Optimal Design of a Small-Scale Multi-Energy Hub for a Sustainable Campus Microgrid

This research project aims to develop and analyze an optimization model for a small-scale multi-energy hub designed to serve a university campus, residential block, or rural facility. The focus is on identifying the optimal configuration and operation of local energy technologies—such as photovoltaic (PV) systems, battery storage, heat pumps, and potentially combined heat and power (CHP) units—to meet electricity and thermal demands in a cost-effective and sustainable way. The project will formulate and solve a linear or mixed-integer linear programming (LP/MILP) model that minimizes the total cost and/or carbon emissions of the system while satisfying energy demands and operational constraints. The model will simulate the hub’s operation over a selected period (e.g., a typical summer week or month), considering different technology options, renewable energy availability, and energy pricing scenarios. By the end of the project, the student will produce a clear analysis of optimal technology selection, investment sizing, and operational strategy, and assess how changes in key parameters (e.g., electricity tariffs, solar availability) impact system performance.
Objectives:
Design a simplified multi-energy system layout.
Develop and solve an optimization model using GAMS, Pyomo, or Excel Solver.
Evaluate trade-offs between cost, emissions, and self-sufficiency.
Analyze scenarios with different renewable potentials and tariffs.
Provide actionable insights for future expansion of the energy hub.
Expected Outcomes:
A working optimization model of a small-scale energy hub.
Scenario analysis results and performance comparison.
A final project report (10–15 pages) and presentation summarizing methodology and findings.
Ideal Candidate:
Background in energy systems, engineering, or operations research.
Familiarity with optimization tools (e.g., GAMS, Pyomo, Excel Solver).
Interest in renewable energy and energy system planning.