Fine Planning Method of Power Grid Based on Principal Component Analysis and Index Correlation Degree

With the power grid development changing from high-speed to high-quality stage, the proportion of new energy increasing and the scale of power grid operation data expanding, the planning and the decision-making is becoming more and more difficult. Moreover, it is hard to deal with the big data during the high-quality development stage of power grid and the inaccuracy of grid planning brings difficulties to decision making of grid construction and investment, though the traditional grid planning method can still handle the scientific requirement of decision-making model. This paper is mainly focused on the relevance between statistical characteristics of data indicators and power grid planning. The principal component analysis method is used to reduce the dimension of data indicators, which makes the data system more efficient. Meanwhile, the project is sorted by index correlation degree method, so that the planning point is more accurate and the refinement degree of grid planning is improved.

I. Introduction

At present, the development of power grid in China is changing from a high-speed to a high-quality stage, and at the same time, also from a well-off power grid focusing on power supply reliability and power quality to a modern power grid considering economy and coordination [1 – 3]. The power grid is now entering a stage of large-scale utilization of clean energy focusing on intelligent grid [4], presenting both new features and new challenges: •

Both extreme light and heavy load problems exist in power grid, it is therefore urgent to improve the quality and efficiency of the grid;

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On the other hand, some planning districts are faced with the problem of power supply coordination during the process of grid transition;

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In addition, the efficiency problem of the power grid aroused from the expiration of the service life, the decommissioning of the used equipment and the alteration between the new and used equipment;

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The national macro energy policy is greatly supporting the development of new energy and energy storage with the proportion of new energy power increasing and the number of supporting energy storage demonstration projects adding, thus resulting the complexifying factors and heavy tasks during the planning.