Research on Energy Saving Regulation of District Heating System based on Fish Migration Optimization Algorithm

Abstract An improved fish migration optimization algorithm (FMO) was proposed to solve the multi-objective optimization problem of district heating system. Through the hybrid coding strategy compatible with the mixed variable optimization of pump start-stop (0/1 decision) and temperature/flow (continuous regulation), combined with the time-delay model of pipe network, the thermal inertia compensation mechanism is designed, and the dynamic weight Pareto model of economy-environmental-reliability is constructed. The experiment shows that the improved FMO saves 19.7% of energy compared with the traditional PSO algorithm in the 50-node system, the temperature fluctuation of the client is reduced by 32%, and the computing efficiency is increased by 3.2 times. Practical engineering applications achieve 15- minute online optimization through the OPC UA interface, reducing 820 tons of CO 2 per year, providing an efficient solution for smart heating systems.