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Software-Enabled Investigation in Metaheuristic Power Grid Optimization

机译：元启发式电网优化中的软件研究

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摘要

Actual developments in power grid research, analysis, and operation are dominated clearly by the strong convergence of electrical engineering with information technology. Hence, new control abilities in power grids come up that revolutionize traditional optimization issues, requiring novel solution methods. At the same time, heuristic algorithms have emerged to be highly capable of handling those new optimization problems. In this work, a simulation-based optimization approach is proposed that enables investigation with metaheuristic algorithms for domain experts, where especially the power engineering point of view gets highlighted. HeuristicLab is demonstrated as a framework for optimization, which facilitates usage and development of optimization algorithms in a way that is attractive not only to computer scientists. From a software point of view, architectural aspects are treated that enable the decoupling of optimization algorithms and problems, which is a basic fundament of the framework. Further, interprocess communication is discussed that enables the interaction of optimization algorithms and simulation problems, and a practical showcase demonstrates the framework's application to real-world power grid optimization issues.
机译：电气工程与信息技术的强大融合明显地主导了电网研究，分析和运行的实际发展。因此，电网中出现了新的控制能力，彻底改变了传统的优化问题，需要新颖的解决方法。同时，启发式算法已经变得能够处理这些新的优化问题。在这项工作中，提出了一种基于仿真的优化方法，该方法可以使用超启发式算法为领域专家进行调查，其中特别强调了功率工程的观点。 HeuristicLab被证明是用于优化的框架，它不仅以吸引计算机科学家的方式促进了优化算法的使用和开发。从软件的角度来看，架构方面被视为可以使优化算法和问题脱钩，这是框架的基本基础。此外，还讨论了进程间通信，该通信可实现优化算法和仿真问题的交互，而实际的展示则演示了该框架在实际电网优化问题中的应用。

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