An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach

Author:

Elzein I.1,Petrenko Yu. N.1

Affiliation:

1. Belarusian National Technical University

Abstract

Photovoltaic power plants have non-linear voltage-current characteristic, with specific maximum power point, which depends on operating conditions, viz. irradiation and temperature. In targeting the maximum power, it is by far known that the photovoltaic arrays have to operate at the maximum power point despite unpredicted weather changes. For this reason the controllers of all photovoltaic power electronic converters employ some method for maximum power point tracking. This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. Further, during the advanced stages of this research study, the model will compare the results obtained for tracking the maximum power point from model predictive controller and a PID-controller as they are integrated Perturb and Observe algorithm. The obtained results will verify that the adaptive PID-controller Perturb and Observe algorithm has limitation for tracking the precise MPP during the transient insulation conditions. As compared to the proposed adaptive/modified model predictive controller for Perturb and Observe algorithm we illustrate that by adopting this method we will get to establish more accurate and efficient results of the obtained power in any dynamic environmental conditions: advantages as on regulation time (six times under the accepted experimental conditions) and by the number of fluctuations.

Publisher

Belarusian National Technical University

Subject

Energy Engineering and Power Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference35 articles.

1. Khroustalev B. M., Pilipenko V. M., Danilevsky L. N., Nguyen Thuy Nga (2014) On Problem in Development of House Building Construction with Minimum Power Resources Consumption. Energetika. Izvestiya Vysshikh Uchebnykh Zavedenii i Energeticheskikh Ob’edinenii SNG = Energetika. Proceedings of the CIS Higher Education Institutions and Power Engineering Associations, (5), 45–60 (in Russian).

2. Kundas C. P., Poznyak S. S., Shenets L. V. (2009) Renewable Sources of Power. Minsk, International Sakharov Environmental Institute of Belarusian State University. 315 (in Russian).

3. Maronchuk I. I., Sanikovich D. D., Mironchuk V. I. (2019) Solar Cells: Current State and Development Prospects. Energetika. Izvestiya Vysshikh Uchebnykh Zavedenii i Energeticheskikh Ob’edinenii SNG = Energetika. Proceedings of the CIS Higher Education Institutions and Power Engineering Associations, 62 (2), 105–123. https://doi.org/10.21122/1029-7448-2019-62-2-105-123 (in Russian).

4. Zalizny D. I. (2019) Model of a Photovoltaic Cell for the MatLab/Simulink SimPowerSystems Library. Energetika. Izvestiya Vysshikh Uchebnykh Zavedenii i Energeticheskikh Ob’edinenii SNG = Energetika. Proceedings of the CIS Higher Education Institutions and Power Engineering Associations, 62 (2), 135–145. https://doi.org/10.21122/1029-7448-2019-62-2-135-145 (in Russian).

5. Veerachary M., Senjyu T., Uezato K. (2020) Voltage-Based Maximum Power Point Tracking Control of PV System. IEEE Transactions on Aerospace and Electronic Systems, 38 (1), 262–270. https://doi.org/10.1109/7.993245.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3