热电联产是提升燃煤发电机组能量利用效率的有效手段,通过热电联产电站的热电负荷优化分配可提升热电联产电站的综合能量利用效率。本文针对5台热电联产机组、2个供热热网构成的热电联产电站,研究获得了不同类型热电联产机组的变工况运行特性和能耗特性,采用粒子群智能算法建立了热电联产电站运行优化模型,以电站总煤耗量最低为优化目标开展了两个热网的供热优化。结果表明,在不同的对外电热负荷量下,相比于现有负荷分配方式,采用粒子群算法得到的优化分配结果可以使全厂总煤耗量降低约3.1~13.6 t/h,占比0.97%~2.27%。

Cogeneration is an effective way to enhance the energy efficiency of coal-fired power units. The comprehensive energy efficiency of cogeneration power plants can be improved through the scheduling of heat and power loads of cogeneration power plants. In this paper, the operational and energy consumption characteristics of different type cogeneration units under variable working conditions are obtained for the cogeneration power station composed of five cogeneration units and two heating networks. The operation optimization model of the cogeneration power station is developed with particle swarm intelligence algorithm, and the heating optimization of two heating networks is carried out with the minimum total coal consumption as the optimization goal. The results show that under different external power and heating loads, compared with the existing load scheduling methods, the optimal scheduling results obtained by the particle swarm optimization algorithm can reduce the total coal consumption of the whole plant by about 3.1 - 13.6t/h, accounting for 0.97% - 2.27%.

TK212