Fierce global competition and reduced profit margins are forcing many manufacturing plants to maximize their operational efficiency. This includes the consumption of energy across the plant as well as the inventory buildup. To reduce the cost of energy purchased from the electric utility, the plant operator may use the available on-site generation or reschedule the operation of one or more workstations so that the plant is less heavily operational during peak-load hours when the price of electricity is high. All this must be done while considering the interdependencies between various workstations as well as the target production level (and possible penalties in case it is not met). These factors turn the energy management problem into a constrained optimization one where the operational constraints of the workstations, the capacity limits of available energy resources, and the financial information are all taken into account. Developing such a solution is the focus of the current paper. A nonlinear mixed-integer optimization problem is formulated here that tries to optimize the performance of an industrial plant subject to the above operational and technical constraints. The problem is solved for two scenarios, when the reverse power injection by the plant is allowed and when it is not.
['Moein Choobineh', 'Salman Mohagheghi']
Optimal energy management in an industrial plant using on-site generation and demand scheduling