Impact of weather inputs on heating plant: agglomeration modeling
NN'09 Proceedings of the 10th WSEAS international conference on Neural networks
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Methods for prediction of heat distribution parameters
MACMESE'11 Proceedings of the 13th WSEAS international conference on Mathematical and computational methods in science and engineering
Hi-index | 0.00 |
This paper describes the usage of peak functions in the heat load modeling of district heating system. Heat load is approximated by the sum of time dependent and temperature dependent components. The temperature dependent component is approximated using sum of two peak functions and temperature dependent component is approximated using generalized logistic function. The model parameters are estimated using Particle Swarm Algorithm.