Multi-Timescale Coordinated Optimization for Adaptive Scheduling of Industrial Park CCHP Systems with Integrated Thermal and Cold Storage

In order to addresses operation limitations in industrial park CCHP systems, including single load patterns and the disconnect between storage capacity planning and operational strategies. A multi-time-scale collaborative optimization framework with multi-energy complementary storage is proposed. An enhanced CCHP system model integrates gas engines, waste heat recovery units, and absorption chillers with coupled electricity-heat-cooling flow dynamics. Equipment scheduling and power allocation are optimized using an improved Branch-and-Bound algorithm to minimize annual costs covering investment, operation, and dynamic energy pricing. For thermal and cold storage capacity configuration, an Adaptive Weighted Particle Swarm Optimization algorithm determines the optimal chilled/hot water tank capacities by maximizing revenue through valley electricity storage and peak discharge. The system achieves a peak comprehensive efficiency of 71.38% via full daytime waste heat utilization for cooling and partial nighttime surplus absorption. Results demonstrate that adaptive operational strategy, rather than capacity expansion, is the primary driver for elevating systemic efficiency.