In this study, a methodology for calculating representative regional photovoltaic power generation in 24 hours of the year was developed to expand renewable energy cloud platform functionality of Korea Energy Agency. To compute regional photovoltaic power generation in 24 hours of the year, the monthly regional representative insolation in 24 hours was calculated, as well as their probability distributions. Accordingly, the monthly regional photovoltaic power generation in 24 hours was calculated, and the expected value of regional photovoltaic power generation in 24 hours of the year was derived. Subsequently, the representative regional photovoltaic power generation in 24 hours of the year was calculated. Representative regional photovoltaic power generation in 24 hours of the year calculated in this study can be applied to distributed energy resources to resolve the output variability of renewable energy. The obtained result can be used for distributed resource operation planning, such as estimating the regional Energy Storage System capacity. Currently, the Korea Energy Agency's renewable energy cloud platform provides users only with information about solar installation. However, the function of the renewable energy cloud platform can be expanded by applying the results obtained in this study to the distributed resource operation planning.
In this study, we calculated regional optimal energy storage system (ESS) capacity to maximize customer profits for the grid-connected PV-ESS system. We used the results of calculating the photovoltaic (PV) power generation in 24 hours, representing a year in each region, with the data from the Renewable Energy Cloud Platform operated by the Korea Energy Agency. In addition, to increase the utilization of the Renewable Energy Cloud Platform, we proposed to provide information to users on ESS installation capacity by applying the method of calculating the regional optimal ESS capacity developed in this study to the platform. As a result, when PV power generation companies install the grid-connected PV-ESS systems in each region, they select and install the most economical ESS capacity. The results of this study is expected to expand the supply of renewable energy and ESS.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citationsβcitations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.