Chance-Constrained and Robust Optimization for Power Systems with Intermittent Renewable Generation

间歇性可再生能源发电电力系统的机会约束和鲁棒优化

• 批准号: 1202264
• 负责人: Yongpei Guan
• 金额: $ 23.48万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-15 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1202264&HistoricalAwards=false
• 关键词: Chance; Constrained; Robust; Optimization; Power

The objective of this project is to discover robust and cost efficient power generation scheduling, in order to maintain a smart and secure power grid while ensuring high utilization of renewable energy. The approach is to study innovative robust and chance constrained optimization models along with solution methodologies to provide thermal unit commitment decisions incorporating intermittent renewable generation. Intellectual Merit: This project proposes one of the first studies on two-stage robust and chance-constrained optimization methods to solve power grid optimization problems. The proposed project will enrich scientific methods to solve power grid optimization problems under renewable generation uncertainty, while ensuring system reliability. In addition, the proposed solution approach will lead to methodology innovations for robust and chance constrained optimization, including deriving exact separation algorithms for two-stage robust unit commitment problems and proving the convergence of the sample average approximation algorithm for two-stage chance constrained stochastic programs. Broader Impacts: The proposed research is extremely beneficial for the reliability runs for system operators to achieve cost efficiency and security. It will also provide a tool to estimate the storage capacity requirement in order to guarantee a certain percentage (e.g., 80%) of electricity usage coming from renewable. In addition, the collaboration with national research labs facilitates testing real data and implementation at energy markets in short time, which will immediately benefit the society. Finally, results from this project will be disseminated through multiple means, including journal publications and conference presentations, and underrepresented students will be involved in all aspects of this research effort.

该项目的目标是发现稳健且具有成本效益的发电调度，以维持智能和安全的电网，同时确保可再生能源的高利用率。该方法是研究创新的稳健和机会约束的优化模型以及解决方案方法，以提供结合间歇性可再生能源发电的热机组承诺决策。智力优势：该项目提出了解决电网优化问题的两阶段稳健和机会约束优化方法的首批研究之一。该项目将丰富解决可再生能源发电不确定性下电网优化问题的科学方法，同时确保系统可靠性。此外，所提出的解决方案将带来鲁棒和机会约束优化的方法创新，包括推导两阶段鲁棒单元组合问题的精确分离算法，并证明两阶段机会约束随机程序的样本平均近似算法的收敛性。更广泛的影响：拟议的研究对于系统运营商的可靠性运行以实现成本效率和安全性极其有益。它还将提供一个工具来估计存储容量需求，以保证一定比例（例如 80%）的电力使用来自可再生能源。此外，与国家研究实验室的合作有助于在短时间内测试真实数据并在能源市场上实施，这将立即造福社会。最后，该项目的结果将通过多种方式传播，包括期刊出版物和会议演讲，代表性不足的学生将参与这项研究工作的各个方面。