Fuzzy Optimization for Power System Scheduling and Transaction Problems

9420972 LUH调度电力系统和确定公用事业之间的电力交易是电力公用事业公司面临的重要活动。这两项活动形成了一个综合问题，因为它们是通过系统需求和准备金要求相结合的。目标是提供可靠、经济和清洁的电力。这个问题变得非常重要，因为放松管制的趋势使电力市场竞争更加激烈，而且由于《清洁空气法》使公用事业运营条件更加严格。在东北公用事业服务公司的支持下，康涅狄格大学建议探索三个重要且紧密联系的领域：(L)基于拉格朗日松弛的短期调度和交易的模糊优化方法，以处理交易和燃料价格以及系统需求等不确定性；(2)长达一年的长期交易和调度，利用时间聚合的思想考虑排放约束和输电线路容量约束；(3)一类新的算法，通过探索凹的、分段光滑的和不可微的拉格朗日对偶函数的几何特征来优化它们，以提高性能。这些领域形成了一个协同研究计划，一个领域引领另一个领域，支持其他领域。我们的目标是帮助公用事业工程师基于合理的数学原理做出有效的调度和交易决策，并推动具有一般不确定性特征的系统，特别是电力系统的优化技术的最新发展和实践。***

9420972 Luh Scheduling power systems and determining inter-utility power transactions are important activities faced by electric utilities. These two activities form an integrated problem since they are coupled through system demand and reserve requirements. The objective is to supply reliable, economic and clean power. This problem is becoming very important because of the deregulation trend making the power market more competitive, and because of the Clean Air Act making utility operating conditions more stringent. The University of Connecticut, with support from Northeast Utilities Service Company, proposes to explore three vital and closely linked areas: (l) a Lagrangian relaxation based fuzzy optimization approach for short-term scheduling and transaction to handle uncertainties such as transaction and fuel prices and system demand; (2) transaction and scheduling for a long time horizon up to one year with the consideration of emission constraints and transmission line capacity constraints by using the time aggregation idea; and (3) a new class of algorithms to optimize the concave, piecewise smooth, and non- differentiable Lagrangian dual functions by exploring their geometric characteristics for improved performance. These areas form a synergistic research program, with one area leading to the next and supporting the others. Our aim is to help utility engineers make effective scheduling and transaction decisions based on sound mathematical principles, and to advance the state- of-the-art and practice of optimization techniques for systems characterized by uncertainties in general and power systems in particular. ***