摘要
分布式热电联产系统是一种临近用户的先进能源系统,系统构型、装机容量和运行策略的选择对系统节能性、环保性和经济性有重要影响。本研究以某办公大楼为对象,根据其全年实时运行数据,分析了其热电负荷特征;同时,为该办公楼构建了分别以微燃机和内燃机为动力单元的两种不同CHP系统构型方案,建立了相应的变工况能量平衡模型。进一步探讨了系统在以热定电与以电定热、变工况运行与额定运行、有储热与无储热、24h连续运行与早起晚停等不同运行策略下动力机组装机容量对该办公楼经济性、节能性和环保性的影响规律。同时运用多目标评价指标来对系统不同装机容量和运行策略下的收益综合评估,并引入了混沌粒子群优化算法来找到系统最大的综合收益,结果表明,该办公楼应用CHP系统后全年的经济性、节能性和环保性较传统的单一功能模式分别提高了22.85%、17.45%、25.06%。
A distributed combined heating and power(CHP)system is an advanced energy system which is close to end users.The selection of system configuration,capacity and operation strategy has an important impact on energy saving,environmental protection and economics of the system.This research took a building as an example and analyzed the characteristics of the thermal and electric loads using real time data.At the same time,two different configurations were constructed for the CHP system using respectively a micro-turbine and an internal-combustion engine as the power source,and corresponding variable-condition energy balance models were established.Furthermore,the influence of the power unit capacity on the economics,energy saving and environmental protection of the office building was discussed under different operation strategies,such as Following Thermal Load and Following Electric Load,operating under varying operating conditions and rated operation,with and without heat storage,24-hour continuous operation and early rising and late stopping.Meanwhile,a multi-objective evaluation index was used to evaluate the benefits of the system under different installed capacities and operation strategies,and a chaotic particle swarm optimization algorithm was introduced to find the maximum comprehensive benefits of the system.The results showed that the economic,energy-saving and environmental protection performance of the office building with the CHP system was better than the traditional single function model,and the enhancements were22.85%,17.45%and25.06%,respectively.
作者
张健
徐玉杰
李斌
陈海生
纪律
郭丛
ZHANG Jian;XU Yujie;LI Bin;CHEN Haisheng;JI Lv;GUO Cong(North China Electric Power University,Baoding 071003,Hebei,China;Institute of Engineering Thermophysics,Chinese Academy of Sciences,Beijing 100190,China)
出处
《储能科学与技术》
CAS
CSCD
2019年第1期83-91,共9页
Energy Storage Science and Technology
基金
国家重点研发计划项目(2017YFB0903602)
中国科学院洁净能源先导科技专项项目(XDA21070200)
中国科学院前沿科学重点研究项目(QYZDB-SSW-JSC023)
中国科学院国际合作局国际伙伴计划项目(182211KYSB20170029)
关键词
分布式热电联产系统
负荷特征
系统构型
容量优化
粒子群算法
distributed combined heating and power system
load character
configuration scheme
capacity optimization
particle swarm optimization algorithm