Multi-objective optimization under uncertainty for electrical energy systems with renewable energy sources, load participation, and plug-in hybrid electric vehicles

可再生能源、负荷参与和插电式混合动力汽车电能系统不确定性下的多目标优化

• 批准号: 249711-2010
• 负责人: Rosehart, William
• 金额: $ 3.13万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=570699
• 关键词: Multi; objective; optimization; under; uncertainty

Electrical Energy Systems are on the edge of a significant revolution in their operation and planning. Great interest is being directed towards increased integration of renewable or "clean" energy sources such as wind- and solar-based generation, and they are expected to be a substantial component of future electrical power systems. Power system operators and planners must address many new challenges when faced with large integration of wind- and solar-powered generation in electrical grids because of the variability associated with their power output and geographical limitations where they can be located. The challenges can lead to economic and stability problems if not properly addressed. The objectives of the proposed research program is to first develop a deeper understanding of relationships between economic cost, environment costs, and stability when incorporating stochastic elements such as wind and solar generation, and Plug-in Hybrid Electric Vehicles (PHEV). Multi-objective algorithms, appropriate for power system planning and operation, given large penetrations of stochastic elements, such as wind and solar generation and PHEV will be developed. The aim of the algorithms is to enable the development of tools that will maximize the benefit society can gain from Plug-in Hybrid Electric Vehicles and renewable energy sources such as solar and wind.

电能系统公司在运营和规划方面即将迎来一场重大革命。人们对更多地整合可再生能源或“清洁”能源产生了极大的兴趣，如风能和太阳能发电，预计它们将成为未来电力系统的重要组成部分。电力系统运营商和规划者在面临电网中风能和太阳能发电的大规模整合时，必须应对许多新的挑战，因为它们的功率输出具有变异性，而且它们所在的地理位置也有限制。这些挑战如果得不到妥善解决，可能会导致经济和稳定问题。 拟议的研究计划的目标是首先加深对经济成本、环境成本和稳定性之间关系的理解，当纳入风能和太阳能发电以及插电式混合动力汽车(PHEV)等随机因素时。多目标算法适用于电力系统的规划和运行，考虑到风能、太阳能发电和PHEV等随机因素的大渗透率。这些算法的目的是使工具的开发能够最大限度地发挥社会从插电式混合动力汽车以及太阳能和风能等可再生能源中获得的好处。