Design of load frequency controller for multi-area system using AI techniques

被引:0
作者
Machavarapu S. [1 ]
Gopala Rao M.V. [2 ]
Ramana Rao P.V. [3 ]
机构
[1] EEE Department, Vignan’s Lara Institute of Technology & Science, Vadlamudi
[2] EEE Department, Prasad V. Potluri Siddhartha Institute of Technology, Kanuru
[3] EEE Department, College of Engineering & Technology, Acharya Nagarjuna University, Nagarjuna Nagar
来源
Journal Europeen des Systemes Automatises | 2020年 / 53卷 / 04期
关键词
Automatic speed governor; Backpropagation algorithm; Fuzzy logic controller; Load frequency controller; PI-controller; Tie line;
D O I
10.18280/jesa.530413
中图分类号
学科分类号
摘要
The paper presents an adaptive Load Frequency Controller (LFC) based on a neural network for the interconnected multi-area systems. When there is an imbalance between active power generation and demand there will deviation in the frequency from the reference value. Major disturbances that lead to the variation in frequency beyond the allowable limits are variation in load demand and faults, etc. Initially PID based LFC which is a conventional controller is used to bring back the variations in frequency when there is a disturbance. But these conventional controllers will operate certain operating points only, very slow and, are less efficient for nonlinear systems. To avoid the flaws in the conventional controller the artificial intelligent controllers such as neural network and fuzzy logic controllers are designed. The three, two area, and single area systems are considered as the test systems. The response of all the test systems is observed without and with PI, fuzzy, and neural network controllers. It was observed that the neural network controller is outperforming in damping the variation in the frequency due to the disturbances. © 2020 Lavoisier. All rights reserved.
引用
收藏
页码:541 / 548
页数:7
相关论文
共 16 条
  • [1] Ranganayakulu R., Babu G.U., Rao A.S., Patle D.S., A comparative study of fractional order PI/PID tuning rules for stable first order plus time delay processes, Resource-Efficient Technologies, 2, pp. S136-S152, (2016)
  • [2] Annamraju A., Nandiraju S., Robust frequency control in a renewable penetrated power system: An adaptive fractional order-fuzzy approach, Protection and Control of Modern Power Systems, 4, 16, (2019)
  • [3] Liu H., Hu Z., Song Y., Vehicle-to-grid control for supplementary frequency regulation considering charging demands, IEEE Transactions on Power Systems, 30, 6, pp. 3110-3119, (2015)
  • [4] Debbarma S., Dutta A., Utilizing electric vehicles for LFC in restructured power systems using fractional order controller, IEEE Transactions on Smart Grid, 8, 6, pp. 2554-2564, (2017)
  • [5] Hanwate S., Hote Y.V., Saxena S., Adaptive policy for load frequency control, IEEE Transactions on Power Systems, 33, 1, pp. 1142-1144, (2018)
  • [6] Kayalvizhi S., Kumar D.M.V., Load frequency control of an isolated micro grid using fuzzy adaptive model predictive control, IEEE Access, 5, pp. 16241-16251, (2017)
  • [7] Trang L.T.M., Nouri H., Modeling dynamic frequency control with power reserve limitations, 53rd International Universities Power Engineering Conference, pp. 1-5, (2018)
  • [8] Farag K.A., Sharaf A.M., A novel modified robust load frequency controller scheme, Energy Systems, (2019)
  • [9] Manikandan S., Kokil P., Delay-dependent stability analysis of network-based load frequency control of one and two area power system with time-varying delays, Fluctuation and Noise Letters, 18, 1, pp. 1-19, (2019)
  • [10] Pappachen A., Fathima A.P., Critical research areas on load frequency control issues in a deregulated power system: A state-of-the-art-of-review, Renewable and Sustainable Energy Reviews, 72, pp. 163-177, (2017)