Abstract
With the existence of several energetic resources and local production site by consumers a new strategy for managing the distribution of energy is indispensable. This paper aims to develop a simulation platform for energy resources management of a Micro Grids Network to optimize the electricity consumption. Using the remote control systems and data integration from distributed databases the system regulates automatically the distribution following the need of each customer and need of Micro Grid. The solution use an incremental search algorithm based on the total satisfaction of the constraints by priority order. In this paper, as software platform solution, we use the multi-agent system (MAS) technology. This choice is motivated by the functional ability of agents, and their self-adaptation to the environment (i.e. change the feature). The ability of the interaction between the agents and their mobility will define and specify the real-time needs of each Micro Grids according to its production and consumption capacity and the need of its neighbors. The functional architecture of the operating system is based on a graph, where each node can be a customer or producer of energy or both of them associated with list of requirement constraints. We used the principle of Distributed Databases to facilitate communication inter-agents and to optimize the time of data transfer between agents of different Micro Grids and simplified access “on demand” to the data with high availability. Thanks to the distributed databases solution, we can easily integrate the critical data on a data center and improve the response time of readjustment and equilibration of the electricity distribution and consumption.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pepermans, G., Driesen, J., Haeseldonckx, D., et al.: Distributed generation: definition, benefits and issues. Energy Policy 33, 787–798 (2005)
Molderink, A., Bakker, V., Bosman, M., et al.: Management and control of domestic smart grid technology. IEEE Trans. Smart Grid 1(2), 109–119 (2010)
Carrasco, J., Franquelo, L., Bialasiewicz, J., et al.: Power electronic systems for the grid integration of renewable energy sources: a survey. IEEE Trans. Ind. Electron. 53(4), 1002–1016 (2006)
Justo, J.J., Mwasilu, F., Lee, J., Jung, J.-W.: AC-microgrids versus DC-microgrids with distributed energy resources: a review. Renew. Sustain. Energy Rev. 24, 387–405 (2013)
Guerrero, J., Chandorkar, M., Lee, T., Loh, P.: Advanced control architectures for intelligent microgrids–part I: decentralized and hierarchical control. IEEE Trans. Ind. Electron. 60(4), 1254–1262 (2013)
Guerrero, J., Loh, P.C., Lee, T.-L., Chandorkar, M.: Advanced control architectures for intelligent microgrids – part II: power quality, energy storage, and AC/DC microgrids. IEEE Trans. Ind. Electron. 60(4), 1263–1270 (2012)
SolarRay, Grid-tie package systems without batteries. http://www.solarray.com/CompletePackages/Grid-Tie-No-Batteries T.php, posted on (2012)
Westermann, D., Kratz, M.: A real-time development platform for the next generation of power system control functions. IEEE Trans. Ind. Electron. 57(4), 1159–1166 (2010)
Ekneligoda, N.C., Weaver, W.W.: A game theoretic bus selection method for loads in multibus DC power systems. IEEE Trans. Ind. Electron. 61(4), 1669–1678 (2014)
Başar, T., Olsder, G.L.: Dynamic Noncooperative Game Theory. Series in Classics in Applied Mathematics. SIAM, Philadelphia (1999)
Vásquez, J., Guerrero, J., Miret, J., Castilla, M., de Vicuña, L.: Hierarchical control of intelligent microgrids. IEEE Ind. Electron. Mag. 4(4), 23–29 (2010)
Guerrero, J., Vasquez, J., Matas, J., de Vicuña, L., Castilla, M.: Hierarchical control of droop-controlled AC and DC microgrids – a general approach toward standardization. IEEE Trans. Ind. Electron. 58(1), 158–172 (2011)
Guerrero, J., Vásquez, J., Matas, J., Castilla, M., de Vicuña, L.: Control strategy for flexible microgrid based on parallel line-interactive ups systems. IEEE Trans. Ind. Electron. 56(3), 726–736 (2009)
Hill, C., Such, M., Chen, D., Gonzalez, J., Grady, W.: Battery energy storage for enabling integration of distributed solar power generation. IEEE Trans. Smart Grid 3(2), 850–857 (2012)
Liu, Y., Yuen, C., Huang, S., Hassan, N.U., Wang, X., Xie, S.: Peakto-average ratio constrained demand-side management with consumer’s preference in residential smart grid. IEEE J. Sel. Topics Signal Process. PP(99), 1–14 (2014)
Hassan, N.U., Pasha, M.A., Yuen, C., Huang, S., Wang, X.: Impact of scheduling flexibility on demand profile flatness and user inconvenience in residential smart grid system. Energies 6(12), 6608–6635 (2013)
Balaguer, I., Lei, Q., Yang, S., Supatti, U., Peng, F.Z.: Control for grid-connected and intentional islanding operations of distributed power generation. IEEE Trans. Ind. Electron. 58(1), 147–157 (2011)
Liu, Y., Hassan, N., Huang, S., Yuen, C.: Electricity cost minimization for a residential smart grid with distributed generation and bidirectional power transactions. In: IEEE PES Innovative Smart Grid Technologies (ISGT), Washington, DC, pp. 1–6, February 2013
Zhang, D., Shah, N., Papageorgiou, L.G.: Efficient energy consumption and operation management in a smart building with microgrid. Energy Convers. Manag. 74, 209–222 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Ezziyyani, M., Cherrat, L. (2018). Optimal Regulation of Energy Delivery for Community Microgrids Based on Constraint Satisfaction and Multi-agent System. In: Ezziyyani, M., Bahaj, M., Khoukhi, F. (eds) Advanced Information Technology, Services and Systems. AIT2S 2017. Lecture Notes in Networks and Systems, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-69137-4_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-69137-4_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69136-7
Online ISBN: 978-3-319-69137-4
eBook Packages: EngineeringEngineering (R0)