Dynamic equivalence method for medium and small hydropower clusters

Abstract

The invention discloses a dynamic equivalence method for medium and small hydropower clusters. The method comprises: obtaining the running measurement information of the target small and medium hydropower clusters; establishing a dynamic equivalence model for the target small and medium hydropower clusters; using the adaptive control parameter improved differential evolution algorithm to identify the parameters of the dynamic equivalence model; and substituting the model parameters into the dynamic equivalence model to complete the dynamic equivalence model of the target small and medium hydropower clusters. According to the invention, the method selects the equivalence model as the third-order generator parallel static ZIP load model, selects the active power, the reactive power, the voltage and the frequency of the small and medium-sized hydropower cluster transmission line phase measurement data as the input data, and adopts the adaptive control parameter improved differential evolution algorithm to identify the parameters of the dynamic equivalence model. With relatively high dynamic responding precision and the well-stable parameter identification algorithm, the method could be applied for the equivalence parameter identification and calculation of medium and small hydropower clusters and has good engineering application value.

Description

technical field [0001] The invention specifically relates to a dynamic equivalent method for small and medium hydropower clusters. Background technique [0002] Due to the flexibility, convenience and environmental friendliness of small and medium-sized hydropower, the development of small and medium-sized hydropower stations in areas rich in hydropower has been relatively rapid in recent years. The individual capacity of these units is small, and the impact of each unit on the power grid can be ignored. However, with the gradual increase of its grid-connected scale, the impact of the entire small and medium-sized hydropower group on the stability and safe operation of the power system will be difficult to ignore. Since the parameters of each unit and line are difficult to obtain, it is very difficult to establish a detailed model of small and medium hydropower clusters including all hydropower units; moreover, due to the high order of the detailed model, even if the detaile...

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Problems solved by technology

There are literature (Bowei Hu, Jingtao Sun, LijieDing, Xinyu Liu, Xiaoru Wang, "Dynamic Equivalent Modeling for Small and Medium Hydropower Generator Group Based on Measurements," Energy, vol.9.no.5, pp.1-14, May 2016 .) The small and medium-sized hydroelectric power group is equivalent to the generator parallel load model, and based on the measured data, the model parameters are identified by using the dynamic multi-swarm particle swarm optimization (DMS-PSO) algorithm, but the dynamic response characteristics of the equivalent model are in the After the second pendulum, the error is large, and its parameter identification method is not stable

Particle swarm optimization is widely used in the field of parameter identification, but the parameter identification algorithm based on particle swarm optimization is not accurate in some scenarios

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