Bilevel programming; Community microgrid; Energy market; Marginal pricing
Abstract :
[en] This work fits in the context of community microgrids, where members of a community can exchange energy and services among themselves, without going through the usual channels of the public electricity grid. We introduce and analyze a framework to operate a community microgrid, and to share the resulting revenues and costs among its members. A market-oriented pricing of energy exchanges within the community is obtained by implementing an internal local market based on the marginal pricing scheme. The market aims at maximizing the social welfare of the community, thanks to the more efficient allocation of resources, the reduction of the peak power to be paid, and the increased amount of reserve, achieved at an aggregate level. A community microgrid operator, acting as a benevolent planner, redistributes revenues and costs among the members, in such a way that the solution achieved by each member within the community is not worse than the solution it would achieve by acting individually. In this way, each member is incentivized to participate in the community on a voluntary basis. The overall framework is formulated in the form of a bilevel model, where the lower level problem clears the market, while the upper level problem plays the role of the community microgrid operator. Numerical results obtained on a real test case implemented in Belgium show around 54% cost savings on a yearly scale for the community, as compared to the case when its members act individually.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Cornélusse, Bertrand ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Smart-Microgrids
Savelli, Iacopo; Dipartimento di Ingegneria dell'Informazione e Scienze Matematiche, Università di Siena, Italy
Paoletti, Simone; Dipartimento di Ingegneria dell'Informazione e Scienze Matematiche, Università di Siena, Italy
Giannitrapani, Antonio; Dipartimento di Ingegneria dell'Informazione e Scienze Matematiche, Università di Siena, Italy
Vicino, Antonio; Dipartimento di Ingegneria dell'Informazione e Scienze Matematiche, Università di Siena, Italy
Language :
English
Title :
A community microgrid architecture with an internal local market
Morales, J.M., Conejo, A.J., Madsen, H., Pinson, P., Zugno, M., Integrating renewables in electricity markets. Int series in operations research & management science, vol. 205, 2014, Springer, New-York.
Hatziargyriou, N., (eds.) Microgrids: architectures and control, 2014, John Wiley and Sons, Chichester, UK.
Hirsch, A., Parag, Y., Guerrero, J., Microgrids: a review of technologies, key drivers, and outstanding issues. Renew Sustain Energy Rev 90 (2018), 402–411.
Mengelkamp, E., Gärttner, J., Rock, K., Kessler, S., Orsini, L., Weinhardt, C., Designing microgrid energy markets: a case study: the Brooklyn microgrid. Appl Energy 210 (2018), 870–880.
Khazaei, H., Zhao, Y., Indirect mechanism design for efficient and stable renewable energy aggregation. IEEE Trans Power Syst, 2018, 1–12 Early access.
Quashie, M., Marnay, C., Bouffard, F., Joós, G., Optimal planning of microgrid power and operating reserve capacity. Appl Energy 210 (2018), 1229–1236.
Liu, N., Yu, X., Wang, C., Li, C., Ma, L., Lei, J., Energy-sharing model with price-based demand response for microgrids of peer-to-peer prosumers. IEEE Trans Power Syst 32:5 (2017), 3569–3583.
Parag, Y., Sovacool, B.K., Electricity market design for the prosumer era. Nat Energy 1 (2016), 1–6.
Olivier, F., Marulli, D., Ernst, D., Fonteneau, R., Foreseeing new control challenges in electricity prosumer communities. Proc of 10th bulk power systems dynamics and control symposium, 2017, 1–8.
Cazalet E, De Martini P, Price J, Woychik E, Caldwell J. Transactive energy models, [Online]. Available: [accessed Jan. 4, 2019]; Sep 2016.
Zhao, Y., Solar energy sharing in net metered community microgrids: can the social goals be achieved?. Proc. of 52nd annual conference on information sciences and systems, 2018, 1–6.
Zhang, D., Samsatli, N.J., Hawkes, A.D., Brett, D.J.L., Shah, N., Papageorgiou, L.G., Fair electricity transfer price and unit capacity selection for microgrids. Energy Econ 36 (2013), 581–593.
Moret, F., Pinson, P., Energy collectives: a community and fairness based approach to future electricity markets. IEEE Trans Power Syst, 2018, 1–11 early access.
Lüth, A., Zepter, J.M., del Granado, P.C., Egging, R., Local electricity market designs for peer-to-peer trading: the role of battery flexibility. Appl Energy 229 (2018), 1233–1243.
Del Granado, P.C., Pang, Z., Wallace, S.W., Synergy of smart grids and hybrid distributed generation on the value of energy storage. Appl Energy 170 (2016), 476–488.
van der Stelt, S., AlSkaif, T., van Sark, W., Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances. Appl Energy 209 (2018), 266–276.
Barbour, E., Parra, D., Awwad, Z., González, M.C., Community energy storage: a smart choice for the smart grid?. Appl Energy 212 (2018), 489–497.
Ma, X., Wang, Y., Qin, J., Generic model of a community-based microgrid integrating wind turbines, photovoltaics and CHP generations. Appl Energy 112 (2013), 1475–1482.
Xu, X., Jin, X., Jia, H., Yu, X., Li, K., Hierarchical management for integrated community energy systems. Appl Energy 160 (2015), 231–243.
Bohman, M., Andersson, R., Pricing cogenerated electricity and heat in local communities. J Public Econ 33:3 (1987), 333–356.
Schweppe, F.C., Caraminis, M.C., Tabors, R.O., Bohn, R., Spot pricing of electricity. 1988, Kluwer Academic Publishers, Norwell, MA.
Caramanis, M.C., Bohn, R.E., Schweppe, F.C., Optimal spot pricing: practice and theory. IEEE Trans Power Appar Syst 101:9 (1982), 3234–3245.
Mas-Colell, A., Whinston, M.D., Green, J.R., Microeconomic theory. 1995, Oxford University Press, New York.
Biggar, D.R., Hesamzadeh, M.R., The economics of electricity markets. 2014, John Wiley & Sons, Chichester, UK.
Cornélusse, B., Ernst, D., Warichet, L., Legros, W., Efficient management of a connected microgrid in Belgium. CIRED - Open Access Proc J 2017:1 (2017), 1729–1732.
Bard, J.F., Practical bilevel optimization: algorithms and applications. Nonconvex optimization and its applications, vol. 30, 1998, Springer, Boston, MA.
Sinha, A., Malo, P., Deb, K., A review on bilevel optimization: from classical to evolutionary approaches and applications. IEEE Trans Evol Comput 22:2 (2018), 276–295.
Gabriel, S.A., Conejo, A.J., Fuller, J.D., Hobbs, B.F., Ruiz, C., Complementarity modeling in energy markets. Int series in operations research & management science, vol. 180, 2013, Springer-Verlag, New York.
Fernández-Blanco, R., Arroyo, J.M., Alguacil, N., Consumer payment minimization under uniform pricing: a mixed-integer linear programming approach. Appl Energy 114 (2014), 676–686.
Feijoo, F., Das, T.K., Design of Pareto optimal CO2 cap-and-trade policies for deregulated electricity networks. Appl Energy 119 (2014), 371–383.
Savelli, I., Cornélusse, B., Giannitrapani, A., Paoletti, S., Vicino, A., A new approach to electricity market clearing with uniform purchase price and curtailable block orders. Appl Energy 226 (2018), 618–630.
Litvinov, E., Design and operation of the locational marginal prices-based electricity markets. IET Gener, Transmiss Distrib 4:2 (2010), 315–323.
Mangasarian, O.L., Uniqueness of solution in linear programming. Linear Algebra Appl 25 (1979), 151–162.
Boyd, S., Vandenberghe, L., Convex optimization. 2004, Cambridge University Press, New York.
Hart, W.E., Laird, C.D., Watson, J.-P., Woodruff, D.L., Hackebeil, G.A., Nicholson, B.L., et al. Pyomo – optimization modeling in Python. 2nd ed. Springer optimization and its applications, vol. 67, 2017, Springer Science & Business Media, New York.
IBM-ILOG, CPLEX User's Manual - Version 12 Release 7; 2016.
Zepter, J.M., Lüth, A., Crespo del Granado, P., Egging, R., Prosumer integration in wholesale electricity markets: synergies of peer-to-peer trade and residential storage. Energy Build 184 (2019), 163–176.