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

该项目的目标是发现稳健和成本效益高的发电调度，以维护智能和安全的电网，同时确保可再生能源的高利用率。其方法是研究创新的、稳健的和机会约束的优化模型以及求解方法，以提供包含间歇可再生发电的火电机组组合决策。智能优点：这个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。该方案在保证系统可靠性的同时，丰富了解决可再生能源不确定条件下电网优化问题的科学方法。此外，所提出的求解方法将导致稳健和机会约束优化的方法论创新，包括推导两阶段稳健机组组合问题的精确分离算法，以及证明两阶段机会约束随机规划的样本平均近似算法的收敛。更广泛的影响：拟议的研究对系统运营商实现成本效益和安全性的可靠性运行非常有益。它还将提供一种工具来估计存储容量需求，以保证一定百分比(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，该项目的成果将通过多种方式传播，包括期刊出版物和会议报告，代表性不足的学生将参与这项研究的所有方面。

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.