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An optimization-based algorithm for scheduling hydrothermal power systems with cascaded reservoirs and discrete hydro constraints

机译:基于优化的水库级联离散水力约束热电调度算法

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摘要

An optimization-based algorithm is presented for the short-term scheduling of hydrothermal power systems using the Lagrangian relaxation technique. This paper concentrates on the solution methodology for hydro subproblems with cascaded reservoirs and discrete hydro constraints. Continuous reservoir dynamics and constraints, discontinuous operating regions, discrete operating states and hydraulic coupling of cascaded reservoirs are considered in an integrated fashion. The key idea is to substitute out the reservoir dynamics and to relax the reservoir level constraints by using another set of multipliers, making a hydro subproblem unit-wise and stage-wise decomposable. The optimal generation level for each operating state at each hour can be obtained simply by minimizing a single variable function. Dynamic programming is then applied to optimize the operating states across the planning horizon with a small number of well structured transitions. A modified subgradient algorithm is used to update multipliers. After the dual problem converges, the feasible solution to the hydropower subsystem is obtained by using a network flow algorithm, with operating states obtained in the dual solutions, and possibly adjusted by heuristics. Numerical testing based on practical system data sets show that this method is efficient and effective for dealing with hydrothermal power systems with cascaded reservoirs and discrete hydroelectric constraints.
机译:提出了一种基于优化的算法,采用拉格朗日松弛技术对水火发电系统进行短期调度。本文集中讨论具有级联水库和离散水力约束的水力子问题的解决方法。综合考虑了连续油藏动力学和约束,不连续工作区域,离散工作状态和级联油藏的水力耦合。关键思想是通过使用另一组乘数来替代水库动力学并放宽水库水位约束,使水力子问题在单位和阶段都可分解。只需将单个变量函数最小化,即可获得每小时每个运行状态的最佳发电量。然后应用动态编程以通过少量结构良好的过渡来优化整个计划范围内的运行状态。修改后的次梯度算法用于更新乘数。对偶问题收敛后,使用网络流算法获得水电子系统的可行解,并在对偶解中获得运行状态,并可能通过启发式方法进行调整。基于实际系统数据集的数值测试表明,该方法对于处理具有级联水库和离散水电约束的热电系统是有效的。

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