Power grid static voltage stability margin probability prediction method considering new energy uncertainty
The invention relates to a power grid static voltage stability margin probability prediction method considering new energy uncertainty. The power grid static voltage stability margin probability prediction method specifically comprises the following steps: constructing a power prediction error model...
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| creator | XU YEYAN WANG XINYING WANG JIANFENG QI JINSHAN LIAO SIYANG PU TIANJIAO YAO LIANGZHONG |
| description | The invention relates to a power grid static voltage stability margin probability prediction method considering new energy uncertainty. The power grid static voltage stability margin probability prediction method specifically comprises the following steps: constructing a power prediction error model of new energy represented by wind power and photovoltaic; constructing a wind power and photovoltaic static scene generation model based on a prediction error model and Monte Carlo sampling; constructing a single-scene static voltage stability margin prediction method based on deep learning; and generating a power grid static voltage stability margin probability prediction result considering the new energy uncertainty by adopting a kernel density estimation method. The method has the following advantages: on one hand, the scene generation model based on the new energy prediction error considers the randomness of new energy power generation, and the obtained static voltage stability margin probability distribution |
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The power grid static voltage stability margin probability prediction method specifically comprises the following steps: constructing a power prediction error model of new energy represented by wind power and photovoltaic; constructing a wind power and photovoltaic static scene generation model based on a prediction error model and Monte Carlo sampling; constructing a single-scene static voltage stability margin prediction method based on deep learning; and generating a power grid static voltage stability margin probability prediction result considering the new energy uncertainty by adopting a kernel density estimation method. 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The power grid static voltage stability margin probability prediction method specifically comprises the following steps: constructing a power prediction error model of new energy represented by wind power and photovoltaic; constructing a wind power and photovoltaic static scene generation model based on a prediction error model and Monte Carlo sampling; constructing a single-scene static voltage stability margin prediction method based on deep learning; and generating a power grid static voltage stability margin probability prediction result considering the new energy uncertainty by adopting a kernel density estimation method. The method has the following advantages: on one hand, the scene generation model based on the new energy prediction error considers the randomness of new energy power generation, and the obtained static voltage stability margin probability distribution</abstract><oa>free_for_read</oa></addata></record> |
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| language | chi ; eng |
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| subjects | CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRICITY GENERATION PHYSICS SYSTEMS FOR STORING ELECTRIC ENERGY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Power grid static voltage stability margin probability prediction method considering new energy uncertainty |
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