Improved heat demand prediction of individual households

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 1, Issue PART 1, 2010, Pages 110-115

  Bakker, Vincent ^a   Bosman, Maurice G C ^a   Molderink, Albert ^a   Hurink, Johann L ^a   Smit, Gerard J M ^a  

^a UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Energy management; Neural network applications; Prediction methods

Indexed keywords

ELECTRIC NETWORK PARAMETERS; ELECTRIC POWER GENERATION; ENERGY EFFICIENCY; ENERGY MANAGEMENT; FORECASTING; HEATING;

ELECTRICITY NETWORKS; HEAT DEMAND PREDICTION; MICRO-COMBINED HEAT AND POWER; NEURAL NETWORK APPLICATION; NEURAL NETWORK TECHNIQUES; PREDICTION METHODS; PRODUCTION CAPACITY; VIRTUAL POWER PLANTS;

NEURAL NETWORKS;

EID: 80051992424     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20100329-3-pt-3006.00022     Document Type: Conference Paper

References (11)

1. Asar, A.U. and McDonald, J. (1994). A specification of neural network applications in the load forecasting prob-lem. Control Systems Technology, IEEE Transactions on, 2(2), 135-141. doi:10.1109/87.294341.
2. Bakker, V., Molderink, A., Hurink, J.L., and Smit, G.J.M. (2008a). Domestic heat demand prediction using neu-ral networks. In Proceedings of Nineteenth International Conference on Systems Engineering, Las Vegas, Nevada, USA, 189-194. IEEE Computer Society Press, Los Alamitos.
3. Bakker, V., Molderink, A., Hurink, J.L., and Smit, G.J.M. (2008b). Using heat demand prediction to optimize virtual power plant production capacity. In Proceedings of the Nineteenth Annual Workshop on Circuits, Systems ans Signal Processing (ProRISC), Velthoven, 11-15. Technology Foundation, Utrecht.
4. Bosman, M.G.C., Bakker, V., Molderink, A., Hurink, J.L., and Smit, G.J.M. (2009). The microchp scheduling problem. In Proceedings of the Second Global Conference on Power Control and Optimization, PCO 2009, Bali, Indonesia, 8. Springer Verlag, London.
5. Chen, S.T., Yu, D., and Moghaddamjo, A. (1992). Weather sensitive short-term load forecasting using nonfully connected artiffcial neural network. Power Systems, IEEE Transactions on, 7(3), 1098-1105. doi:10.1109/ 59.207323. (Pubitemid 23563458)
6. 2-besparingspotentieel van micro-WKK in Nederland (2010-2030). Technical report, Werkgroep Decentraal.
7. Dotzauer, E. (2002). Simple model for prediction of loads in district-heating systems. Applied Energy, 73(3-4), 277-284. doi:PIIS0306- 2619(02)00078-8. (Pubitemid 36049241)
8. Krose, B. and van der Smagt, P. (1993). An introduction to neural networks. URL citeseer.ist.psu.edu/ article/krose93introduction.html.
9. Molderink, A., Bosman, M.G.C., Bakker, V., Hurink, J.L., and Smit, G.J.M. (2009). Simulating the effect on the energy eficiency of smart grid technologies. In Winter Simulation Conference 2009. IEEE.
10. Serban, E. and Popescu, D. (2008). Prediction of domestic warm-water consumption. W. Trans. on Comp., 7(12), 2032-2041.
11. United States Department of Energy (2003). The micro CHP technologies roadmap. Results of the Micro-CHP Technologies Roadmap Workshop.