Co-analysis of load distribution and thermal economy of cogeneration units based on improved particle swarm optimization algorithm

• Established a thermal power load optimization model based on coal consumption. • Solves boundary oscillation and local optimum issues in traditional PSO algorithms. • Explored the law of heat and power load distribution in cogeneration units. • Reduces gross coal use by 6.9–8.6 g/(kW·h), improving overall plant economy. To improve the operational efficiency and economic performance of cogeneration power plants, this study investigates the optimal thermoelectric load distribution of combined heat and power (CHP) units. Based on the coal consumption characteristics of CHP systems, a thermoelectric load allocation method is proposed. A high-fidelity simulation model of the cogeneration units is established using the power station’s heat balance diagrams, enabling precise evaluation of energy consumption under varying operating conditions. The effects of different load allocation strategies on total coal consumption are systematically examined. An improved Direction Vector-based Particle Swarm Optimization (DPSO) algorithm is developed to construct the thermoelectric load optimization model. Compared with conventional PSO and other intelligent algorithms, the proposed DPSO exhibits superior convergence speed and solution quality. Using typical daily load data and applying the feasible operation region as a constraint boundary, results indicate that the optimized load distribution among four cogeneration units connected to the same heating network reduces total coal consumption by 1.8–3.16 kg/s and decreases the standard coal consumption rate for power generation by 6.9–8.6 g/(kW·h). The analysis further reveals that prioritizing the electrical output of larger units under thermal load constraints while maximizing the thermal output of smaller units under electrical load constraints constitutes an optimal strategy for minimizing overall coal consumption. These findings provide both substantial economic benefits and practical operational guidance for enhancing the thermal economy of cogeneration power plants.

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Publication Details

Journal
Thermal Science and Engineering Progress
Published
2025-12-24
DOI
https://doi.org/10.1016/j.tsep.2025.104454
Primary Topic
Integrated Energy Systems Optimization
Type
article
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article

Co-analysis of load distribution and thermal economy of cogeneration units based on improved particle swarm optimization algorithm

Hongjie Su, Xincong Li, Wenli Pan, Jianlong Ma et al.
Thermal Science and Engineering Progress
Integrated Energy Systems Optimization
article

Co-analysis of load distribution and thermal economy of cogeneration units based on improved particle swarm optimization algorithm

Hongjie Su, Xincong Li, Wenli Pan, Jianlong Ma, Shenqiang Nie, Xiaoming Dong, Feng Wang, Qunhao Gu
article en

Abstract

• Established a thermal power load optimization model based on coal consumption. • Solves boundary oscillation and local optimum issues in traditional PSO algorithms. • Explored the law of heat and power load distribution in cogeneration units. • Reduces gross coal use by 6.9–8.6 g/(kW·h), improving overall plant economy. To improve the operational efficiency and economic performance of cogeneration power plants, this study investigates the optimal thermoelectric load distribution of combined heat and power (CHP) units. Based on the coal consumption characteristics of CHP systems, a thermoelectric load allocation method is proposed. A high-fidelity simulation model of the cogeneration units is established using the power station’s heat balance diagrams, enabling precise evaluation of energy consumption under varying operating conditions. The effects of different load allocation strategies on total coal consumption are systematically examined. An improved Direction Vector-based Particle Swarm Optimization (DPSO) algorithm is developed to construct the thermoelectric load optimization model. Compared with conventional PSO and other intelligent algorithms, the proposed DPSO exhibits superior convergence speed and solution quality. Using typical daily load data and applying the feasible operation region as a constraint boundary, results indicate that the optimized load distribution among four cogeneration units connected to the same heating network reduces total coal consumption by 1.8–3.16 kg/s and decreases the standard coal consumption rate for power generation by 6.9–8.6 g/(kW·h). The analysis further reveals that prioritizing the electrical output of larger units under thermal load constraints while maximizing the thermal output of smaller units under electrical load constraints constitutes an optimal strategy for minimizing overall coal consumption. These findings provide both substantial economic benefits and practical operational guidance for enhancing the thermal economy of cogeneration power plants.

Thermal Science and Engineering ProgressVol. 69
Inner Mongolia University of Technology (CN)
Openalex Percentile: Top 42%
Integrated Energy Systems Optimization
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