摘要
随着我国“双碳”目标的提出,公共建筑能耗低碳化成为重点研究领域,其中基于冷热负荷预测结果优化供能系统调度策略是实现“按需供能”的有效技术手段。针对公共建筑,基于热阻法构建了冷热负荷预测模型,根据负荷预测结果,采用改进粒子群优化(PSO)算法对复合冷热源供能系统的负载、水网供回水温度和流量、阀门开度以及泵组启用台数进行迭代寻优,以供能系统运行成本、机组寿命和环保性为优化目标提出全工况最佳运行策略。基于研究成果对某公共建筑冬季供热系统进行节能改造,可在满足建筑热负荷、平衡水力工况和延长机组运行寿命的同时,分别实现降低泵组功耗10.66%、系统运行成本21.52%。结果符合理论实际,证明了所提方法的可行性与有效性,为公共建筑的按需供热、节能运行提供了有效参考。
With the proposal of"dual-carbon"goal in China,the decarbonization of energy consumption in public buildings has become a key research area,in which optimizing the scheduling strategy for energy supply systems based on the prediction results of hot and cold loads is an effective technological means to achieve the"on-demand energy supply".A hot and cold load prediction model for public buildings is constructed based on the thermal resistance method.According to the load prediction results,control optimization is performed on the parameters of an energy supply system by improved particle swarm algorithm(PSO),with the objectives of minimizing operating costs,reducing environmental costs and prolonging the service life of units.After iterative optimization on the parameters including the load of the combined coldheat-power supply system,temperatures and flow rates of supply and return water,openings of valves and number of operating pump units,an optimal operation strategy under all operation conditions is proposed.A public building taking the proposed optimal operation strategy to update its heating system can reduce the power consumption of pump units by 10.66%and cut the operating cost by 21.52%,while meeting the heating demand of the building,balancing the hydraulic conditions and extending the operating life of the units.The consistency of the test results and the theoretical data proves the feasibility and effectiveness of the method proposed,providing an effective reference for on-demand heat supply and energy-saving operation of public buildings.
作者
孙健
张云帆
蔡潇龙
刘鼎群
SUN Jian;ZHANG Yunfan;CAI Xiaolong;LIU Dingqun(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University,Beijing 102206,China;Design Department,China Mobile Park Construction and Development Company Limited,Beijing 102206,China)
出处
《综合智慧能源》
CAS
2024年第3期12-19,共8页
Integrated Intelligent Energy
基金
国家重点研发计划项目(2019YFE0104900)
国家自然科学基金项目(52090062)
中央高校基本科研业务费专项资金资助(2020MS009)
中移园区建设发展有限公司科技项目(2023-282)。
关键词
“双碳”目标
等效热阻
负荷预测
复合冷热源系统
粒子群优化算法
多目标优化
"dual-carbon"goal
equivalent thermal resistance
load forecasting
combined cold-heat-power supply system
particle swarm optimization algorithm
multi-objective optimization
