LAUSR

Abstract In this paper we develop a distributed optimization method for a Heat Exchangers Network. The considered network is given by an interconnected hot thermal sources flows and cold consumers flows through counter-current heat exchangers. The optimization problem corresponds to a maximization of the thermal power benefits, expressed as a heating utility function, of the different consumers flows from the overall sources flows through the network. This utility function is estimated using Proportional Integral Distributed Average Consensus Estimator on the base of partial information exchange between some consumers through a communication graph. By using the estimated utility function an extremum seeking scheme is implemented for each consumer decision variable (consumer mass flow rate fraction) to achieve the optimal state. Some simulations results are given on a network example which show the effectiveness of the proposed approach.