A Scenario Optimal Reduction Method for Wind Power Time Series

By Jinghua Li, Fei Lan, Hua Wei. IEEE Transactions on Power Systems, 2016

79 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Energy Engineering and Power Technology

View Paper: https://www.semanticscholar.org/paper/5f73f07c60a082804e041057f5b8e8647eb73bed

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Alireza Zare
2. Chi Yung Chung
3. Junpeng Zhan

In Electrical and Electronic Engineering

1. Alireza Zare
2. Chi Yung Chung
3. Junpeng Zhan

In Energy Engineering and Power Technology

1. Alireza Zare
2. Chi Yung Chung
3. Junpeng Zhan

Citations in the corpus

• A Fast Solution Method for Stochastic Transmission Expansion Planning (2017, methodology): “Existing scenario reduction methods include clustering algorithms such as K-means [15], backward and forward selection algorithms [11], [12], and their variation or extension [11], [16], heuristic-based methods [14], [17], etc.”