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A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems

机译:基于热重组的热电联产机组时序动态规划算法

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This paper addresses the unit commitment (UC) in multi-period combined heat and power (CHP) production planning under the deregulated power market. In CHP plants (units), generation of heat and power follows joint characteristics, which implies that it is difficult to determine the relative cost efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained.
机译:本文讨论了在放松管制的电力市场下,多时期热电联产(CHP)生产计划中的机组承诺(UC)。在热电联产工厂(单位)中,热量和电力的产生遵循联合特征,这意味着很难确定工厂的相对成本效率。我们在本文中介绍了DRDP-RSC算法,它是一种基于动态重组的动态规划(DP)算法,它基于单元的ON / OFF状态的线性松弛,小组中单元的顺序承诺。使用植物的松弛状态来减小UC问题的范围,并使用动态重组来提高解决方案的质量。基于现实生活中的数据集的数值结果表明,该算法是有效的,并且获得了具有很小的最优缺口的最优或接近最优的解决方案。

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