Stochastic Optimization Methodologies and Applications in Renewable Energy

可再生能源中的随机优化方法及其应用

• 批准号: 386474-2012
• 负责人: Chen, Shengyuan
• 金额: $ 1.6万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=595945
• 关键词: Stochastic; Optimization; Methodologies; Applications; Renewable

We will study new computer algorithms to control the total electric power output from the renewable resources and traditional thermal generators. The work is important since Canada needs stable and economic electric power supply. The increased renewable energy is intermittent by its nature; hence we need to study new algorithms to stabilize the total output. Not only the electric industry will benefit from the new study, but also every user of the electric power. This is because the new study can help the industry to supply more energy securely and economically. We expect to deliver new and advanced algorithms, which optimize the operations of thermal and renewable generators. The study will advance the field of energy power, and the field of optimization theory. Energy industry is a very important sector of Canada economy, and this study will further enhance Canada's leading position in the world energy market.

我们将研究新的计算机算法，以控制可再生资源和传统火力发电机的总发电量。这项工作很重要，因为加拿大需要稳定和经济的电力供应。增加的可再生能源本质上是间歇性的;因此我们需要研究新的算法来稳定总产量。这项新的研究不仅使电力工业受益，而且使每一个电力用户受益。这是因为新的研究可以帮助该行业安全和经济地提供更多的能源。我们希望提供新的和先进的算法，优化热力和可再生能源发电机的运行。该研究将推动能源动力领域和优化理论领域的发展。能源产业是加拿大经济中非常重要的部门，本研究将进一步提升加拿大在世界能源市场的领先地位。