Abstract:

The reasonable planning and configuration of composite system in low-carbon park is of great significance for improving system energy efficiency and reducing costs and pollutant emissions. Firstly, based on the energy-demand fast prediction method for park and the composite energy system dynamic simulation platform, this paper proposed an optimal planning and configuration method for low-carbon park composite energy system, and established a hybrid optimization algorithm combining Hook-Jeff algorithm and particle swarm optimization. Secondly, by taking a multi-energy system with triple supply of cooling, heating and power system coupled with ground source heat pump, energy storage, and gas boiler in a typical low-carbon park as an example, a comparative analysis was made on the configuration results and optimization speed with different optimization algorithms, and a study was conducted on the impacts of different optimization objectives such as optimal comprehensive optimization objective and lowest whole life-cycle cost and energy consumption on the capacity optimization configuration results and typical daily operation situation. The results show that the proposed optimal configuration method and hybrid optimization algorithm can ensure the optimization capacity and accuracy with higher calculation performance. The energy system configuration results with optimal comprehensive evaluation objectives can take into account multiple factors such as system cost, economic operation, environmental impacts and low-carbon emissions, which can effectively realize the optimal energy form of low-carbon parks.

Key words: low-carbon park, composite energy system, optimal configuration, integrated optimization objective, hybrid optimization algorithm