Application of a TID Controller for the LFC of a Multi Area System using HGS Algorithm

A Tilt Integral Derivative (TID) controller is designed in this paper for the Load Frequency Control (LFC) issue of a multi-area interconnected restructured power system. The suggested TID controller settings are fine-tuned using a novel optimization technique known as Hunger Games Search (HGS) algorithm. A multi-area interconnected power system with various generating units is used to test the performance of the proposed TID controller based on HGS. The suggested controller also takes into account system non-linearities such as Generation Rate Constraints (GRCs) and Governor Dead Band (GDB). The superiority of HGS's optimization over a range of other significant optimization techniques, such as the grey-wolf optimization algorithm, has been confirmed. The simulation results show that the proposed TID controller based on HGS improves system frequency stability significantly under a variety of load perturbation scenarios

Application of Grey Wolf Optimizer Algorithm for Optimal Power Flow of Two-Terminal HVDC Transmission System

This paper applies a relatively new optimization method, the Grey Wolf Optimizer (GWO) algorithm for Optimal Power Flow (OPF) of twoterminal High Voltage Direct Current (HVDC) electrical power system. The OPF problem of pure AC power systems considers the minimization of total costs under equality and inequality constraints. Hence, the OPF problem of integrated AC-DC power systems is extended to incorporate HVDC links, while taking into consideration the power transfer control characteristics using a GWO algorithm. This algorithm is inspired by the hunting behavior and social leadership of grey wolves in nature. The proposed algorithm is applied to two different case-studies: the modified 5-bus and WSCC 9-bus test systems. The validity of the proposed algorithm is demonstrated by comparing the obtained results with those reported in literature using other optimization techniques. Analysis of the obtained results show that the proposed GWO algorithm is able to achieve shorter CPU time, as well as minimized total cost when compared with already existing optimization techniques. This conclusion proves the efficiency of the GWO algorithm

Load Frequency Control (LFC) Strategies in Renewable Energy‐Based Hybrid Power Systems:A Review

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in the hybrid power system. Load Frequency Controller (LFC) design ensures the reliable and efficient operation of the power system. The main function of LFC is to maintain the system frequency within safe limits, hence keeping power at a specific range. An LFC should be supported with modern and intelligent control structures for providing the adequate power to the system. This paper presents a comprehensive review of several LFC structures in a diverse configuration of a power system. First of all, an overview of a renewable energy-based power system is provided with a need for the development of LFC. The basic operation was studied in single-area, multi-area and multi-stage power system configurations. Types of controllers developed on different techniques studied with an overview of different control techniques were utilized. The comparative analysis of various controllers and strategies was performed graphically. The future scope of work provided lists the potential areas for conducting further research. Finally, the paper concludes by emphasizing the need for better LFC design in complex power system environments

Particle Swarm Optimization, Genetic Algorithm and Grey Wolf Optimizer Algorithms Performance Comparative for a DC-DC Boost Converter PID Controller

[EN] Power converters are electronic devices widely applied in industry, and in recent years, for renewable energy electronic systems, they can regulate voltage levels and actuate as interfaces, however, to do so, is needed a controller. Proportional-Integral-Derivative (PID) are applied to power converters comparing output voltage versus a reference voltage to reduce and anticipate error. Using PID controllers may be complicated since must be previously tuned prior to their use. Many methods for PID controllers tunning have been proposed, from classical to metaheuristic approaches. Between the metaheuristic approaches, bio-inspired algorithms are a feasible solution; Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are often used; however, they need many initial parameters to be specified, this can lead to local solutions, and not necessarily the global optimum. In recent years, new generation metaheuristic algorithms with fewer initial parameters had been proposed. The Grey Wolf Optimizer (GWO) algorithm is based on wolves¿ herds chasing habits. In this work, a comparison between PID controllers tunning using GWO, PSO, and GA algorithms for a Boost Converter is made. The converter is modeled by state-space equations, and then the optimization of the related PID controller is made using MATLAB/Simulink software. The algorithm¿s performance is evaluated using the Root Mean Squared Error (RMSE). Results show that the proposed GWO algorithm is a feasible solution for the PID controller tunning problem for power converters since its overall performance is better than the obtained by the PSO and GA.The authors wish to thank the Institute of Energy Engineering of the Polytechnic University of Valencia, Spain, and the Department of Water and Energy Studies of the University of Guadalajara, Mexico, for all their support and collaboration.Águila-León, J.; Chiñas-Palacios, C.; Vargas-Salgado Carlos; Hurtado-Perez, E.; García, EXM. (2021). 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Vasisht, "Solar PV interface to Grid-Tie Inverter with Current Referenced Boost Converter," in 2018 IEEE 13th International Conference on Industrial and Information Systems (ICIIS), IEEE: 343-348, 2018, doi:10.1109/ICIINFS.2018.8721313.S.E. Babaa, G. El Murr, F. Mohamed, S. Pamuri, "Overview of Boost Converters for Photovoltaic Systems," Journal of Power and Energy Engineering, 06(04), 16-31, 2018, doi:10.4236/jpee.2018.64002.J. Berner, K. Soltesz, T. Hägglund, K.J. Åström, "An experimental comparison of PID autotuners," Control Engineering Practice, 73, 124-133, 2018, doi:10.1016/J.CONENGPRAC.2018.01.006.K. Ogata, Modern Control Engineering, 5th ed., Prentice Hall, 2010.K. Nisi, B. Nagaraj, A. Agalya, "Tuning of a PID controller using evolutionary multi objective optimization methodologies and application to the pulp and paper industry," International Journal of Machine Learning and Cybernetics, 10(8), 2015-2025, 2019, doi:10.1007/s13042-018-0831-8.M.T. Özdemir, D. Öztürk, "Comparative performance analysis of optimal PID parameters tuning based on the optics inspired optimization methods for automatic generation control," Energies, 10(12), 2017, doi:10.3390/en10122134.G.-Q. Zeng, X.-Q. Xie, M.-R. Chen, "An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations," Energies, 10(11), 1840, 2017, doi:10.3390/en10111840.Y. Sawle, S.C. Gupta, A.K. Bohre, "Optimal sizing of standalone PV/Wind/Biomass hybrid energy system using GA and PSO optimization technique," Energy Procedia, 117, 690-698, 2017, doi:10.1016/j.egypro.2017.05.183.S. Surender Reddy, C. Srinivasa Rathnam, "Optimal Power Flow using Glowworm Swarm Optimization," International Journal of Electrical Power & Energy Systems, 80, 128-139, 2016, doi:10.1016/J.IJEPES.2016.01.036.C.Y. Acevedo-arenas, A. Correcher, C. Sánchez-díaz, E. Ariza, D. Alfonso-solar, C. Vargas-salgado, J.F. Petit-suárez, "MPC for optimal dispatch of an AC-linked hybrid PV / wind / biomass / H2 system incorporating demand response," Energy Conversion and Management, 186(February), 241-257, 2019, doi:10.1016/j.enconman.2019.02.044.M. Çelebi, "Efficiency optimization of a conventional boost DC/DC converter," Electrical Engineering, 100(2), 803-809, 2018, doi:10.1007/s00202-017-0552-0.Q.Y. Lu, W. Hu, L. Zheng, Y. Min, M. Li, X.P. Li, W.C. Ge, Z.M. Wang, "Integrated coordinated optimization control of automatic generation control and automatic voltage control in regional power grids," Energies, 5(10), 3817-3834, 2012, doi:10.3390/en5103817.J. Aguila‐Leon, C. Chiñas‐Palacios, E.X.M. Garcia, C. 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Lewis, "Grey Wolf Optimizer," Advances in Engineering Software, 69, 46-61, 2014, doi:10.1016/j.advengsoft.2013.12.007.S.-X. Li, J.-S. Wang, "Dynamic Modeling of Steam Condenser and Design of PI Controller Based on Grey Wolf Optimizer," Mathematical Problems in Engineering, 2015, 1-9, 2015, doi:10.1155/2015/120975.S. Yadav, S.K. Verma, S.K. Nagar, "Optimized PID Controller for Magnetic Levitation System," IFAC-PapersOnLine, 49(1), 778-782, 2016, doi:10.1016/J.IFACOL.2016.03.151.R.H.G. Tan, L.Y.H. Hoo, "DC-DC converter modeling and simulation using state space approach," 2015 IEEE Conference on Energy Conversion (CENCON), (2), 42-47, 2015, doi:10.1109/CENCON.2015.7409511

Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

Selfish Herd Optimisation based fractional order cascaded controllers for AGC study

In a modern, and complex power system (PS), robust controller is obligatory to regulate the frequency under uncertain load/parameter change of the system. In addition to this, presence of nonlinearities, load frequency control (LFC) of a Power System becomes more challenging which necessitates a suitable, and robust controller. Single stage controller does not perform immensely against aforesaid changed conditions. So, a novel non-integer/fractional order (FO) based two-stage controller incorporated with 2-degrees of freedom (2-DOF), derivative filter (N), named as 2-DOF-FOPIDN-FOPDN controller, is adopted to improve the dynamic performance of a 3-area power system. Each area of the power system consists of both non-renewable and renewable generating units. Again, to support the superior performance of 2-DOF-FOPIDN-FOPDN controller, it is compared with the result produced by PID, FOPID, and 2-DOF-PIDN-PDN controllers. The optimal design of these controllers is done by applying Selfish Herd Optimisation (SHO) technique. Further, the robustness of the 2-DOF-FOPIDN-FOPDN controller is authenticated by evaluating the system performance under parameter variation. The work is further extended to prove the supremacy of SHO algorithm over a recently published article based on pathfinder algorithm (PFA)

Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

A novel hybrid many optimizing liaisons gravitational search algorithm approach for AGC of power systems

A hybrid Many Optimizing Liaisons Gravitational Search Algorithm (hMOL-GSA)-based fuzzy PID controller is proposed in this work for Automatic Generation Control problem. MOL is a simplified version of particle swarm optimization which ignores the particle best position consequently simplifying the algorithm. The proposed method is employed to tune the fuzzy PID parameters. The outcomes are equated with some newly proposed methods like Artificial Bee Colony (ABC)-based PID for the identical test systems to validate the supremacy of GSA and proposed hMOL-GSA techniques. Further, the design task has been carried out in a three-area test system and the outcomes are equated with newly proposed Firefly Algorithm (FA) optimized PID and Teaching Learning-Based Optimization (TLBO) tuned PIDD controller for the identical system. Better system response has been observed with proposed hMOL-GSA method. Finally, sensitivity study is being carried out and robustness of the proposed method is established