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Computational Methods for Mixed-Integer Programs in Power Systems

电力系统混合整数程序的计算方法

基本信息

批准号：
1807260
负责人：
Javad Lavaei
金额：
$ 36万
依托单位：
University of California-Berkeley
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1807260&HistoricalAwards=false
关键词：
Computational Methods Mixed Integer Programs

项目摘要

The goal of this project is to design provably efficient computational methods for the optimal operation of power systems and to facilitate their transformation into sustainable systems. Since power systems are large-scale interconnected networks with tens of thousands of devices connected to one another via a physical infrastructure, power operators periodically solve a series of highly complex optimization problems to be able to run these systems. One major power optimization problem is unit commitment (UC), which optimizes the production schedules of the participating generators and is the backbone of the US electricity market with the value exceeding $300B annually. In addition, the emerging problem of optimal transmission switching (OTS) enables a further improvement of power systems operation by co-optimizing the interactions among the resources in the infrastructure. Since these problems are highly nonlinear, well-established optimization algorithms cannot efficiently solve them consistently and suffer from major drawbacks. This project aims to address the pressing need to develop effective techniques that are able to solve much larger power optimization problems on a much shorter time scale with a higher accuracy, compared to the current capabilities. This project leverages the underlying structures of real-world systems to develop customized computational techniques for power optimization problems with strong theoretical and practical guarantees. The focus is on the UC problem (with binary variables at the nodes of the system) and the OTS problem (with binary variables on the links of the system), since other mixed-integer power problems mathematically resemble a combination of UC and OTS. The proposed approach relies on advanced topics in graph theory, conic optimization, valid inequalities, rounding techniques, penalization methods, branch-and-bound techniques, robust optimization, and algebraic geometry. This project will advance the area of nonlinear power optimization, and its findings will significantly impact the energy management systems of power grids leading to major monetary savings and environmental benefits. This project has substantial outreach components with contributions to the programs "Engineering for Kids" and "Engineers without Borders," as well as educational activities to foster undergraduate research, engineering leadership for MS students, graduate curriculum enrichment, and cross fertilization of knowledge among different societies.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的目标是设计可证明有效的计算方法，用于电力系统的优化运行，并促进其转化为可持续发展的系统。由于电力系统是大规模互联网络，成千上万的设备通过物理基础设施相互连接，电力运营商定期解决一系列高度复杂的优化问题，以便能够运行这些系统。其中一个主要的电力优化问题是机组组合（UC），它优化了参与发电机的生产计划，是美国电力市场的支柱，每年的价值超过3000亿美元。此外，新出现的问题，最佳传输切换（OTS），使进一步改善电力系统的运行，通过共同优化的基础设施中的资源之间的相互作用。由于这些问题是高度非线性的，完善的优化算法不能有效地解决它们一致，并遭受重大缺陷。该项目旨在解决开发有效技术的迫切需求，这些技术能够在更短的时间内以更高的精度解决更大的功率优化问题。该项目利用现实世界系统的底层结构，为电力优化问题开发定制的计算技术，具有强有力的理论和实践保证。重点是UC问题（在系统的节点上具有二进制变量）和OTS问题（在系统的链路上具有二进制变量），因为其他混合整数幂问题在数学上类似于UC和OTS的组合。所提出的方法依赖于图论，圆锥优化，有效的不等式，舍入技术，惩罚方法，分支定界技术，鲁棒优化和代数几何中的高级主题。该项目将推进非线性电力优化领域，其研究结果将对电网的能源管理系统产生重大影响，从而节省大量资金并带来环境效益。该项目有大量的外展组成部分，为“儿童工程”和“无国界工程师”项目做出贡献，以及促进本科生研究，MS学生工程领导力，研究生课程丰富，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准。