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A new Lagrangian relaxation based method for power system scheduling with identical units

机译:一种基于拉格朗日松弛的具有相同单元的电力系统调度方法

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When the Lagrangian relaxation based methods are used to solve power system scheduling problems, severe solution oscillation may be caused by homogeneous subproblems with identical solutions. In this case the dual solution may be far away from the optimal schedule and, as a result, the quality of the feasible schedule obtained may be very unsatisfactory. This problem has long been recognized as an inherent disadvantage of the price based methods but few effective methods are developed to resolve this issue. In this paper, a new method is presented, combining the concepts of the augmented Lagrangian relaxation and surrogate subgradient method to produce a good search direction. The piecewise linear penalty associated with the system constraints is added to the Lagangian and subproblems are solved sequentially so that no approximation as in the augmented Lagrangian relaxation method is needed to maintain the decomposability. As a result, the better dual solution structure and better feasible schedules are obtained comparing with the standard Lagrangian relaxation method, and solution oscillation can be avoided or greatly reduced. Numerical testing shows the new methods are efficient and the quality of the feasible schedule is greatly improved.
机译:当使用基于拉格朗日松弛法的方法来解决电力系统调度问题时,具有相同解的齐次子问题可能会导致严重的解振荡。在这种情况下,双重解决方案可能会远离最佳计划,因此,所获得的可行计划的质量可能会非常不令人满意。长期以来,这个问题一直被认为是基于价格的方法的固有缺点,但是很少有有效的方法来解决此问题。本文提出了一种新的方法,结合了增强的拉格朗日松弛法和替代次梯度法的概念,以产生良好的搜索方向。与系统约束相关的分段线性惩罚被添加到Lagangian,并且子问题被顺序求解,因此不需要像在扩展Lagrangian松弛方法中那样的近似来维持可分解性。结果,与标准的拉格朗日松弛法相比,可以获得更好的对偶解结构和更好的可行方案,并且可以避免或大大减少解的振荡。数值测试表明,新方法是有效的,可行进度表的质量得到了极大的提高。

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