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9.1 Multiple Conflicting Objectives

Core idea

Multiple Conflicting Objectives must be treated as a system-level decision rather than an isolated technique. For a wind turbine balancing AEP, structural mass, fatigue, control effort, capital cost, and LCOE, state what is fixed, what is optimized, what information is available, and what equations define feasibility.

The relevant quantities are plant and controller design, scenarios ss, and objective vector FF. The chapter-level formulation is

minF=[AEP,m,Dfatigue,Eu,LCOE].\min F=[-\mathrm{AEP},m,D_{\mathrm{fatigue}},E_u,\mathrm{LCOE}].

For this section, trace how the choice changes energy production, the active constraints, and the implementable engineering design. A method is useful only when its assumptions are explicit and its result answers the same system question as the baseline.

Multiobjective Pareto fronts.

Engineering interpretation

Ask three questions:

  1. Which physical, informational, computational, or economic resource changed?

  2. Which objective component or active constraint made the change valuable?

  3. Does the conclusion survive model, disturbance, initialization, uncertainty, and implementation checks?

A practical action is to define stakeholder metrics. Record units and assumptions before optimization, report component objectives and margins afterward, and verify the result using an independent calculation or higher-fidelity model.

Activity 9.1: quantify multiple conflicting objectives