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Modified dynamic programming based unit commitment technique

机译：改进的基于动态规划的单元承诺技术

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This paper represents a modified dynamic programming solution to the unit commitment (UC) problem. The UC is a complex decision-making process because of multiple constraints which may not be violated while finding the optimal or suboptimal commitment schedule. There are many methods to solve the UC problem gradually. So, before we present our method, we will show the drawbacks of the standard dynamic programming methods which use general purpose optimization techniques to the UC problem. The priority list method, the lagrange relaxation and the mixed integer linear programming (MILP) are possible to apply to a real power system for performing the unit commitment. However, by using these methods, we could not get an optimal solution but only a suboptimal silution. Therefore we propose to get an optimal solution by using dynamic programming. Performing dynamic programming takes a lot of simulation time, so it is not optimal to use in a real power system for performing the unit commitment. Therefore, we need a modified dynamic programming method to satisfy both the simulated and the real power system to get the optimal solution. For those not familiar with UC problem, we introduce the constraints, production cost and start-up cost. The goal of the objective function is in cost minimization, so we use the economic dispatch using the lambda iteration method when we calculate the production costs. Finally, we compare the UC solution by using both methods.
机译：本文代表了一种改进的动态规划解决方案，用于解决单位承诺（UC）问题。 UC是一个复杂的决策过程，因为在找到最佳或次优承诺计划时可能不会违反多个约束。有很多方法可以逐步解决UC问题。因此，在介绍我们的方法之前，我们将展示使用通用优化技术解决UC问题的标准动态编程方法的弊端。优先级列表方法，滞后范围松弛法和混合整数线性规划（MILP）可以应用于执行单位承诺的有功功率系统。但是，通过使用这些方法，我们无法获得最佳解决方案，而只能获得次优的解决方案。因此，我们建议通过使用动态规划来获得最佳解决方案。执行动态编程需要花费大量的仿真时间，因此在实际电源系统中执行单元承诺并不是最佳选择。因此，我们需要一种改进的动态规划方法，既要满足仿真系统也要满足有功系统，才能获得最优解。对于那些不熟悉UC问题的人，我们介绍了约束条件，生产成本和启动成本。目标函数的目标是最小化成本，因此在计算生产成本时，我们会使用lambda迭代方法进行经济调度。最后，我们通过两种方法比较UC解决方案。

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