Multi-objective optimal temperature control for Organic Rankine Cycle systems

The Organic Rankine Cycle (ORC) has attracted a lot of interests for its ability to recover low-grade heat and the possibility to be implemented in decentralized low-capacity power plants. In this paper, a new optimal temperature control method is proposed for ORC systems with non-Gaussian disturbances which influence the quality of exhaust gas. The objective here is to control the speed of the pump so that the superheated vapor temperature follows a target one. It means that the error between those two temperatures is minimized both in magnitude and randomness, which are characterized by mean value and entropy, respectively. Therefore, the proposed control strategy is regarded as a multi-objective optimization problem. To solve this problem, a Multi-Objective Estimation of Distribution Algorithm (MOEDA) is adopted to obtain all the possible optimal control inputs. Simulation results show the effectiveness of the proposed technique.