Assess students' ability to formulate and solve a constrained optimization problem to select installed capacities of renewable technologies and storage for a small town so as to minimize combined lifecycle cost and CO2 emissions over a year with seasonal (monthly/weekly or hourly) demand and generation profiles. Students should define decision variables, construct a weighted objective function (cost + emissions), set constraints (time-step energy balance, capacity limits, storage charging/discharging dynamics, reliability/reserve or unmet-demand limits, non-negativity), choose an appropriate solution approach (LP/MIP or heuristic), specify required data and assumptions (generation profiles, demand seasonality, costs, emission factors), run a baseline optimization, perform sensitivity analysis on weightings, storage size, and technology costs, and interpret trade-offs and policy implications in results and recommendations.