由于风能、太阳能等可再生能源受天气条件影响，具有间歇性和波动性，将会影响多能互补系统的可靠运行。氢能作为一种优质的二次能源，具有绿色无污染和高能量密度的优势。为应对新能源出力的不确定性，构建了多能互补热电联产系统模型，该系统包括热电机组、风力发电机组、光伏发电机组、电锅炉及氢储系统，并引入余热回收环节，以提升系统灵活性与能源利用效率。在此基础上，建立了以总运行成本最小和碳排放最少为目标的优化调度模型。针对该模型，提出一种改进的多目标模拟退火粒子群算法，有效提高了收敛速度和寻优精度。对山东省某地区的算例进行仿真分析，结果表明所提方法使系统总运行成本平均降低了12.51%，碳排放量平均减少了 5.53%，验证了所建模型与算法的可行性和优越性。

Renewable energy sources such as wind and solar power exhibit intermittency and volatility due to weather conditions, which can compromise the reliable operation of multi-energy complementary systems. Hydrogen energy, as a high-quality secondary energy source, offers advantages of being green, pollution-free, and possessing high energy density. To address the uncertainty in new energy output, this paper constructs a multi-energy complementary cogeneration system model.  This  system  integrates  a  thermal  power  unit,  wind  turbines,  photovoltaic  generators,  an  electric  boiler,  and  a hydrogen storage system, incorporating waste heat recovery to enhance system flexibility and energy utilization efficiency. Based on this, an optimization scheduling model is established with the dual objectives of minimizing total operating costs and  reducing  carbon  emissions.  For  this  model,  an  improved  multi-objective  simulated  annealing  particle  swarm optimization algorithm is proposed, effectively accelerating convergence and preventing local optima. Simulation analysis using a case study from a region in Shandong province demonstrates that the proposed method reduces the system’s total operating costs by an average of 12.51% and carbon emissions by 5.53%, validating the feasibility and superiority of the developed model and algorithm.