An evaluation method of load identification effect under superimposed operating conditions

Abstract

The invention relates to a method for evaluating a load identification effect under a superimposed operation condition. The method comprises the following steps: 1, selecting load identification products; 2, setting a standard value of a load identification product; 3, carrying out electric appliance category interval division; 4, carrying out weighting coefficient calculation of the power consumption ratio of a single electric appliance; 5, carrying out power consumption accuracy calculation of the single electric appliance; 6, carryin gout overall accuracy calculation under the multi-electric-appliance superposition operation condition; and 7, judging whether the identification effect of the overall accuracy under the multi-electric-appliance superposition operation condition meets the requirements or not. The method adopts an error calculation principle and is simple and easy to understand; in the calculation process, through flexible coefficient allocation or index and weight deletion, accurate identification under the multi-electric-appliance superposition operation working condition is achieved; in the identification effect evaluation process, a large number of load event waveforms do not need to be adopted, numerous data acquisition is avoided, and the method is high in applicability and practicability in occasions with high timeliness such as network access detection and acceptance detection.

Description

technical field [0001] The invention relates to an evaluation method of load identification effect under superimposed operating conditions, and belongs to the technical field of intelligent power utilization. Background technique [0002] In recent years, with the development of smart grids and the continuous improvement of people's living standards, residential users' demand for precise and lean power consumption services is also growing. At present, the power grid company can only push the total household electricity consumption information to users every day, and it is difficult to monitor the electricity consumption of major electrical appliances at home, and cannot provide users with further refined energy consumption services such as home energy efficiency evaluation and home appliance working condition acquisition. [0003] Non-intrusive load identification technology is a new type of advanced measurement technology. By collecting the real-time information of the tota...

AI Technical Summary

Problems solved by technology

From the perspective of grid supply and demand interconnection applications in residential power consumption scenarios and fine-grained power consumption behavior identification applications for high-energy-consuming electrical appliances, power grid companies are concerned about the ability to identify high-energy-consuming adjustable and controllable loads, and residents are concerned about high-power consumption at home. The fine-grained electricity consumption behavior of appliances that account for a large proportion of electricity consumption, and the industry’s evaluation of multiple appliances under superimposed operating load conditions is mostly carried out by calculating the effects of each appliance and then weighting them on average. However, this effect evaluation method cannot truly give feedback. Application requirements in the above application scenarios

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