Smart Control Strategy for Adaptive Management of Islanded Hybrid Microgrids

Q3 Engineering EAI Endorsed Transactions on Energy Web Pub Date : 2024-03-25 DOI:10.4108/ew.5539

S. Poonkuzhali, A. Geetha

引用次数: 0

Abstract

This research paper presents a smart power control approach specifically designed for an independent microgrid. The proposed hybrid system consists of various crucial components, including a PV array, super capacitor, DC bus, battery bank, and AC bus working together to generate and store electricity within the microgrid. To address the challenges arising from random fluctuations in ecological parameters and changes in load demand, a supervisory controller is developed to enhance the standalone hybrid microgrid. This allows for optimized power management within the micro grid. The Liebenberg Marquardt algorithm is used to retrieve the trained ANN machine. The two and three hidden layered ANN machines have 96% accuracy on an average, whereas the single-layer ANN machine have poor predictive ability. The proposed model is implemented and analysed using MATLAB/Simulink. The observed results from the simulation experiments validate the effectiveness of integrating available resources in ensuring the resilience and reliability of microgrids.

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岛式混合微电网适应性管理的智能控制策略

本研究论文介绍了一种专为独立微电网设计的智能电力控制方法。所提出的混合系统由各种关键部件组成，包括光伏阵列、超级电容器、直流总线、电池组和交流总线，共同在微电网内发电和储电。为应对生态参数随机波动和负载需求变化带来的挑战，开发了一种监控控制器来增强独立混合微电网。这样就能优化微电网内的电力管理。利本伯格-马夸特（Liebenberg Marquardt）算法用于检索训练有素的 ANN 机器。两层和三层隐藏式 ANN 机器的平均准确率为 96%，而单层 ANN 机器的预测能力较差。使用 MATLAB/Simulink 对所提出的模型进行了实施和分析。模拟实验的观察结果验证了整合可用资源在确保微电网的弹性和可靠性方面的有效性。

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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来源期刊

EAI Endorsed Transactions on Energy Web Energy-Energy Engineering and Power Technology

CiteScore

2.60

自引率

0.00%

发文量

审稿时长

10 weeks

期刊介绍： With ICT pervading everyday objects and infrastructures, the ‘Future Internet’ is envisioned to undergo a radical transformation from how we know it today (a mere communication highway) into a vast hybrid network seamlessly integrating knowledge, people and machines into techno-social ecosystems whose behaviour transcends the boundaries of today’s engineering science. As the internet of things continues to grow, billions and trillions of data bytes need to be moved, stored and shared. The energy thus consumed and the climate impact of data centers are increasing dramatically, thereby becoming significant contributors to global warming and climate change. As reported recently, the combined electricity consumption of the world’s data centers has already exceeded that of some of the world''s top ten economies. In the ensuing process of integrating traditional and renewable energy, monitoring and managing various energy sources, and processing and transferring technological information through various channels, IT will undoubtedly play an ever-increasing and central role. Several technologies are currently racing to production to meet this challenge, from ‘smart dust’ to hybrid networks capable of controlling the emergence of dependable and reliable green and energy-efficient ecosystems – which we generically term the ‘energy web’ – calling for major paradigm shifts highly disruptive of the ways the energy sector functions today. The EAI Transactions on Energy Web are positioned at the forefront of these efforts and provide a forum for the most forward-looking, state-of-the-art research bringing together the cross section of IT and Energy communities. The journal will publish original works reporting on prominent advances that challenge traditional thinking.