随着社会经济的高速发展, 电网规模不断增大, 电网容量不断提高, 电力损耗问题日趋严重, 为了合理高效地利用电力, 对于网用电量异常的研究十分关键。针对电网用电量异常的问题, 对某城市一区域电网用电量数据进行逻辑分组聚类预处理, 并运用启发式算法构建两种针对性的启发式模型。利用从电网部署的检测仪表收集到的数据进行实验验证, 结合启发式算法进行检测, 异常用电情况下的相对异常指数较正常情况扩大6~10倍, 能够对电网的异常电量使用现象有较好的识别与检测能力, 验证了所提出方法的有效性。

Nowadays, with the rapid development of social economy, the scale of power grid is increasing, the capacity of power grid is increasing, and the problem of power loss is becoming more and more serious. In order to make rational and efficient use of power, the research on abnormal power consumption is very important. Aiming at the problem of abnormal power consumption, this paper preprocesses the power consumption data of a regional power grid logically, and uses heuristic algorithm to build two targeted heuristic models. The data collected from the detection instruments deployed in the power grid are used for experimental verification. The relative anomaly index in the case of abnormal power consumption is 6~10 times larger than that in the normal case. Combined with the heuristic algorithm, it can better identify and detect the abnormal power consumption phenomenon of the power grid, and verify the effectiveness of the proposed method.