. Ying-Yi Hong, 2016. "Electric Power Systems Research," Energies, MDPI, vol. 9(10), pages 1-4, October.
    13. Schmeling, Lucas & Schönfeldt, Patrik & Klement, Peter & Vorspel, Lena & Hanke, Benedikt & von Maydell, Karsten & Agert, Carsten, 2022. "A generalised optimal design methodology for distributed energy systems," Renewable Energy, Elsevier, vol. 200(C), pages 1223-1239.
    14. Noordhoek, Marije & Dullaert, Wout & Lai, David S.W. & de Leeuw, Sander, 2018. "A simulation–optimization approach for a service-constrained multi-echelon distribution network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 292-311.
    15. Guido C. Guerrero-Liquet & Santiago Oviedo-Casado & J. M. Sánchez-Lozano & M. Socorro García-Cascales & Javier Prior & Antonio Urbina, 2018. "Determination of the Optimal Size of Photovoltaic Systems by Using Multi-Criteria Decision-Making Methods," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    16. Coslovich, Luca & Pesenti, Raffaele & Ukovich, Walter, 2006. "Minimizing fleet operating costs for a container transportation company," European Journal of Operational Research, Elsevier, vol. 171(3), pages 776-786, June.
    17. Anurag Agarwal, 2009. "Theoretical insights into the augmented-neural-network approach for combinatorial optimization," Annals of Operations Research, Springer, vol. 168(1), pages 101-117, April.
    18. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    19. Avilés A., Camilo & Oliva H., Sebastian & Watts, David, 2019. "Single-dwelling and community renewable microgrids: Optimal sizing and energy management for new business models," Applied Energy, Elsevier, vol. 254(C).
    20. Rita Portugal & Helena Ramalhinho-Lourenço & José P. Paixao, 2006. "Driver scheduling problem modelling," Economics Working Papers 991, Department of Economics and Business, Universitat Pompeu Fabra.

    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:10:y:2017:i:10:p:1449-:d:112722. 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.