Cooperative Optimization of A Refrigeration System with A Water-Cooled Chiller and Air-Cooled Heat Pump by Coupling BPNN and PSO

Aiming at the issues of unreasonable cooperation schemes and inappropriate setting parameters refrigeration system with multi-chiller plants, this paper presents a cooperative optimization method to improve energy performance composed water-cooled chillers air-cooled heat pumps. The process includes scheme parameter optimization. To content dynamic cooling load, working sequence pumps variable frequency chilled water is first optimized. Based on optimal scheme, back-propagation neural network (BPNN) coupled particle swarm (PSO) implemented explore preferred operating multiple chiller plants corresponding best coefficient (COP). Compared initial operation module, consumption pump fan decreases by over 50%, COP improved 16% (COP = 3.85) through operation. After optimization, total reduced 21.7%, increased 26.5% 4.20). Therefore, proposed can provide useful guidance for plants.