A Dynamic Optimization Framework with Model Predictive Control Elements for Long Term Planning of Capacity Investments in a District Energy System

• Main Author: Mojica Velazquez, Jose Luis
• Format: Others
• Published: BYU ScholarsArchive 2013
• Subjects: heating; network; capacity; expansion; boilers; energy; controller; optimal; timing; formulation; economic; dependent; Chemical Engineering
• Online Access: https://scholarsarchive.byu.edu/etd/3886; https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=4885&context=etd

The capacity expansion of a district heating system is studied with the objective of evaluating the investment decision timing and type of capacity expansion. District energy is an energy generation system that provides energy, such as heat and electricity, generated at central locations and distributed to the surrounding area. The study develops an optimization framework to find the optimal investment schedule over a 30 year horizon with the options of investing in traditional heating sources (boilers) or a next-generation combined heat and power (CHP) plant that can provide heat and electricity. In district energy systems, the investment decision on the capacity and type of system is dependent on demand-side requirements, energy prices, and environmental costs. The main contribution of this work is to formulate the capacity planning over a time horizon asa dynamic optimal control problem. In this way, an initial system configuration can be modified by a 'controller' that optimally applies control actions that drive the system from an initial state to an optimal state. The optimal control is a model predictive control (MPC) formulation that not only provides the timing and size of the capacity investment, but also guidance on the mode of operation that meets optimal economic objectives with the given capacity.