Opportunity constraint evaluation method for carrying capacity of distribution network with heat storage type electric heating access

Abstract

The chance constraint evaluation method for the bearing capacity of the distribution network with the heat storage type electric heating access comprises the steps that meteorological data and distribution network data are acquired; establishing a thermal load demand model, and extracting a typical thermal load demand curve by adopting a clustering method; establishing a heat accumulating type electric heating system and an operation control model; establishing a distribution network bearing capacity evaluation model containing heat accumulating type electric heating access, and determining chance constraint confidence according to the load adjusting capacity; obtaining distribution network basic electrical load probability distribution based on non-parametric kernel density estimation, extracting a basic load curve of the heat storage type electric heating access distribution network according to chance constraint confidence, and performing deterministic conversion on an evaluation model containing chance constraint; and solving the converted evaluation model to obtain the maximum heat supply area which can be borne by the distribution network. According to the method, the bearable heat supply area of the distribution network can be effectively increased, the utilization rate of the distribution network is improved, and reasonable evaluation of the heat storage type electric heating access scale under the current distribution network structure and demand response is achieved.

Description

technical field [0001] The invention relates to the field of distribution network planning, and is a chance constraint evaluation method for distribution network carrying capacity including thermal storage electric heating access. Background technique [0002] Regenerative electric heating has the ability to adjust the size and time transfer of power, and can actively participate in grid regulation; current research on regenerative electric heating mainly focuses on improving the consumption of renewable energy and optimizing the configuration of equipment parameters. The proposed thermal storage electric heating planning schemes do not consider the carrying potential of the distribution network. They are all modeled on the premise of meeting the planning scheme and the convenience of reconstruction and expansion. The results may deviate from the reality and affect the feasibility of the planning scheme. Therefore, it is necessary to evaluate the maximum heating area under t...

AI Technical Summary

Problems solved by technology

If the active role of users actively participating in power grid peak regulation under demand response is ignored, the evaluation results of distribution network carrying capacity will be relatively conservative, which will restrict the full utilization of distribution network resources to a certain extent.

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