Site utility system optimization with operation adjustment under uncertainty
Site utility system optimization with operation adjustment under uncertainty
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DOI：
10.1016/j.apenergy.2016.05.036
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发表时间：
2017-01
期刊：
影响因子：
11.2
通讯作者：
Li Sun;Limei Gai;Robin Smith
中科院分区：
文献类型：
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作者：
Li Sun;Limei Gai;Robin Smith
公用事业系统必须满足不同条件下的过程能量和功率需求。系统性能取决于锅炉、燃气轮机、汽轮机、凝汽器和减压阀的系统配置和单个设备的运行负荷。蒸汽压力和蒸汽过热对系统中的蒸汽分配和汽轮机蒸汽膨胀发电也有重要影响，应纳入系统优化。在系统优化中应考虑工艺蒸汽功率需求变化、电价波动等不确定性因素，尽可能消除因不确定因素引起的蒸汽功率亏空造成的生产损失。本文将不确定因素分为基于时间的不确定因素和基于概率的不确定因素，提出了包含多周期设备负荷分担、设备冗余启动和电力输入补偿缺电的运行计划，以处理不确定因素的发生，并将其表示为优化模型中的多周期项目和资源项目。本文有两个案例研究。一个案例说明了在设计阶段确定系统配置、设备选型和系统运行调度以处理不确定性的系统设计。另一种情况提供了现有系统的运行优化方案，特别是当蒸汽过热度变化时。该方法对提高系统能效具有实际指导意义。
Utility systems must satisfy process energy and power demands under varying conditions. The system performance is decided by the system configuration and individual equipment operating load for boilers, gas turbines, steam turbines, condensers, and let down valves. Steam mains conditions in terms of steam pressures and steam superheating also play important roles on steam distribution in the system and power generation by steam expansion in steam turbines, and should be included in the system optimization. Uncertainties such as process steam power demand changes and electricity price fluctuations should be included in the system optimization to eliminate as much as possible the production loss caused by steam power deficits due to uncertainties. In this paper, uncertain factors are classified into time-based and probability-based uncertain factors, and operation scheduling containing multi-period equipment load sharing, redundant equipment start up, and electricity import to compensate for power deficits, have been presented to deal with the happens of uncertainties, and are formulated as a multi-period item and a recourse item in the optimization model. There are two case studies in this paper. One case illustrates the system design to determine system configuration, equipment selection, and system operation scheduling at the design stage to deal with uncertainties. The other case provides operational optimization scenarios for an existing system, especially when the steam superheating varies. The proposed method can provide practical guidance to system energy efficiency improvement.