Research on Investment Forecast of Distribution Based on BP Neural Network

Kang, Yanfang; Guo, Xiaofeng; Li, Dapeng; Li, Xuyang

doi:10.1109/icaica50127.2020.9181886

Cited by 1 publication

(1 citation statement)

References 2 publications

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“…At present, scholars at home and abroad do not have much research on power grid investment prediction, and most of them use artificial intelligence and statistical methods for prediction, such as references [42][43][44][45][46][47]. The commonly used methods for forecasting power grid investment demand are shown in Fig.…”

Section: Power Grid Investment Demand Forecast Methodsmentioning

confidence: 99%

A Survey on Investment Demand Assessment Models for Power Grid Infrastructure

Chen

et al. 2021

IEEE Access

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The investment demand forecast of the power grid is the further deepening of grid supply and demand management. Under the current reform of the power system in China, we are facing new challenges in analyzing and predicting the investment demand of the power grid. Firstly, the influencing factors of power grid investment demand from both internal and external aspects are analyzed in this paper. Then the selection principles of power grid investment demand factors by domestic and foreign scholars are summarized in this paper. Based on the above content, the forecast indicators and selection methods of domestic and foreign scholars on power grid investment demand are summarized in this paper. The common influencing factor mining algorithms are the grey correlation analysis, the core principal component analysis, and their combination methods. Moreover, the research status of domestic and foreign scholars in power grid investment demand, data mining technology, and forecasting technology is investigated. The current situation of power grid investment demand in China and the common forecasting methods are also elaborated. Finally, the key issues that need to be solved in future research on the investment demand of power grid infrastructure are summarized in this paper. This review will help power utilities find problems in power grid infrastructure investment demand and guide the future investment demand calculations of power utilities. INDEX TERMS Grid infrastructure, power grid investment, demand forecasting, indicator system, power utilities Power Demand Forecasting Methods Classic Forecasting Methods Traditional Forecasting Methods Modern Forecasting Methods Unit Consumption Method Power Elasticity Coefficient Method Per Capita Electricity Consumption Conversion Algorithm

show abstract

Section: Power Grid Investment Demand Forecast Methodsmentioning

confidence: 99%

A Survey on Investment Demand Assessment Models for Power Grid Infrastructure

Chen

et al. 2021

IEEE Access

View full text Add to dashboard Cite

show abstract

Research on Investment Forecast of Distribution Based on BP Neural Network

Cited by 1 publication

References 2 publications

A Survey on Investment Demand Assessment Models for Power Grid Infrastructure

A Survey on Investment Demand Assessment Models for Power Grid Infrastructure

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