Application of Swarm Intelligence Algorithms to Optimize the Power Consumption Model

P. Matrenin, A. Khalyasmaa, S. Eroshenko, A. Rusina
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引用次数: 0

Abstract

This paper presents the problem of power consumption mathematical model development using the Pamir, the region of Tajikistan, as a case. The model view illustration describing the load curve is known, it is required to find the model parameters values. The paper compares three approaches: manual selection; deterministic method based on Fourier transform with local gradient search; meta-heuristic swarm algorithms. It is shown that swarm algorithms, due to their multipurposeness and scalability, make it possible to obtain more accurate models with less labor costs. But it is necessary to use several swarm algorithms, since it is impossible to determine in advance which one will be the best solution for a specific task. The results were confirmed by the application for the load curves of the UPS of Siberia.
群体智能算法在电力消耗模型优化中的应用
本文以塔吉克斯坦帕米尔地区为例,提出了电力消费数学模型的建立问题。描述负荷曲线的模型视图插图已知,则需要找到模型参数值。本文比较了三种方法:人工选择;基于傅里叶变换和局部梯度搜索的确定性方法;元启发式群算法。研究表明,群算法具有多用途和可扩展性,可以用较少的人工成本获得更精确的模型。但有必要使用几种群算法,因为不可能提前确定哪一种算法将是特定任务的最佳解决方案。通过对西伯利亚UPS负荷曲线的应用,验证了这一结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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