Prediction interval of wind power using parameter optimized Beta distribution based LSTM model-Reference-Cited by-同舟云学术

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Prediction interval of wind power using parameter optimized Beta distribution based LSTM model

Published:2019-09 Issue: Volume:82 Page:105550
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Yuan Xiaohui^ORCID,Chen Chen,Jiang Min,Yuan Yanbin

Funder

National Natural Science Foundation of China

Open Fund of the State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems for China Electric Power Research Institute

Fundamental Research Funds for the Central Universities, China

Publisher

Elsevier BV

Subject

Software

Reference42 articles.

1. A new quantum inspired chaotic artificial bee colony algorithm for optimal power flow problem;Yuan;Energy Convers. Manage.,2015

2. https://worldofrenewables.com/the-top-10-countries-in-the-world-by-wind-energy-capacity/.

3. Design of a fractional order PID controller for hydraulic turbine regulating system using chaotic non-dominated sorting genetic algorithm II;Chen;Energy Convers. Manage.,2014

4. Nonlinear dynamic analysis and robust controller design for Francis hydraulic turbine regulating system with a straight-tube surge tank;Liang;Mech. Syst. Signal Process.,2017

5. Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models;Wang;Renew. Sustain. Energy Rev.,2016

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