Multi-objective Optimization of Dynamic Back Pressure Setpoint Based on Genetic Algorithm

doi:10.11930/j.issn.1004-9649.201803122

Abstract

Abstract: Aiming at existing defects in backpressure value setting of most air-cooled units in China, by taking advantage of the parameters obtained during the operation of a 300MW direct air-cooled unit, a multi-objective optimization genetic algorithm (GA) was used to establish a specific mathematical model for back pressure and air cooler fan power consumption, and then solve the optimal solution for back pressure and minimum air cooler fan power consumption under certain constraints. Through this dynamic setting method, the backpressure setting of air-cooled units are optimized dynamically under variable load and AGC conditions, which is of great practical significance for the operating parameter adjustment of air-cooled units as well as the control strategy optimizations. It is also beneficial for the safe and economical operation of air-cooled units.

Key words: thermal power plant, direct air cooling, multi-objective optimization, genetic algorithm(GA), air-cooled fan power consumption, back pressure setting, dynamic optimization

CLC Number:

TP273
TM611

WANG Qi, QU Yan, BAI Jianyun, HOU Pengfei, LI Yongmao, FENG Geng. Multi-objective Optimization of Dynamic Back Pressure Setpoint Based on Genetic Algorithm[J]. Electric Power, 2018, 51(9): 59-64.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201803122

https://www.electricpower.com.cn/EN/Y2018/V51/I9/59

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