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Tight Conic Formulation of Unit Commitment Problem and Comparison with MINLP/MILP Formulations

机译:单位承诺问题的紧圆锥公式,以及与MINLP / MILP公式的比较

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Unit Commitment (UC) in its classical form is a mixed integer non-linear programming (MINLP) problem, which is not scalable to power systems with large number of generators. Mixed integer linear programming (MILP) versions of UC use linear or piece-wise linearized cost functions of the generators, which is computationally efficient for larger systems, and is the state-of-the-art method in some of the existing energy management system (EMS) tools. In this paper, we demonstrate that use of linear cost functions in MILP can lead to suboptimal solutions, thus having larger differences in cost which can be possibly run into millions of dollars. We then develop a tighter conic reformulation of the UC problem that retains the quadratic cost functions of the generators and utilizes convex hull descriptions of harder inter-temporal constraints. This improves on the computational efficiency, and as a result, the formulation shows better scalability than MINLP and significantly lower operational costs compared to MILP. We demonstrate efficacy of the proposed UC formulation using several case studies considering upto 1,000 generators.
机译:经典形式的单位承诺(UC)是一个混合整数非线性规划(MINLP)问题,无法解决具有大量发电机的电力系统的问题。 UC的混合整数线性规划(MILP)版本使用发电机的线性或分段线性化成本函数,这对于大型系统而言计算效率高,并且是某些现有能源管理系统中的最先进方法(EMS)工具。在本文中,我们证明了在MILP中使用线性成本函数会导致次优解决方案,因此成本差异较大,可能会导致数百万美元的损失。然后,我们对UC问题进行了更严格的圆锥重构,它保留了生成器的二次成本函数,并利用了更严格的跨时间约束的凸包描述。这提高了计算效率,因此,与MILP相比,该公式显示出比MINLP更好的可伸缩性,并且显着降低了运营成本。我们通过考虑多达1,000个发电机的几个案例研究证明了拟议的UC配方的功效。

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