Operational optimization on large‐scale combined heat and power units with low‐pressure cylinder near‐zero output

Wang, Zijie; Gu, Yujiong; Zhao, Zhengxu; Lu, Shuyin

doi:10.1002/ese3.1439

Cited by 1 publication

(1 citation statement)

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“…In 1995, particle swarm optimization (PSO) was proposed by Kennedy and Eberhart [23] to imitate the social behavior of animals. The swarm-based stochastic algorithm has been extended for utilization in CHP [24] operation optimization. To receive the optimal solution, the personal best position (p best,i ) for each particle and the global best position (g best,i ) in the swarm need to be evaluated.…”

Section: Particle Swarm Optimization Methodsmentioning

confidence: 99%

Numerical Study on Peak Shaving Performance of Combined Heat and Power Unit Assisted by Heating Storage in Long-Distance Pipelines Scheduled by Particle Swarm Optimization Method

Ju,

Wang,

Feng

et al. 2024

Energies

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Thermal energy storage in long-distance heating supply pipelines can improve the peak shaving and frequency regulation capabilities of combined heat and power (CHP) units participating in the power grid. In this study, a one-dimensional numerical model was established to predict the thermal lag in long-distance pipelines at different scale levels. The dynamic response of the temperature at the end of the heating pipeline was considered. For the one-way pipe lengths of 10 km, 15 km and 20 km, the response times of the temperature at the distal end were 2.33 h, 2.94 h and 3.54 h, respectively. The longer the flow period, the further the warming-up time is delayed. An optimization scheduling approach was also created to illustrate the peak shaving capabilities of a CHP unit combined with a long-distance pipeline thermal energy storage component. It was demonstrated that the maximum heating load of the unit increased up to 503.08 MW, and the heating load could be expanded in the range of 17.88 MW to 203.76 MW at the minimum electric load of the unit of 104.08 MW. Finally, the particle swarm optimization method was adopted to guide the operating strategy through a whole day to meet both the electric power and heating power requirements. For the optimized case, the comprehensive energy utilization efficiency and the exergy efficiency increase to 64.4% and 56.73%. The thermal energy storage applications based on long-distance pipelines were simulated quantitively and proved to be effective in promoting the operational flexibility of the CHP unit.

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Section: Particle Swarm Optimization Methodsmentioning

confidence: 99%