Distributed economic dispatch of embedded generation in smart grids

Engineering Applications of Artificial Intelligence

Volumn 44, Issue , 2015, Pages 64-78

  Dibangoye, J ^a   Doniec, A ^b   Fakham, H ^c   Colas, F ^c   Guillaud, X ^d  

^a INRIA   (France)

^b ECOLE DES MINES DE DOUAI   (France)

^c ARTS ET MÉTIERS PARISTECH   (France)

^d ECOLE CENTRALE DE LILLE   (France)

Author keywords

Distributed stochastic unit commitment problem; Information preserving; Multi agent planning; Smart grid

Indexed keywords

DISTRIBUTED POWER GENERATION; ELECTRIC LOAD DISPATCHING; ELECTRIC POWER TRANSMISSION NETWORKS; GRADIENT METHODS; MULTI AGENT SYSTEMS; OPTIMIZATION; SCHEDULING; STOCHASTIC SYSTEMS;

DISTRIBUTED COMPUTATIONS; DISTRIBUTED GENERATING UNITS; GRADIENT DESCENT ALGORITHMS; INFORMATION PRESERVING; MULTI-AGENT PLANNING; MULTIPLE DISTRIBUTED GENERATORS; SMART GRID; STOCHASTIC UNIT COMMITMENTS;

SMART POWER GRIDS;

EID: 84940099247     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2015.05.007     Document Type: Article

References (28)

1. K. Aoki, M. Itoh, T. Satoh, K. Nara, and M. Kanezashi Optimal long-term unit commitment in large scale systems including fuel constrained thermal and pumped-storage hydro IEEE Trans. Power Syst. 4 3 1989 1065 1073
2. F.L. Bellifemine, G. Caire, and D. Greenwood Developing Multi-Agent Systems with JADE 2007 John Wiley and Sons
3. Borghetti, A., Frangioni, A., Lacalandra, F., Lodi, A., Martello, S., Nucci, C., Trebbi, A., 2001. Lagrangian relaxation and tabu search approaches for the unit commitment problem. In: 2001 IEEE Porto Power Tech Proceedings, vol. 3.
4. F. Bouffard, F. Galiana, and A. Conejo Market-clearing with stochastic security - part i: formulation IEEE Trans. Power Syst. 20 4 2005 1818 1826
5. S. Boyd, and L. Vandenberghe Convex Optimization 2004 Cambridge University Press, New York, NY, USA
6. A. Cohen, and M. Yoshimura A branch-and-bound algorithm for unit commitment IEEE Trans. Power Appar. Syst. PAS 102 2 February 1983 444 451
7. R. Dechter Constraint optimization Constraint Processing 2003 Morgan Kaufmann San Francisco 363 397
8. Dufour, C., Abourida, S., Belanger, J., 2005. Hardware-in-the-loop simulation of power drives with rt-lab. In: Proceedings of the 6th International IEEE Conference on Power Electronics and Drives Systems, PEDS 2005, vol. 2, November, pp. 1646-1651.
9. M. Fisher The Lagrangian relaxation method for solving integer programming problems Manage. Sci. 50 2004 1861 1871
10. Guan, X., Zhai, Q., Papalexopoulos, A., 2003. Optimization based methods for unit commitment: Lagrangian relaxation versus general mixed integer programming. In: Power Engineering Society General Meeting, vol. 2, July 2003, IEEE, Toronto, Canada.
11. B. Kim, and R. Baldick Coarse-grained distributed optimal power flow IEEE Trans. Power Syst. 12 2 1997 932 939
12. Kok, J., Scheepers, M., Kamphuis, I., 2010. Intelligence in electricity networks for embedding renewables and distributed generation. In: Intelligent Infrastructures. Intelligent Systems, Control and Automation: Science and Engineering. Springer. pp. 179-209.
13. Kumar, A., Faltings, B., Adrian, P., 2009. Distributed constraint optimization with structured resource constraints. In: Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2009, vol. 2, pp. 923-930.
14. V. Lesser, M. Tambe, and C.L. Ortiz Distributed Sensor Networks: A Multiagent Perspective 2003 Kluwer Academic Publishers Norwell, MA, USA
15. G. Mathews, H. Durrant-Whyte, and M. Prokopenko Decentralised decision making in heterogeneous teams using anonymous optimisation Robot. Auton. Syst. 57 3 2009 310 320
16. Miller, S., Ramchurn, S., Rogers, A., 2012. Optimal decentralised dispatch of embedded generation in the smart grid. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, vol. 1, pp. 281-288.
17. P.J. Modi, W.-M. Shen, M. Tambe, and M. Yokoo Adopt: asynchronous distributed constraint optimization with quality guarantees Artif. Intell. 161 1-2 2005 149 180
18. Nikovski, D., Zhang, W., 2010. Factored Markov decision process models for stochastic unit commitment. In: 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply (CITRES), pp. 28-35.
19. M. Nowak, and W. Rmisch Stochastic lagrangian relaxation applied to power scheduling in a hydro-thermal system under uncertainty Ann. Oper. Res. 100 1-4 2000 251 272
20. S. Ramchurn, P. Vytelingum, A. Rogers, and N. Jennings Putting the 'smarts' into the smart grid: a grand challenge for artificial intelligence Commun. ACM 55 4 2012 86 97
21. G. Sheble, and G. Fahd Unit commitment literature synopsis IEEE Trans. Power Syst. 9 1 1994 128 135
22. W. Snyder, H. Powell, and J. Rayburn Dynamic programming approach to unit commitment IEEE Trans. Power Syst. 2 2 1987 339 348
23. S. Takriti, J. Birge, and E. Long A stochastic model for the unit commitment problem IEEE Trans. Power Syst. 11 3 1996 1497 1508
24. A. Tarim, S. Manandhar, and T. Walsh Stochastic constraint programming: a scenario-based approach Constraints 11 1 2006 53 80
25. J. Tsitsiklis, D. Bertsekas, and M. Athans Distributed asynchronous deterministic and stochastic gradient optimization algorithms IEEE Trans. Autom. Control 31 9 1986 803 812
26. Vytelingum, P., Ramchurn, S., Voice, T., Rogers, A., Jennings, N., 2010. Trading agents for the smart electricity grid. In: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2010, vol. 1, pp. 897-904.
27. W. Zhang, G. Wang, Z. Xing, and L. Wittenburg Distributed stochastic search and distributed breakout: properties, comparison and applications to constraint optimization problems in sensor networks Artif. Intell. 161 1-2 2005 55 87
28. S. Zilberstein, R. Washington, D.S. Bernstein, and A.-I. Mouaddib Decision-theoretic control of planetary rovers Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents 2002 Springer-Verlag London, UK 270 289