Equipment capacity optimization of an educational building’s CCHP system by genetic algorithm and sensitivity analysis
Equipment capacity optimization of an educational building’s CCHP system by genetic algorithm and sensitivity analysis
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基于遗传算法和敏感性分析的教育建筑冷热电联供系统设备容量优化
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Emami
中科院分区：
文献类型：
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作者：
M. Shahnazari;Leila Samandari;S. Emami
冷热电联产 (CCHP) 系统由于其高效率和低排放，可产生电力、冷却和热量。这些系统已广泛应用于各种建筑类型，如办公室、酒店、医院和商场。本文对一座建筑进行了经济和技术分析，以确定一年内特定电力、冷却和供热负荷曲线所需燃气发动机的尺寸和运行情况。为了执行此任务，引入了目标函数净现值 (NPV) 并通过遗传算法 (GA) 最大化。此外，结果最终找到了最佳容量。此外，还需要进行敏感性分析，以显示最佳解决方案如何因燃料价格、购电价格和售电价格等关键参数的变化而变化。结果表明，这些参数对系统性能有影响。
Combined cooling, heating, and power (CCHP) systems produce electricity, cooling, and heat due to their high efficiency and low emission. These systems have been widely applied in various building types, such as offices, hotels, hospitals and malls. In this paper, an economic and technical analysis to determine the size and operation of the required gas engine for specific electricity, cooling, and heating load curves during a year has been conducted for a building. To perform this task, an objective function net present value (NPV) was introduced and maximized by a genetic algorithm (GA). In addition, the results end up finding optimal capacities. Furthermore, a sensitivity analysis was necessary to show how the optimal solutions vary due to changes in some key parameters such as fuel price, buying electricity price, and selling electricity price. The results show that these parameters have an effect on the system’s performance.