Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling

Process cooling for food production is an energy-intensive industry with complex interactions and restrictions that complicate the ability to utilize energy-flexibility due unforeseen consequences in production. Therefore, methods assessing potential flexibility individual facilities enable active participation of process-cooling electricity system are essential, but not yet well discussed literature. this paper introduces assessment method based on multi-method simulation multi-objective optimization investigating energy process cooling, a case study Danish facility canned-meat Multi-method used paper: multi-agent-based investigate entities within system’s behavior; discrete-event explore entire flow; dynamics capture thermophysical properties refrigeration unit states refrigerated environment. A library developed, able represent generic production-flow canned-food cooling. data-driven symbolic-regression approach determines logic agents. Using binary tuple-matrix refrigeration-schedule optimization, refrigeration-cycle operation determined, weather forecasts, price, CO2 emissions without violating room-temperature limits. The results one-week’s October 2020 show 32% costs can be saved 822 kg reduced. thereby facilities, benefit overall cost reduction; at same time, quality throughput influenced.