Abstract
AbstractThis paper proposes probabilistic generation assessment system introduction of renewable energy generators. This paper is focused on wind turbine generator and solar cell generator. The proposed method uses an assessment model based on probabilistic model considering uncertainty of resources (wind speed and solar radiation). Equivalent generation function of the wind and solar farms are evaluated. The equivalent generation curves of wind farms and solar farms are assessed using regression analysis method using typical least square method from last actual generation data for wind farms. The proposed model is applied to Korea Renewable Generation System of 8 grouped 41 wind farms and 9 grouped around 600 solar farms in South Korea.
Highlights
This paper proposes probabilistic generation assessment system introduction of renewable energy generators
The proposed method uses an assessment model based on probabilistic model considering uncertainty of resources
The proposed model is applied to Korea Renewable Generation System of 8 grouped 41 wind farms and 9 grouped around 600 solar farms in South Korea
Summary
With the Fukushima nuclear disaster in April 2011 and the effects of global warming, the proportion of traditional generators (load dispatching generator) is reducing worldwide, and the dependence on generators using renewable energy is increasing by gradation to replace them. Supply capacities of load dispatching generators can be estimated and controlled and are very effectively used for estimation of margin of power, maintenance planning and power feeding, but for generators using new and renewable energy among NCCGs, it is hard to estimate supply capacities objectively, due to the uncertainty of natural resource supply and power output.[9]
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