综合需求响应作为提升能源利用效率，促进可再生清洁能源消纳的有效途径之一，其本质是通过综合能源设备的多能耦合能力引导用户参与源荷双向互动。为提升综合能源系统的运行控制水平需要准确评估综合能源设备的响应价值。对此，提出了一种基于Sobol’全局灵敏度分析的综合能源设备响应价值量化方法。以总运行成本最小为目标函数，考虑多类型需求响应，建立了综合能源系统泛化优化模型，并构建了基于粒子群-反向传播神经网络的综合能源系统优化代理模型。采用Sobol’全局灵敏度方法，量化设备效率参数对于成本、用户满意度、综合能源利用率以及电能替代率的全局灵敏度指标，用于评估综合能源设备的响应价值并且辨识影响系统状态的关键设备。通过对江苏省某商业园区进行仿真，获得了各综合能源设备效率的全局灵敏度系数，分析了不同设备效率对系统状态的影响，准确量化了综合能源设备的响应价值，验证了所提方法的有效性。

With the advancement of the dual-carbon process, integrated demand response has become one of the effective ways to solve the problem of low energy utilization efficiency and the difficult consumption of renewable clean energy. It is necessary to accurately evaluate the response value of integrated energy equipment in the integrated energy system to improve the operation control level of the system. In response to this, a comprehensive method for quantifying the value of the response of integrated energy devices based on Sobol' global sensitivity analysis has been proposed. This method can quantify their global sensitivity to the system when various influencing factors change simultaneously. Taking the minimum total operating cost as the objective function and considering multiple types of demand response, the integrated energy system generalization optimization model is established, and the integrated energy system generalization optimization model proxy model based on particle swarm optimization and backpropagation neural network is constructed. The responsive value index including cost, user satisfaction, comprehensive energy utilization rate and electric energy substitution rate are defined. Based on Sobol's global sensitivity theory, a multi-dimensional responsive value quantization method of integrated energy equipment with efficiency deviation is established to identify the key equipment that affects the system state. Through the simulation of a business park in Jiangsu Province, the first order sensitivity and total sensitivity of efficiency deviation of each integrated energy equipment are obtained, the multi-dimensional value of the integrated energy equipment is analyzed, and the effectiveness of the proposed method is verified.