Optimal chiller loading by evolution strategy for saving energy

This study employs evolution strategy (ES) to solve optimal chiller loading (OCL) problem. ES overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW–partial load ratio (PLR) curves include non-convex functions. The complicated process of evolution by the genetic algorithm (GA) method for solving OCL can also be simplified by the ES method. This study uses the chilled water supply temperature as the variable to be solved for the decoupled air conditioning system. After analysis and comparison of the case study, it has been concluded that this method not only solves the problems of Lagrangian method and GA method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems.