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

该项目的目标是发现强大且具有成本效益的发电调度，以保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鲁棒性和机会约束优化模型沿着与解决方案的方法，以提供热单位的承诺决策，将间歇性可再生能源发电。智力优势：本计画提出一个第一个研究两阶段强健与机会约束最佳化方法来解决电力网最佳化问题。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导致方法创新的鲁棒和机会约束优化，包括推导两阶段鲁棒机组组合问题的精确分离算法和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性。更广泛的影响：拟议的研究是非常有益的系统运营商的可靠性运行，以实现成本效益和安全性。它还将提供一个工具来估计存储容量需求，以保证一定的百分比（例如，80%的电力来自可再生能源。此外，与国家研究实验室的合作有助于在短时间内测试能源市场的真实的数据和实施，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工作的各个方面。

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.