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首页> 外文期刊>Annals of Operations Research >Sustainable operation-oriented investment risk evaluation and optimization for renewable energy project: a case study of wind power in China
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Sustainable operation-oriented investment risk evaluation and optimization for renewable energy project: a case study of wind power in China

机译：可持续的经营型企业投资风险评估和优化可再生能源项目 - 以中国风电为例

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摘要

Renewable energy is playing an increasingly important role in energy security and environmental protection. As China has a huge demand for renewable energy and also has abundant wind resources, it is vital that government, investors and operators work together to ensure the sustainable development of the wind energy industry. Even though China is already a leader in wind power generation with the largest installed wind power capacity in the world, it has continued to build new wind power facilities. However, due to industrial immaturity and the need for significant investment, wind power investors and operators are faced with uncertainty about the attendant risks. To achieve risk mitigation and sustainability, this paper proposes an investment risk evaluation and optimization process for Chinese wind power projects. The Monte Carlo method is first used to evaluate the investment risks, after which a multi-objective programming model is built for the optimization. A specific case in western China is examined to demonstrate the proposed methodology, with the evaluation results indicating that the project has high investment risk. Based on the case study, the key risk factors are identified and optimization suggestions given for China's wind power projects. The proposed methodology and findings contribute to research on the planning, investment and sustainable operation of renewable energy power generation projects in other areas in China.
机译：可再生能源在能源安全和环境保护方面发挥着越来越重要的作用。随着中国对可再生能源的巨大需求而且风力资源丰富，政府，投资者和运营商共同努力，以确保风能产业的可持续发展至关重要。尽管中国已经成为世界上安装的风电能力最大的风力发电领域，但它继续建立新的风电设施。但是，由于工业的不成熟和对大量投资的需求，风力投资者和运营商面临着有关服务员风险的不确定性。为实现风险缓解和可持续性，本文提出了中国风电项目的投资风险评估和优化过程。首先使用Monte Carlo方法来评估投资风险，之后建立了多目标编程模型进行了优化。检查中国西部的具体案例展示了拟议的方法，评价结果表明该项目具有高投资风险。基于案例研究，确定了中国风电项目的识别和优化建议。拟议的方法和调查结果有助于研究中国其他地区可再生能源发电项目的规划，投资和可持续运行。

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