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Towards Collaborative Virtual Power Plants

  • Kankam O. Adu-KankamEmail author
  • Luis M. Camarinha-Matos
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 521)

Abstract

To promote flexible integration of distributed energy resources into the smart grid, the notion of Virtual Power Plants (VPPs) was proposed. VPPs are formed by the integration of heterogeneous systems, organizations and entities which collaborate to ensure optimal generation, distribution, storage, and sale of energy in the energy market. The collaborative nature of VPPs gives the semblance of collaborative business ecosystem, constituted of a mix of highly interdependent relationship among stakeholders. The systematic literature review methodology is used to summarize research evidence of emerging convergence between the Collaborative Networks (CN) and VPP domains. It is observed that, various strategic and dynamic collaborative alliances are formed within a VPP which are similar to various CN organizational forms like: Virtual Breeding Environments (VBE), grasping opportunity driven-networks etc. CN principles like: virtual organization creation, operation and dissolution, negotiation, broker services, etc., are also found. Emerging collaborative forms like hybrid collaborations between known traditional CN forms were also visible.

Keywords

Collaborative Networks Virtual Power Plants Distributed energy resources Energy market Smart grid 

Notes

Acknowledgement

This work was funded in part by the Center of Technology and Systems of Uninova and the Portuguese FCT-PEST program UID/EEA/00066/2013.

References

  1. 1.
    Kramer, O., Satzger, B., Lässig, J.: Managing energy in a virtual power plant using learning classifier systems. In: Proceedings of the 2010 International Conference on Genetic and Evolutionary Methods, GEM, pp. 111–117 (2010)Google Scholar
  2. 2.
    Lyberopoulos, G., Theodoropoulou, E., Mesogiti, I., Makris, P., Varvarigos, E.: A highly-dynamic and distributed operational framework for smart energy networks. In: 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD, pp. 120–124 (2014)Google Scholar
  3. 3.
    Camarinha-Matos, L.M., Afsarmanesh, H.: On reference models for collaborative networked organizations. Int. J. Prod. Res. 46(9), 2453–2469 (2008)CrossRefzbMATHGoogle Scholar
  4. 4.
    Kitchenham, B.: Procedures for performing systematic reviews. TR/SE-0401, NICTA Technical Report 0400011T.1 (2004). http://www.ifs.tuwien.ac.at/~weippl/systemicReviewsSoftwareEngineering.pdf. Accessed 10 Aug 2017
  5. 5.
    Petersen, K., Feldt, R., Mujtaba, S., Mattsson, M.: Systematic mapping studies in software engineering. In: 12th International Conference on Evaluation and Assessment in Software Engineering, EASE 2008, vol. 17, pp. 68–77 (2008)Google Scholar
  6. 6.
    Dethlefs, T., Preisler, T., Renz, W., Hamburg, H.A.W., Tor, B.: A DER registry system as an infrastructural component for future smart grid applications. In: Proceedings of International ETG Congress, Die Energiewende - Blueprints for the New Energy Age, pp. 93–99 (2015)Google Scholar
  7. 7.
    Botsis, V., Doulamis, N., Doulamis, A., Makris, P., Varvarigos, E.: Efficient clustering of DERs in a virtual association for profit optimization. In: Proceedings - 18th Euromicro Conference on Digital System Design, DSD, pp. 494–501 (2015)Google Scholar
  8. 8.
    Rinaldi, S., Pasetti, M., Ferrari, P., Massa, G., Della Giustina, D., Unareti, S.A.: Experimental characterization of communication infrastructure for virtual power plant monitoring. In: 2016 IEEE International Workshop on Applied Measurements for Power Systems (AMPS), pp. 1–6 (2016)Google Scholar
  9. 9.
    Huang, Y., Warnier, M., Brazier, F., Miorandi, D.: Social networking for smart grid users. A preliminary modeling and simulation study. In: IEEE 12th International Conference on Networking, Sensing and Control, pp. 438–443 (2015)Google Scholar
  10. 10.
    Biswas, S., Bagchi, D., Narahari, Y.: Mechanism design for sustainable virtual power plant formation. In: IEEE International Conference on Automation Science and Engineering, pp. 67–72 (2014)Google Scholar
  11. 11.
    Siebert, N., et al.: Reflexe: managing commercial and industrial flexibilities in a market environment. In: IEEE Grenoble Conference PowerTech, POWERTECH, pp. 1–6 (2013)Google Scholar
  12. 12.
    Baeyens, E., Bitar, E.Y., Khargonekar, P.P., Poolla, K.: Wind energy aggregation: a coalitional game approach. In: Proceedings of 50th IEEE Conference on Decision and Control and European Control Conference, pp. 3000–3007 (2011)Google Scholar
  13. 13.
    El Bakari, K., Kling, W.L.: Development and operation of virtual power plant system. In: 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), pp. 1–5 (2011)Google Scholar
  14. 14.
    Bakari, K.E., Kling, W.L.: Fitting distributed generation in future power markets through virtual power plants. In: 2012 9th International Conference on the European Energy Market, pp. 1–7 (2012)Google Scholar
  15. 15.
    Han, X., Bindner, H.W., Mehmedalic, J., Tackie, D.V.: Hybrid control scheme for distributed energy resource management in a market context. In: 2015 IEEE Power & Energy Society General Meeting, pp. 1–5 (2015)Google Scholar
  16. 16.
    Kamphuis, R., Wijbenga, J.P., Van Der Veen, J.S., Macdougall, P., Faeth, M.: DREAM: an ICT architecture framework for heterarchical coordination in power systems. In: 2015 IEEE Eindhoven PowerTech, POWERTECH, pp. 1–4 (2015)Google Scholar
  17. 17.
    Messinis, G., Dimeas, A., Hatziargyriou, N., Kokos, I., Lamprinos, I.: ICT tools for enabling smart grid players’ flexibility through VPP and DR services. In: 2016 13th International Conference on the European Energy Market (EEM), pp. 1–5 (2016)Google Scholar
  18. 18.
    Hernandez, L., et al.: A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants. IEEE Commu. Mag. 51(1), 106–113 (2013)CrossRefGoogle Scholar
  19. 19.
    Raju, L., Appaswamy, K., Vengatraman, J., Morais, A.A.: Advanced energy management in virtual power plant using multi agent system. In: 3rd International Conference on Electrical Energy Systems (ICEES), pp. 133–138 (2016)Google Scholar
  20. 20.
    Oliveira, P., Pinto, T., Morais, H.: MASGriP—a multi-agent smart grid simulation platform. In: Power and Energy Society General Meeting, pp. 1–8 (2012)Google Scholar
  21. 21.
    Vale, Z.A., Morais, H., Khodr, H.: Intelligent multi-player smart grid management considering distributed energy resources and demand response. In: 2010 IEEE Power and Energy Society General Meeting, pp. 1–7 (2010)Google Scholar
  22. 22.
    Zehir, M.A., Bagriyanik, M.: Smart energy aggregation network (SEAN): an advanced management system for using distributed energy resources in virtual power plant applications. In: 3rd International Istanbul Smart Grid Congress and Fair, ICSG 2015, pp. 1–4 (2015)Google Scholar
  23. 23.
    Fu, H., Wu, Z., Li, J., Zhang, X.: A configurable µVPP with managed energy services: a malmo western harbour case. IEEE Power Energy Technol. Syst. J. 3(4), 166–178 (2016).  https://doi.org/10.1109/JPETS.2016.2596779CrossRefGoogle Scholar
  24. 24.
    Brenna, M., Falvo, M.C., Foiadelli, F., Martirano, L., Poli, D.: From virtual power plant (VPP) to sustainable energy microsystem (SEM): an opportunity for buildings energy management. In: 2015 IEEE Industry Applications Society Annual Meeting, vol. 6, pp. 1–8 (2015)Google Scholar
  25. 25.
    Dagdougui, H., Ouammi, A., Sacile, R.: Distributed optimal control of a network of virtual power plants with dynamic price mechanism. In: Proceedings of the 8th Annual IEEE International Systems Conference, SysCon, pp. 24–29 (2014)Google Scholar
  26. 26.
    Morais, H., Pinto, T., Vale, Z., Praça, I.: Multilevel negotiation in smart grids for VPP management of distributed resources. IEEE Intell. Syst. 27(6), 8–16 (2012)CrossRefGoogle Scholar
  27. 27.
    Capodieci, N., Cabri, G.: Managing deregulated energy markets: an adaptive and autonomous multi-agent system application. In: Proceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013, pp. 758–763 (2013)Google Scholar
  28. 28.
    Spínola, J., Faria, P., Vale, Z.: Remuneration of distributed generation and demand response resources considering scheduling and aggregation. In: IEEE Power and Energy Society General Meeting, pp. 1–5 (2015)Google Scholar
  29. 29.
    Faria, P., João, S., Vale, Z.: Aggregation and remuneration of electricity consumers and producers for the definition of demand-response programs. IEEE Trans. Ind. Inform. 12(3), 952–961 (2016)CrossRefGoogle Scholar
  30. 30.
    Rahimiyan, M., Baringo, L.M.: Strategic bidding for a virtual power plant in the day-ahead and real-time markets: a price-taker robust optimization approach. IEEE Trans. Power Syst. 31(4), 2676–2687 (2016)CrossRefGoogle Scholar
  31. 31.
    Ribeiro, C., Pinto, T., Vale, Z.: Remuneration and tariffs in the context of virtual power players. In: Proceedings of the 23rd International Workshop on Database and Expert Systems Applications, pp. 308–312 (2012)Google Scholar
  32. 32.
    Ribeiro, C., Pinto, T., Morais, H., Vale, Z., Santos, G.: Intelligent remuneration and tariffs for virtual power players. In: 2013 IEEE Grenoble Conference PowerTech Towards Carbon Free Society Through Smarter Grids, POWERTECH, pp. 308–312 (2013)Google Scholar
  33. 33.
    Santos, G., Pinto, T., Vale, Z., Morais, H., Praca, I.: Balancing market integration in MASCEM electricity market simulator. In: Power and Energy Society General Meeting, pp. 1–8 (2012)Google Scholar
  34. 34.
    Enose, N.: Implementing an integrated security management framework to ensure a secure smart grid. In: Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI, pp. 778–784 (2014)Google Scholar
  35. 35.
    Farag, M.M., Azab, M., Mokhtar, B.: Cross-layer security framework for smart grid: physical security layer. In: IEEE PES Innovative Smart Grid Technologies, Europe, pp. 1–7 (2014)Google Scholar
  36. 36.
    Hittini, H., Abdrabou, A., Zhang, L.: SADSA: security aware distribution system architecture for smart grid applications. In: Proceedings of the 2016 12th International Conference on Innovations in Information Technology, IIT, pp. 1–6 (2016)Google Scholar
  37. 37.
    Sedjelmaci, H., Senouci, S.M.: Smart grid security: a new approach to detect intruders in a smart grid neighborhood area network. In: 2016 International Conference on Wireless Networks and Mobile Communications (WINCOM), pp. 6–11 (2016)Google Scholar
  38. 38.
    Liu, Y., Xin, H., Qu, Z., Gan, D.: An attack-resilient cooperative control strategy of multiple distributed generators in distribution networks. IEEE Trans. Smart Grid 7(6), 2923–2932 (2016)CrossRefGoogle Scholar
  39. 39.
    Qi, J., Hahn, A., Lu, X., Wang, J., Liu, C.: Cybersecurity for distributed energy resources and smart inverters. IET Cyber-Physical Syst. Theory Appl. 1(1), 28–39 (2016)CrossRefGoogle Scholar
  40. 40.
    Aydeger, A., Akkaya, K., Cintuglu, M.H., Uluagac, A.S., Mohammed, O.: Software defined networking for resilient communications in smart grid active distribution networks. In: 2016 IEEE International Conference on Communications (ICC), pp. 1–6 (2016)Google Scholar
  41. 41.
    Egbue, O., Naidu, D., Peterson, P.: The role of microgrids in enhancing macrogrid resilience. In: 2016 International Conference on Smart Grid and Clean Energy Technologies (ICSGCE), pp. 125–129 (2016)Google Scholar
  42. 42.
    Line, M.B., Tøndel, I.A., Jaatun, M.G.: Cyber security challenges in smart grids. In: 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), pp. 5–7 (2011)Google Scholar
  43. 43.
    Cowan, K.R., Daim, T.U.: Integrated technology roadmap development process: creating smart grid roadmaps to meet regional technology planning needs in oregon and the pacific northwest. In: Proceedings of PICMET 2012: Technology Management for Emerging Technologies, pp. 2871–2885 (2012)Google Scholar
  44. 44.
    Hahn, A., Govindarasu, M.: Cyber vulnerability disclosure policies for the smart grid. In: 2012 IEEE Power and Energy Society General Meeting, pp. 1–5 (2012)Google Scholar
  45. 45.
    Danekas, C.: Deriving business requirements from technology roadmaps to support ICT-architecture management. In: 2012 International Conference on Smart Grid Technology (SG-TEP), Economics and Policies, no. Section II, pp. 1–4 (2012)Google Scholar
  46. 46.
    Kilbourne, B., Bender, K.: Spectrum for smart grid: Policy recommendations enabling current and future applications. In: 2010 First IEEE International Conference on Smart Grid Communications, pp. 578–582 (2010)Google Scholar
  47. 47.
    Kim, J., Park, H.-I.: Policy directions for the smart grid in Korea. IEEE Power Energy Mag. 9(1), 40–49 (2011).  https://doi.org/10.1109/MPE.2010.939166CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.Faculty of Sciences and Technology, UNINOVA - CTSNova University of LisbonMonte CaparicaPortugal
  2. 2.School of EngineeringUniversity of Energy and Natural Resources (UENR)SunyaniGhana

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