Journal of Shanghai Jiaotong University >
Unit Commitment Optimization Model Considering Impact of Multiple Operating Conditions on Unit Life Loss
Received date: 2023-08-21
Accepted date: 2023-09-11
Online published: 2023-10-07
Thermal power units face a dilemma of accelerated lifespan degradation and extended service duration. On one hand, large-scale integration of new energy sources has increased peak shaving conditions and accelerated losses of the units. On the other hand, service units will reach designed lifespan before carbon neutrality is achieved, while flexible operation of the power system necessitates extending their service life of units. Therefore, it is of great significance to consider the losses caused by varicus operating conditions on the lifespan of the unit and optimize the operating structure of the unit in scheduling simulation for unit longevity and carbon reduction efforts. To make unit life losses in theoretical research more practical, the traditional model that averages the losses in deep peak shaving conditions has been discarded. Instead, new judgment criteria for conventional and various special operating conditions of thermal power units are established. The lifespan loss cost of the unit is integrated into the operating objective function and the corresponding constraint conditions are modified. Finally, a unit commitment model considering the multi-operating condition lifespan losses of thermal power units is constructed. Example simulations indicate that the conventional model underestimates the actual loss cost of the units. In constrast, the proposed model can not only reduce the operating cost and unit life loss by considering the lifespan impacts of multi-operating conditions, but also enhance the peak shaving capacity of thermal power units and promote wind power consumption.
LUO Yifu , HU Qinran , QIAN Tao , CHEN Tao , ZHANG Yuanshi , ZHANG Fei , WANG Qi . Unit Commitment Optimization Model Considering Impact of Multiple Operating Conditions on Unit Life Loss[J]. Journal of Shanghai Jiaotong University, 2025 , 59(6) : 768 -779 . DOI: 10.16183/j.cnki.jsjtu.2023.401
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