Dispatchable Electric Vehicle Capacity Prediction Model for Power Systems Based on Improved LSTM Algorithm-Reference-Cited by-同舟云学术

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Dispatchable Electric Vehicle Capacity Prediction Model for Power Systems Based on Improved LSTM Algorithm

Published:2024-05-24 Issue: Volume: Page:1601-1604
ISSN:
Container-title:2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)
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Author:

Liu Guojing¹,Shi Jing²,Li Zesen²,Liu Bailiang¹,Ge Yi²,Huang Xiaoshu³

Affiliation:

1. State Grid Jiangsu Electric Power Co., Ltd,Nanjing,China,210000

2. State Grid Jiangsu Electric Power Co., Ltd. Economic and Technical Research Institute,Nanjing,China,210000

3. Jiangsu Muke Shichuang Technology Co., Ltd,Nanjing,China,210000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10574856/10574899/10575648.pdf?arnumber=10575648

Reference7 articles.

1. Improving Forecasting Accuracy of Project Earned Value Metrics: Linear Modeling Approach

2. Deep-Learning-Based Probabilistic Forecasting of Electric Vehicle Charging Load With a Novel Queuing Model

3. Assessment of hybrid transfer learning method for forecasting EV profile and system voltage using limited EV charging data

4. Analysis of the Relative Operating Characteristic and Economic Value Using the LAPS Ensemble Prediction System in Taiwan

5. Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging

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