An adaptive optimal control model for building cooling and heating sources is presented with the aim of achieving global optimization and satisfying the requirements of time and accuracy in HVAC system control. The adaptive optimal control model includes the optimal control model, parameter identification and optimization algorithm. First, the penalty function is constructed to transform constrained optimization problem into unconstrained optimization problem, and then, the fuzzy self-tuning forgetting factor method is developed for parameter identification. In the end, the genetic algorithm (GA) is used to find the optimum values for the discrete and continuous variables. Optimization is applied for the building cooling source system in a publishing house located in Changsha, China. The optimization is expected to reduce the energy consumption of the cooling source system by 7%. (C) 2008 Elsevier B.V. All rights reserved.