Development of One Day-Ahead Renewable Energy Generation Assessment System in South Korea

Abstract

This paper proposes a probabilistic generation assessment model of renewable energy generators(REGs) considering uncertainty of resources, mainly focused on Wind Turbine Generator(WTG) and Solar Cell Generator(SCG) which are dispersed widely in South Korea The proposed numerical analysis method assesses the one day-ahead generation by combining equivalent generation characteristics function and probabilistic distribution function of wind speed(WS) and solar radiation(SR) resources. The equivalent generation functions(EGFs) of the wind and solar farms are established by grouping a lot of the farms appropriately centered on Weather Measurement Station(WMS). First, the EGFs are assessed by using regression analysis method based on typical least square method from the recorded actual generation data and historical resources(WS and SR). Second, the generation of the REGs is assessed by adding the one day-ahead resources forecast, announced by WMS, to the EGFs which are formulated as third order degree polynomials using the regression analysis. Third, a Renewable Energy Generation Assessment System(REGAS) including D/B of recorded actual generation data and historical resources is developed using the model and algorithm predicting one day-ahead power output of renewable energy generators.

Probabilistic generation assessment system of renewable energy in Korea

“…(2) A × SW 3 bi angle should be considered for applying actual SR as in (8). [10] where Additionally, the solar radiation depends on hourly sun position during one day as shown in Figure 4.…”

“…The time solar angle should be considered for applying actual SR as in (9). Therefore, the ideal solar radiation, which is defined as maximum solar radiation value under the climate condition, should be adjusted using the two solar angles which are daily solar angle and hourly solar angle as in (10). 3.…”