Transformer substation optimization site selection method based on gravity center regression and particle swarm hybrid algorithm

Abstract

The invention discloses a transformer substation optimization site selection method based on gravity center regression and a particle swarm hybrid algorithm. The method is suitable for optimizing andplanning a site selection and volume determination scheme of a transformer substation. The method specifically comprises the steps of firstly determining the number n of substations needing to be newly built in a power grid, then dividing load nodes in the power grid into n load districts by adopting a gravity center regression algorithm, obtaining position coordinates and supplied loads of the substations for supplying power to the load districts, and initializing the positions of particles by taking the position coordinates and the supplied loads as initial values of a particle swarm algorithm; and then taking the minimum global load moment as a target fitness value, optimizing substation positions and supplied loads by adopting a particle swarm algorithm to obtain optimized n substationpositions and supplied loads, and finally solving the substation capacity of each substation according to a constraint relationship between the substation capacity of the substation and the suppliedloads. The calculation result of the design has good accuracy, stability and optimization effect.

Description

technical field [0001] The invention belongs to the field of power grid planning, and in particular relates to a substation optimal site selection method based on a center of gravity regression and a particle swarm hybrid algorithm. Background technique [0002] The site selection and capacity determination of substations is an important link in power grid planning and construction. It is based on the results of space load forecasting and comprehensively considers the geographical location, power supply capacity and economic constraints of substations, and plays an important role in power grid construction, layout and investment. important role. At present, the site selection of substations is mainly based on the work experience of designers. As the grid structure becomes more and more complex, more and more factors need to be considered, and the work efficiency and accuracy of substation site selection need to be improved. With the current information system construction a...

AI Technical Summary

Problems solved by technology

For example, the particle swarm algorithm, when used in the calculation of substation site selection, the conventional particle swarm algorithm may fall into local optimum or premature misunderstanding, and it is difficult to achieve global optimization. At the same time, the randomness of the algorithm will also lead to problems such as unstable calculation results.

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