基于证据理论与云模型的火电机组节能减排绩效综合评价

Energy Saving and Emission Reduction Evaluation of Thermal Power Units Based on Evidence Theory and Cloud Model

虽然目前火电机组各项节能减排指标都已有了明确规定,但依然没有形成一种公认合理的机组整体节能减排绩效评判方法。为解决这一问题,提出一种基于证据理论与云模型的火电机组节能减排绩效综合评价方法。首先从“节能”与“减排”两个方面,选择合适的评价指标建立火电厂节能减排指标体系;之后用云模型取代传统的模糊隶属函数,确定各个指标不同评级的信度函数分配;最后用一种基于动态权重系数的证据理论对各评价指标进行多维信息的融合,取融合结果中信任度最大的评级作为最终的综合评价结果。实例分析表明,该方法能很好地兼容评价过程中的模糊性及随机性,具有一定的参考价值。

Although various energy saving and emission reduction indicators of thermal power units have been clearly stipulated,there is still no recognized and reasonable comprehensive evaluation method for the overall performance of units.In order to solve this problem,we proposed a comprehensive evaluation method based on evidence theory and cloud model for energy saving and emission reduction performance of thermal power units.First,from the two aspects of"energy saving"and"emission reduction",we selected appropriate evaluation indicators to establish an energy saving and emission reduction indicator system of thermal power units.Then we used the cloud model to replace the traditional fuzzy membership function to determine the basic probability assignment of different ratings for each indicator.Finally,the improved evidence theory based on dynamic weight coefficient was used to integrate the multi-dimensional information of each evaluation index.The highest credit rating was taken as the final evaluation result.The case analysis shows that the method is compatible with the ambiguity and randomness in the evaluation process,and has certain reference value.