OPTIMAL POWER FLOW ACQUIRING METHOD FOR REGIONAL DISTRIBUTION NETWORK OF SMALL HYDROPOWER GROUPS BASED ON DEEP LEARNING

OPTIMAL POWER FLOW ACQUIRING METHOD FOR REGIONAL DISTRIBUTION NETWORK OF SMALL HYDROPOWER GROUPS BASED ON DEEP LEARNING

Disclosed is an optimal power flow acquiring method for regional distribution network of small hydropower groups based on deep learning, which specifically includes the following steps: generating required data sets by adopting continuous power flow and power flow equation calculation methods; the d...

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Hauptverfasser: LI, Yunyi, BAI, Xiaoqing, WANG, Rui, ZHU, Yun, WANG, Puming, JIA, Yujing, DIAO, Tianyi, SHANG, Qinghua, CHEN, Biyun, WEI, Shangfu, SHI, Xiaoqing, LIU, Guang, TANG, Xian, ZHU, Songyang, LI, Bin, WANG, Xinwen, WENG, Zonglong, ZHANG, Ge, ZHENG, Liqin, LI, Peijie, CHEN, Danlei
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
COUNTING
ELECTRICITY
GENERATION
PHYSICS
SYSTEMS FOR STORING ELECTRIC ENERGY
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Zusammenfassung:Disclosed is an optimal power flow acquiring method for regional distribution network of small hydropower groups based on deep learning, which specifically includes the following steps: generating required data sets by adopting continuous power flow and power flow equation calculation methods; the data set is randomly divided into training data (80 percent) and test data (20 percent); training the built convolutional neural network model with training data to learn the mapping relationship between load and generator output power; inputting test data, and directly obtaining PG and QG from the trained convolutional neural network; and solving residual variables Vi and θi with traditional power flow solver. The application can accelerate the solving speed of the optimal power flow problem with higher prediction accuracy.