A data-driven stochastic optimization approach to the seasonal storage energy management

IEEE Control Systems Letters

Volumn 1, Issue 2, 2017, Pages 394-399

  Darivianakis, Georgios ^a   Eichler, Annika ^a   Smith, Roy S ^a   Lygeros, John ^a  

^a ETH ZURICH   (Switzerland)

Author keywords

Smart cities houses; Stochastic optimal control

Indexed keywords

DIGITAL STORAGE; ENERGY CONSERVATION; ENERGY UTILIZATION; LONG TERM EVOLUTION (LTE); NUMERICAL METHODS; OPTIMIZATION; POTENTIAL ENERGY; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC SYSTEMS;

AFFINE APPROXIMATION; BUILDING ENERGY DEMANDS; COOPERATIVE MANAGEMENT; ENERGY GENERATIONS; STOCHASTIC OPTIMAL CONTROL; STOCHASTIC OPTIMIZATION APPROACH; STOCHASTIC OPTIMIZATION PROBLEMS; TOTAL ENERGY CONSUMPTION;

INFORMATION MANAGEMENT;

EID: 85057277225     PISSN: None     EISSN: 24751456     Source Type: Journal    
DOI: 10.1109/LCSYS.2017.2714426     Document Type: Article

References (19)

1. J. Laustsen, Energy Efficiency Requirements in Building Codes, Energy Efficiency Policies for New Buildings, Int. Energy Agency, Paris, France, pp. 477–488, Mar. 2008.
2. M. Geidl et al., “Energy hubs for the future,” IEEE Power Energy Mag., vol. 5, no. 1, pp. 24–30, Jan./Feb. 2007.
3. A. Parisio, C. D. Vecchio, and A. Vaccaro, “A robust optimization approach to energy hub management,” Int. J. Elect. Power Energy Syst., vol. 42, no. 1, pp. 98–104, 2012.
4. G. Darivianakis, A. Georghiou, R. S. Smith, and J. Lygeros, “A stochastic optimization approach to cooperative building energy management via an energy hub,” in Proc. IEEE Conf. Decis. Control, Osaka, Japan, 2015, pp. 7814–7819.
5. G. Darivianakis, A. Georghiou, R. S. Smith, and J. Lygeros, “The power of diversity: Data-driven robust predictive control for energy efficient buildings and districts,” IEEE Trans. Control Syst. Technol., to be published.
6. S.-E. Fleten and T.-K. Kristoffersen, “Short-term hydropower production planning by stochastic programming,” Comput. Oper. Res., vol. 35, no. 8, pp. 2656–2671, 2008.
7. M. V. F. Pereira and L. M. V. G. Pinto, “Multi-stage stochastic optimization applied to energy planning,” Math. Program., vol. 52, nos. 1–3, pp. 359–375, 1991.
8. G. Pritchard, A. B. Philpott, and P. J. Neame, “Hydroelectric reservoir optimization in a pool market,” Math. Program., vol. 103, no. 3, pp. 445–461, 2005.
9. N. Löhndorf, D. Wozabal, and S. Minner, “Optimizing trading decisions for hydro storage systems using approximate dual dynamic programming,” Oper. Res., vol. 61, no. 4, pp. 810–823, 2013.
10. D. Bertsekas, Dynamic Programming and Optimal Control, vol. 1. Belmont, MA, USA: Athena Sci., 1995.
11. W. Powell, Approximate Dynamic Programming: Solving the Curses of Dimensionality, vol. 703. Hoboken, NJ, USA: Wiley, 2007.
12. A. Ben-Tal, A. Goryashko, E. Guslitzer, and A. Nemirovski, “Adjustable robust solutions of uncertain linear programs,” Math. Program., vol. 99, no. 2, pp. 351–376, 2004.
13. P. M. Esfahani, T. Sutter, and J. Lygeros, “Performance bounds for the scenario approach and an extension to a class of non-convex programs,” IEEE Trans. Autom. Control, vol. 60, no. 1, pp. 46–58, Jan. 2015.
14. K. Margellos, P. Goulart, and J. Lygeros, “On the road between robust optimization and the scenario approach for chance constrained optimization problems,” IEEE Trans. Autom. Control, vol. 59, no. 8, pp. 2258–2263, Aug. 2014.
15. M. C. Campi and S. Garatti, “The exact feasibility of randomized solutions of uncertain convex programs,” SIAM J. Optim., vol. 19, no. 3, pp. 1211–1230, 2008.
16. G. C. Calafiore, “Random convex programs,” SIAM J. Optim., vol. 20, no. 6, pp. 3427–3464, 2010.
17. T. Gal and J. Nedoma, “Multiparametric linear programming,” Manag. Sci., vol. 18, no. 7, pp. 406–422, 1972.
18. K. Orehounig, G. Mavromatidis, R. Evins, V. Dorer, and J. Carmeliet, “Towards an energy sustainable community: An energy system analysis for a village in Switzerland,” Energy Build., vol. 84, pp. 277–286, Dec. 2014.
19. D. B. Crawley, L. K. Lawrie, C. O. Pedersen, and F. C. Winkelmann, “Energy plus: Energy simulation program,” ASHRAE J., vol. 42, no. 4, pp. 49–56, 2000.