# Dispatchable Substation for Operation and Control of Renewable Energy Resources
With the increasing deployment of renewable sources, the operation of transmission systems becomes increasingly complex. Therefore, to minimize uncertainty and complexity of generation from distributed renewable sources, hierarchical control can be implemented. In [6], the author proposed a hierarchical control algorithm for distribution systems with renewable resources. A substation is an ideal unit as a mid-level management center in hierarchical control. Furthermore, ESSs can be added to make groups of distributed renewable sources dispatchable, which can be performed at the substation level [7]. There are several studies and field demonstrations in developing ESS technologies to integrate variable renewable sources. Most representative use cases of ESS are for wind farm applications, such as Duke Energy BESS project in Nottrees, Texas, or SCE wind energy storage project in Tehachapi, California [8]. In South Korea, more than 1.8 GWh of BESS are installed voluntarily by renewable generator owners to receive government incentives for shifting generation output [9]. Most of the ESS projects for renewable integration were designed to provide reserve capacity or shifting generation output. No project or demonstration is found for use of ESS for forecast error reduction. Optimal usage of ESSs at substation may result in an increased use of renewable energy and reduced intermittency. However, the high capital cost and uncertain economic returns make the deployment of ESSs unattractive. Thus, many researchers have worked on optimization problems to find the proper size and operation of ESSs. Mathematical programming and heuristic methods are popular for optimal sizing and siting of ESSs [10]. In case of utilizing ESSs for renewable energy in a predefined location, an analytical method can be applied by making use of statistical data analysis, such as historic wind or solar data [11; 12]. Since wind and solar generation are highly stochastic, probabilistic method for ESSs sizing is suggested in many literatures. In [13], statistical behavior of the forecast error and ESSs sizing are analyzed for several forecast methods. In [14], the author suggested an optimal sizing method of ESS that operated under a model predictive control (MPC) scheme. The MPC is designed to consider forecast uncertainties within one-hour prediction horizon. When considering the ESSs in the substation for reduction of uncertainty by interconnected PV or wind, the relationship between forecast error and size of ESS needs to be analyzed under various combinations of renewable generator. Very few research studies are focused on defining these relationships. In [15; 16], they suggested a method to build a spatial correlation of forecast errors in wind and load forecast using copula theory. In [17], the authors proposed a joint probability distribution model to define temporal correlation of hourly day-ahead short-term wind power forecast error for optimal ESS sizing, and yet the direct relationship between forecast error and ESSs capacity for uncertainty reduction is not defined. This study proposes the concept of \"Dispatchable Substation\" (DSS) and describes its operation for interconnection of renewable energy sources. The relation between renewable forecast data and error is analyzed to find the optimal size of ESSs in the proposed substation. The key role of the proposed substation is to minimize uncertainties from interconnected renewable generators, to receive dispatch orders from TSOs. The entire substation and the interconnected RES are considered as a single generator unit with controllability. Additionally, the DSS provides emergency responses, such as inertia response, governor response, and reactive power support, similar to those of a synchronous generator.