Proactive Automation of a Batch Manufacturer in a Smart Grid Environment

Modern power companies are facing increasing technical challenges with resource management during peak demand intervals that stem from fluctuating demand and increased reliance on solar and wind generation. The peak power problem is partially addressed in some rate structures by applying a demand charge on users' bills, thus creating an incentive for users to reduce their peak demand. Solutions to the peak power issue are largely being addressed on the production side of the power grid (i.e., power plants) through use of fast-ramping peaking power plants. However, solutions are not common on the demand side of the grid, particularly in the manufacturing sector. Other studies have proposed that an ideal solution would involve a smart grid that utilizes automated response and prediction on both ends of the grid. This article analyzes how batch process facilities are well suited to respond to power grid changes as they function in a manner that allows for variable production scheduling. Additionally, the utilization of onsite energy storage is discussed for how it can be managed in order to reduce peak demand at necessary times. Data was analyzed from an industrial-scale bakery that has real-time electrical monitoring devices installed on major electrical systems in the factory. The simulation consisted of the glycol coolant system, the facility's chiller, glycol storage tank, three bread dough mixers, and a fermenter room that includes product hold up. Through model simulation, combined with the implementation of the automation algorithms, a smart grid environment was simulated for the factory, and its results were analyzed. Among all operating schemes considered, the grid-coincident peak reduction, relative to normal operating conditions of the facility, was chosen for smart chilling, mixer staggering, and the combination of the two were 10, 29, and 36 %, respectively.