Contingency Constrained Optimal Power Flow For Deregulated Electricity Markets

电力行业的放松管制将需要动态最优功率流（OPF）算法，这些新工具可以在一个时间范围内有效地安排电力系统的运行，同时包括输电和配电成本、输电线路限制、发电斜坡率限制、能源约束、价格响应负荷和一长串运行突发事件。在放松管制的环境下，输电和配电成本和线路限制将会很大，因为第三方输电系统在满负荷或接近满负荷运行。坡道限制和能量约束将控制负载跟随和峰值支持期间在负荷的大变化。活跃的电力现货市场将导致负荷波动，例如，大型工业客户会改变生产计划，以捕捉较低的能源价格。所有这些都必须在一个安全的操作环境中进行，该环境可以有效地重新安排以纠正一系列突发事件。提出的研究将扩展经典的静态OPF工具，以纳入所有这些问题。根据以往在机组承诺、经济调度和各种非线性优化技术方面的经验，作者将开发一种基于内部点的非线性规划方法来实现动态OPF，该方法包含了重新调度和价格响应负载。开发这些工具的关键思想是约束松弛和问题简化来控制问题的大小，使用拉格朗日松弛来解耦斜坡速率约束（相对于全时间耦合问题的直接解），以及诸如人工变量之类的技术来适应不可行性。

ECS-9810288 Clements Deregulation of the electric power industry will require dynamic optimal power flow (OPF) algorithms, new tools that can efficiently schedule power system operation over a time horizon while including transmission and distribution costs, transmission line limits, generation ramp rate limits, energy constraints, price-responsive loads, and a long list of operational contingencies. In the deregulated environment, transmission and distribution costs and line limits will be significant because of wheeling through third-party transmission systems operating at or near capacity. Ramp limits and energy constraints will control load following and peak support during periods of large changes in load. The active electricity spot market will cause load fluctuations as large industrial customers, for example, shift productions schedules to capture lower energy prices. All must be accommodated within a secure operating environment that can efficiently reschedule to correct for a range of contingencies. The proposed research will extend the classic static OPF tool to incorporate all of these issues. Drawing on prior experience with unit commitment, economic dispatch, and a variety of nonlinear optimization techniques, the proposers will develop an interior-point-based, nonlinear programming approach to dynamic OPF that incorporates rescheduling and price-responsive loads. Key ideas in the development of these tools are constraint relaxation and problem reduction to control problem size, the use of Lagrangian relaxation to decouple ramp rate constraints (vis-a-vis direct solution of the full time-coupled problem), and techniques such as artificial variables to accommodate unfeasibility.