1. Energy, cost and carbondioxide optimization in regional energy systems with periodic and stochastic demand fluctuations.
- Author
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Thoma, M., Wyner, W., Davisson, L. D., MacFarlane, A. G. J., Kwakernaak, H., Massey, J. L., Tsypkin, Ya Z., Viterbi, A. J., Kall, Peter, Groscurth, Helmuth-M., and Kümmel, Reiner
- Abstract
The new linear, stochastic optimization model ECCO has been developed as a computerized planning tool for case studies on integrated energy management involving heat recovery by heat exchanger networks, heat pumps and cogeneration. The procedure of stochastic optimization is described in detail. It is based on a representative sample of time intervals, each of which is characterized by a distinct demand situation that is determined by simulating periodic and stochastic fluctuations of the energy demand. For a model city, which consists of three districts with together nearly 20,000 inhabitants and 4 industrial companies, we obtain the following results: Via heat recovery and cogeneration, the primary energy input into the energy system of the model city may be reduced by 25% compared to a status quo scenario. At the same time, the CO2-emissions are reduced by 31% with some fuel switching from coal to natural gas being involved. Introducing waste heat recovery and cogeneration into the model city at the current low energy price level would increase the cost of the energy system by at least 41% with respect to the status quo. [ABSTRACT FROM AUTHOR]
- Published
- 1992
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