构建先进绝热压缩空气储能（AA-CAES）与内燃机（ICE）和有机朗肯循环（ORC）深度耦合的综合能源系统（IES-ORC-CAES）,通过改变ICE的部分负荷率、ORC的烟气占比、低温烟气温度、电制冷占比和电价低谷期的储电量,实现了系统能量根据用户负荷的动态调整。基于K-均值算法将典型年负荷聚类为典型日场景集,考虑分时电价,以经济性、环保性和能效性为目标,采用并行式的遗传算法对IES-ORC-CAES和参考系统展开优化。结果表明：不同目标下,IES-ORC-CAES系统的年化运行成本、CO2排放量和一次能源消耗量分别比参考系统降低了10.43%、8.19%和1.80%。此外,通过协同调节ICE、ORC和AA-CAES的出力,IES-ORC-CAES系统中AA-CAES和ORC在典型日1分别承担了用户电负荷的12.26%和0.10%,对减小电网压力和增加系统供能灵活性有重要意义。
Abstract
In this paper, an integrated energy system （IES-ORC-CAES） with advanced adiabatic compressed air energy storage （AA-CAES）, internal combustion engine （ICE） and organic Rankine cycle （ORC） is constructed. By changing the partial load rate of ICE, the proportion of flue gas in ORC, the temperature of low-temperature flue gas, the proportion of electric refrigeration and the electricity storage capacity during the valley electricity price period, the dynamic adjustment of system energy according to the user load requirements is realized. Based on the K-means algorithm, the typical annual load is clustered into a typical daily scenario set. Considering the timeofuseelectricity price, the parallel genetic algorithm is used to optimize IES-ORC-CAES and reference system with economy, environmental protection and energy efficiency as objectives.The results show that the annual operation cost, CO2 emission and primary energy consumption of IES-ORC-CAES system are reduced by 10.43%, 8.19% and 1.80% respectively compared with the reference system.In addition, by coordinating the output of ICE, ORC and AA-CAES, AA-CAES and ORC in IES-ORC-CAES system bear 12.26% and 0.10% of users’ electricity load on typical day 1, which is of great significance for reducing grid pressure and increasing system energy supply flexibility.
关键词
先进绝热压缩空气储能 /
有机朗肯循环 /
并行式的遗传算法 /
综合能源系统 /
协同优化 /
性能分析
Key words
AA-CAES /
ORC /
parallel genetic algorithm /
collaborative optimization /
performance analysis
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基金
广东省分布式能源系统重点实验室（2020B1212060075）
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