Abstract
A district heating system (DHS) consists of energy suppliers and consumers, heat generation and storage facilities and power transmission lines in the region. DHS has taken charge of an increasingly important role as the energy cost increases recently. In this work, a model for operational optimization of the DHS in the metropolitan area is presented by incorporating forecast for demand from customers. In the model, production and demand of heat in the region of Suseo near Seoul, Korea, are taken into account as well as forecast for demand using the artificial neural network. The optimization problem is formulated as a mixed integer linear programming (MILP) problem where the objective is to minimize the overall operating cost of DHS. The solution gives the optimal amount of network transmission and supply cost. The optimization system coupled with forecast capability can be effectively used as design and longterm operation guidelines for regional energy policies.
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References
M. Ibrahim and R. Saifure, IEEE Trans. Power Syst., 4(4) (1989).
K. Lru, S. Subbarayan, R. R. Shoults, M. T. Manry, C. Kwan, F. L. Iewis and J. Naccarino, IEEE Trans. Power Syst., 11(2) (1996).
D. Alex and C. Timothy, IEEE Trans. Power Syst., 5, 1535 (1990).
B. Jie, Short-term load forecasting based on neural network and moving average, Iowa State University (2002).
I. Dejan, FME Transactions, 34, 165 (2006).
T. Yalcinoz and U. Eminoglu, Energy Conversion and Management, 46, 1393 (2005).
A. J. Al-Shareef, E.A. Mohamed and E. Al-Judaibi, One hour ahead load forecasting using artificial neural network for the western area of saudi arabia, International Journal of Electrical Systems Science and Engineering (2006).
J. Y. Fan and J. D. McDonald, IEEE Trans. Power Syst., 9, 988 (1994).
D. Erik, Appl. Energy, 73, 277 (2002).
F. Jovic, V. Rajkovic, Z. Jagnjic and D. Vuksanovic, Information Technology Interfaces, 1, 325 (2001).
K. Çomakı, B. Yüksel and Ö. Çomakı, Appl. Thermal Eng., 24, 1009 (2004).
G. Sandou, S. Font, S. Tebbani, A. Hiret and C. Mondon, Decision and Control, 44, 7372 (2005).
J. Söderman and F. Pettersson, Appl. Thermal Eng., 26, 1400 (2005).
J. Söderman, Appl. Thermal Eng., 27, 2665 (2007).
C. Weber, I. Heckl, F. Friedler, F. Marechal and D. Favrat, Network synthesis for a district energy system: A step towards sustainability, 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering, 1869–1874 (2006).
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Park, T.C., Kim, U.S., Kim, LH. et al. Optimization of district heating systems based on the demand forecast in the capital region. Korean J. Chem. Eng. 26, 1484–1496 (2009). https://doi.org/10.1007/s11814-009-0282-8
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DOI: https://doi.org/10.1007/s11814-009-0282-8