In recent years, as climate change caused by CO2 emission followed by a surge in energy consumption becomes growing serious environmental concerns, there has been a significant effort by industrial sectors to reform existing systems operations to improve energy efficiency and sustainability tied to the wide-spread of demand response program and the high penetration of renewable generations. Followed by these efforts, many studies have been conducted to improve energy efficiency and sustainability in a wide range of industrial systems operations. Given this, the co-location of renewable generation integrated with battery energy storage has been considered as a promising solution that enables many industries to realize energy-efficient and sustainable operations. Considering co-located renewable generations, e.g., solar PV panels, integrated with battery energy storage, this study intends to develop a proper control policy for energy storage operations to minimize electricity cost while meeting time-varying electricity demand load in response to intermittent renewable generation and time-of-use electricity prices. Specifically, this study proposes a threshold-based control policy by determining static time-varying thresholds on the state of charge level using two-stage stochastic programming based on historical data. The proposed threshold-based control policy can be applied to energy storage operations by adjusting charging and discharging energy storage to ensure the threshold has the minimum state of charge level of energy storage.