【摘要】 研究了考虑源网协同的热电联产机组的热电负荷优化分配问题。通过建立热网数学模型与机组变工况模型，综合环境温度对热负荷需求及热电可行域边界的影响，构建以总热耗量最小为目标函数、以抽凝-抽背机组热电可行域为约束条件的优化模型，最后采用遗传算法求解。结果表明：在-5℃环境温度下，优化分配较平均分配的总热耗量降幅达1.0%～1.8%;典型日验证中，优化方案实现日标准煤耗量降低129.34t,显著提升了机组联合运行经济性。更多还原

【Abstract】 This study investigates the optimization of thermal and electrical load allocation for combined heat and power(CHP) units considering source-grid coordination. By establishing a thermal network mathematical model and a variable operating condition model for the units, the study comprehensively analyzes the impact of ambient temperature on thermal load demand and the boundaries of the thermal-electric feasible region. An optimization model is constructed with the objective of minimizing total thermal consumption and constrained by the thermal-electric feasible region of the extraction-condensation and extraction-backpressure units. The genetic algorithm is employed for solution. The results indicate that at an ambient temperature of -5 ℃, the optimized allocation achieves a reduction in thermal consumption of 1.0% to 1.8% compared to the average allocation. In a typical day validation, the optimized scheme reduces the daily standard coal consumption by 129.34 tons, significantly improving the economic efficiency of the combined operation of the units.更多还原