scholarly journals Scheduling method of wind power generation for electricity market using state-of-charge transition and forecast error

2019 ◽  
Vol 9 (1) ◽  
pp. 123-132 ◽  
Author(s):  
Aki Kikuchi ◽  
Masakazu Ito ◽  
Yasuhiro Hayashi
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Electricity Market ◽  
Forecast Error ◽  
Wind Power Generation ◽  
State Of Charge ◽  
Scheduling Method

Mixed GA-OPF based prioritized optimal location and rating of wind power generation in deregulated electricity market

2018 ◽  
Vol 35 (5) ◽  
pp. 5071-5075 ◽  
Author(s):  
Naveen Kumar Sharma ◽  
Anuj Banshwar ◽  
Bharat Bhushan Sharma ◽  
Yog Raj Sood ◽  
Rajnish Shrivastava
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Electricity Market ◽  
Optimal Location ◽  
Wind Power Generation ◽  
Deregulated Electricity Market

scholarly journals Weather dependent estimation of continent-wide wind power generation based on spatio-temporal clustering

2017 ◽  
Vol 14 ◽  
pp. 131-138 ◽  
Author(s):  
Bruno U. Schyska ◽  
António Couto ◽  
Lueder von Bremen ◽  
Ana Estanqueiro ◽  
Detlev Heinemann
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Electricity Market ◽  
Large Scale ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Stable Operation ◽  
Temporal Clustering ◽  
Renewable Power ◽  
Spatio Temporal

Abstract. Europe is facing the challenge of increasing shares of energy from variable renewable sources. Furthermore, it is heading towards a fully integrated electricity market, i.e. a Europe-wide electricity system. The stable operation of this large-scale renewable power system requires detailed information on the amount of electricity being transmitted now and in the future. To estimate the actual amount of electricity, upscaling algorithms are applied. Those algorithms – until now – however, only exist for smaller regions (e.g. transmission zones and single wind farms). The aim of this study is to introduce a new approach to estimate Europe-wide wind power generation based on spatio-temporal clustering. We furthermore show that training the upscaling model for different prevailing weather situations allows to further reduce the number of reference sites without losing accuracy.

Novel Synchronous Generator for Wind Power Generation

2014 ◽  
Vol 2 ◽  
pp. 170-173
Author(s):  
Tsuyoshi Higuchi ◽  
Yuichi Yokoi
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Synchronous Generator ◽  
Wind Power Generation
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