Development of an incentive model for renewable energy resources using forecasting accuracy in South Korea

Abstract

This study presents an incentive model for a renewable energy source (RES) supplier, based on forecasting accuracy. The incentive model imposes responsibility of forecasting to RES suppliers by providing an additional revenue or penalty, according to forecasting accuracy. For this, a profit analysis reflecting the current environment was performed. The structure of the incentive model is designed based on the results of profit analysis. Subsequently, the price parameter was determined using an artificially generated forecasting error of the RES. In addition, the utilization of energy storage system (ESS) is analyzed, including the operation algorithm and optimal sizing, to verify the utility of the ESS when the incentive model is applied. In the case study, the actual price data and RES data from South Korea were used. The results show that the incentive model can provide a high level of profit or penalty for the RES supplier, according to the forecasting accuracy. It is also shown that the optimal capacity of the ESS based on econometrics can be reduced by more than 50% compared with the current environment, thereby reducing the burden on the ESS investment of RES suppliers.

Virtual Power Plant with Renewable Energy Sources and Energy Storage Systems for Sustainable Power Grid-Formation, Control Techniques and Demand Response

“…Uncertainty in RESs: As the number of RES integrated into the grid increases, the periodic and stochastic power output will have a certain impact on the operation of the grid. The state-of-the-art day-ahead forecasting methods still have an error rate of 10% for RES output power prediction [19].…”

Day-Ahead PV Generation Scheduling in Incentive Program for Accurate Renewable Forecasting

“…In the day-ahead market of Korea, PV sites forecast their PV generation and schedule their net output for market offerings. In order to reduce energy deviations from PV generation, incentives are provided when the difference between actual output and the generation schedule is lower than a certain level [19].…”

Experimental validation of fuzzy type‐2 against type‐1 scheme applied in DC/DC converter integrated to a PEM fuel cell system

“…Major contrasts are in terms of robustness, control signal, and capacity for tracking. Therefore, we define the error in terms of the current to be followed as Equation (1); in this expression, I L represents the measured output current of the fuel cell (which can be seen in Figure 1.…”

“…Renewable energies resources (RES) are currently a trending topic in terms of the replacement of fossil sources commonly known for their harmful consequences in the environment. 1 Fuel cells are a suitable RES device due to their efficiency which arises 60%, which is one of the highest values in comparison with photovoltaic panels (between 6% and 20%) or wind turbines (around 25%). 2,3 Currently, proton exchange membrane fuel cells (PEMFC) are an innovative technology in countries like China.…”