Fractional-order Sliding Mode Controller Applied for Load Frequency Control of Power System

Author(s):  
Dipayan Guha ◽  
Provas Kumar Roy ◽  
Subrata Banerjee

This paper presents a Fractional Order Sliding Mode Controller (FOSMC) for load frequency control of multi area power system in deregulated environment. In deregulated power system the design of controller is more complicated due to contracted and un-contracted load demands. This proposed controller shall take care of system nonlinearities and uncertainties under bilateral contract scenario for sudden load disturbances. The performance of proposed controller compared to PI controller and without any controller.


This paper presents a Fractional Order based Second Order Sliding Mode Controller (FOSSMC) for Load Frequency Control (LFC) of Deregulated Multi Area Power System (DMAPS). In this paper a new control strategy have been proposed to improve dynamic response of multi area power system under one possible contract scenario by considering bilateral contracts. This proposed new FOSSMC strategy capable of dealing with frequency deviations for sudden change of load on DISCOs. The advantage of FOSSMC in terms of exhibiting dynamic response compared to group of factional order controllers such as Fractional Order PI(FOPI), Fractional Order Fuzzy Controller(FOFLC) and Fractional Order Sliding Mode Controller(FOSMC) and conventional PI controller.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3604
Author(s):  
Hady H. Fayek ◽  
Panos Kotsampopoulos

This paper presents load frequency control of the 2021 Egyptian power system, which consists of multi-source electrical power generation, namely, a gas and steam combined cycle, and hydro, wind and photovoltaic power stations. The simulation model includes five generating units considering physical constraints such as generation rate constraints (GRC) and the speed governor dead band. It is assumed that a centralized controller is located at the national control center to regulate the frequency of the grid. Four controllers are applied in this research: PID, fractional-order PID (FOPID), non-linear PID (NPID) and non-linear fractional-order PID (NFOPID), to control the system frequency. The design of each controller is conducted based on the novel tunicate swarm algorithm at each operating condition. The novel method is compared to other widely used optimization techniques. The results show that the tunicate swarm NFOPID controller leads the Egyptian power system to a better performance than the other control schemes. This research also presents a comparison between four methods to self-tune the NFOPID controller at each operating condition.


2020 ◽  
Vol 5 (1) ◽  
pp. 2
Author(s):  
Hady H. Fayek

Remote farms in Africa are cultivated lands planned for 100% sustainable energy and organic agriculture in the future. This paper presents the load frequency control of a two-area power system feeding those farms. The power system is supplied by renewable technologies and storage facilities only which are photovoltaics, biogas, biodiesel, solar thermal, battery storage and flywheel storage systems. Each of those facilities has 150-kW capacity. This paper presents a model for each renewable energy technology and energy storage facility. The frequency is controlled by using a novel non-linear fractional order proportional integral derivative control scheme (NFOPID). The novel scheme is compared to a non-linear PID controller (NPID), fractional order PID controller (FOPID), and conventional PID. The effect of the different degradation factors related to the communication infrastructure, such as the time delay and packet loss, are modeled and simulated to assess the controlled system performance. A new cost function is presented in this research. The four controllers are tuned by novel poor and rich optimization (PRO) algorithm at different operating conditions. PRO controller design is compared to other state of the art techniques in this paper. The results show that the PRO design for a novel NFOPID controller has a promising future in load frequency control considering communication delays and packet loss. The simulation and optimization are applied on MATLAB/SIMULINK 2017a environment.


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