Modeling of Hybrid Power Generation using FLC

Simranjit Kaur, S. Vig
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Abstract

In this paper, an effective and efficient power hybrid power generation model is presented in which Maximum power point is tracked by using Fuzzy Logic Controller. The main objective of the proposed approach is to enhance the power capabilities of systems in order to fulfill the increasing load demand. To combat this task, a fuzzy based MPPT technique is implement in power generating system that takes two inputs. Furthermore, two optimization algorithms i.e. chaotic map and Differential Evolution (DE) are hybridized for optimizing the range of variables for two input functions of fuzzy model. The fitness value is calculated in terms of increase in power capabilities. Also, the proposed model utilized two energy sources i.e. Wind energy and solar energy for providing the necessary supply to customers during peak hours. A switching circuitry is also used in the proposed hybrid model for switching between two models when one is not able to generate electricity. The performance of the proposed fuzzy based approach is examined and validated by putting it in comparison with traditional ACO model in terms of their voltage, current and power generation abilities. In addition to this, analytical study is also conducted for wind and solar energy models to determine their abilities for generating power and satisfying load demands.
基于FLC的混合发电建模
本文提出了一种利用模糊控制器对最大功率点进行跟踪的高效功率混合发电模型。提出的方法的主要目的是提高系统的电力能力,以满足日益增长的负荷需求。为了解决这一问题,在双输入发电系统中实现了一种基于模糊的MPPT技术。在此基础上,结合混沌映射和差分进化两种优化算法,对模糊模型的两个输入函数的变量范围进行优化。适应度值是根据功率能力的增加来计算的。此外,所提出的模型利用两种能源,即风能和太阳能,在高峰时段为客户提供必要的供应。在混合模型中还使用了切换电路,以便在其中一个不能发电时在两个模型之间切换。通过与传统蚁群控制模型在电压、电流和发电能力方面的比较,验证了所提模糊控制方法的性能。除此之外,还对风能和太阳能模型进行了分析研究,以确定其发电能力和满足负荷需求的能力。
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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