Developing a Decision Support System for the Optimal Operating Strategies of a Polygeneration Facility

Polygeneration, i.e., the generation of two or more energy products at the same time, emerges as a promising solution for optimal energy resource utilization. Due to the highly complex interactions among system components, optimization is needed to achieve environmental and economic benefits. Important work has been done in polygeneration system design, but few studies deal with the response to varying conditions and contingencies to maintain and improve savings and to achieve reliable operation. Here we implement a polygeneration facility model consisting of a combination of renewable and conventional energy generation, conversion, and storage devices. Genetic algorithm is used to find the optimal system designs under different operation strategies that minimize CO₂ emissions, fuel usage, and overall cost. After initial optimization, a decision support system is developed to aid in the day-ahead operation strategy selection to improve system performance under the changing operational conditions. Results show that the 3 operating strategies analyzed can achieve annual savings of 20-27% compared to the reference system. It is also shown that switching strategy can result in additional savings and avoid system collapse in some scenarios. This work will contribute to the future design and operation of polygeneration facilities.