Abstract
Economic transformation creates a new environment for grid investment. In the situation of high quality development, the traditional investment scale prediction model is no longer applicable. Aiming at the problems of single parameter of grid-driven investment scale prediction model and poor linear fitting accuracy, a provincial medium- and long-term investment scale prediction model based on support vector machine was proposed. Aiming at the single parameter and poor line fitting accuracy of the grid-driven investment scale prediction model under the new situation, the new environment, new directions and new requirements for grid investment are analyzed. Based on the support vector machine algorithm, a medium-and long-term investment scale prediction model for provincial grids based on support vector machines is proposed. The scale of provincial grid investment is expected from 2019 to 2022. The empirical results show that the prediction model constructed in this paper is effective and feasible. It is of great significance to explore the prediction model of medium and long-term investment scale of power grid enterprises in the new situation.
Highlights
Introduction trendIn this context, a group of energy storage, distributed energy, and comprehensive energy, deeplyWith the continuous deepening of the new round of power system reform, the research's focus on investment management of power grid companies has shifted from investment efficiency, finanare the samplecing management, investment risk, to the direction of macro decision-making and precise investment
This paper sorts out the index system of external driving factor for power grid investment from four dimensions, namely power demand factor, power grid security factor, energy transition factor and technological innovation factor
A power grid investment scale prediction model was constructed and the following conclusions were obtained through empirical analysis: (1) This paper analyzes the external environment of power grid investment
Summary
This paper sorts out the index system of external driving factor for power grid investment from four dimensions, namely power demand factor, power grid security factor, energy transition factor and technological innovation factor.
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