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A Two-Stage Heuristic Procedure for Solving the Long-Term Unit Commitment Problem with Pumped Storages and Its Application to the German Electricity Market

机译:用泵送存储解决长期单位承诺问题的两级启发式程序及其在德国电力市场的应用

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In electricity systems unit commitment problems (UCP) target at a proper scheduling and coordinating of thermal plants, renewable energies, and storages. The need for fast solution methods has been growing in line with recent changes in the electricity system's environment and complexity, in particular with the increasing share of volatile renewable feed-ins. In order to meet this need even for large-scale systems a decomposition methodology for the UCP is suggested within this paper. Our two-stage decomposition first performs an isolated dispatching of thermal plants using a greedy algorithm, rule-based algorithms and local search based steps, followed by a re-optimization stage in order to incorporate energy storages into the final solution. The comparison of the iterative two-stage heuristic with commonly used approaches based on mixed integer linear programming shows outstanding results in terms of solution time and solution quality. Besides typically used test instances, the heuristic is applied to comprehensive case studies of the German electricity market, where (near-) optimal solutions can be derived for a yearly planning horizon with hourly time steps with computational effort of a few minutes using a standard PC.
机译:在电力系统中,单位承诺问题(UCP)目标在适当的调度和热植物,可再生能量和存储器的协调。对快速解决方案方法的需求符合电力系统环境和复杂性的最新变化,特别是由于挥发性可再生饲料的份额增加。为了满足这种需求,即使对于大规模系统,在本文中建议了UCP的分解方法。我们的两级分解首先使用贪婪算法,规则的算法和基于本地搜索的步骤进行隔离调度,然后是重新优化阶段,以便将能量存储器结合到最终解决方案中。基于混合整数线性编程的常用方法的迭代两级启发式的比较显示了解决方案时间和解决方案质量方面的出色结果。除了通常使用的测试实例外,启发式应用于德国电力市场的综合案例研究,其中(附近)可以通过使用标准PC的数分钟的计算精力来导出每小时时间步骤的年度规划的最佳解决方案。

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