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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Sustainable Optimization for China’s Hydropower Project Investment Portfolio Using Multiobjective Decision Analysis
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Sustainable Optimization for China’s Hydropower Project Investment Portfolio Using Multiobjective Decision Analysis

机译：中国水电项目投资组合的可持续优化使用多目标决策分析

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摘要

The development of renewable energy becomes increasingly important because of exhaustion of fossil energy. Hydropower is one of the most important ways to generate electricity from renewable energy because of its relatively stable output among them. However, hydropower project development with some inherent characteristics is highly susceptible to social and natural environments, which complicates the investment process. For this purpose, this paper proposes a feasible comprehensive optimization model of portfolio investment from the perspective of sustainable development, describing the tradeoff relationship between economic, social, and ecological factors. As a hybrid uncertain NP-hard optimization problem, there are three critical challenges: (1) achieving comprehensive balance between economy, society, and ecology; (2) identifying available multiple conflicting objectives and reasonable constraints; (3) analysing the hybrid uncertain environment. Therefore, a practical problem-oriented multiobjective decision analysis model is established. Then, a multiobjective adaptive particle swarm optimization algorithm is designed to solve the model. Finally, a case study is carried out to verify the practicality of the model and the effectiveness of the improved algorithm. The result demonstrates that the model can be applied as a useful decision-making tool for decision-makers in sustainable hydropower project development.
机译：由于化石能量耗尽，可再生能源的发展变得越来越重要。由于其相对稳定的输出，水电是从可再生能源产生电力的最重要方法之一。然而，水电项目开发具有一些固有的特征，非常容易受到社会和自然环境的影响，这使得投资过程复杂化。为此目的，本文从可持续发展的角度提出了投资组合投资的可行综合优化模型，描述了经济，社会和生态因素之间的权衡关系。作为一个杂交不确定的NP - 硬度优化问题，存在三个危急挑战：（1）在经济，社会和生态学之间实现全面的平衡; （2）识别可用多重冲突目标和合理的限制; （3）分析杂交不确定环境。因此，建立了实际的面向问题的多目标决策分析模型。然后，设计了一种多目标自适应粒子群优化算法来解决模型。最后，执行案例研究以验证模型的实用性和改进算法的有效性。结果表明，该模型可以应用于可持续水电项目开发中的决策者的有用决策工具。

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