Robust de novo programming models for supporting site selection decisions in renewable energy
针对聚光太阳能电站选址这一多目标决策难题，开发了鲁棒全新规划模型，在高度不确定性下帮助决策者选出最优位置，并以摩洛哥为例验证了有效性。
This paper develops novel robust de novo programming models to accurately select optimal locations for concentrated solar power (CSP) plants under high levels of uncertainty. The CSP selection problem is a typical uncertain multi-objective decision-making (MODM) optimal design challenge that involves conflicting environmental, societal, and economic criteria. This paper makes the following contributions: (i) it develops robust counterparts to the conventional de novo programming (DNP) model and its meta-goal programming solution procedure to address a wide range of decision-making problems under conditions of uncertainty, (ii) it proposes a robust revised multi-choice DNP model, and (iii) it contributes to ongoing debates on sustainable development and clean energy transitions by identifying optimal locations for CSP plants in Morocco. The proposed robust methodologies provide decision-makers with increased flexibility for addressing uncertainty in MODM problems, allowing them to express their level of conservatism and preferences by setting priority weights, defining aspiration levels, and merging original explicit goals into meta-goals. Finally, the hypothetical application illustrates the effectiveness of the proposed formulations and demonstrates that they can assist decision-makers in identifying the optimal locations for CSP plants in Morocco under high levels of uncertainty.