Multi-area Multi-source Power System Research Articles

Application of Intelligent controller For Load Frequency Control for Multi-Area Multi-Source Power System

Application of Intelligent controller For Load Frequency Control for Multi-Area Multi-Source Power System

Impact Assessment of Redox Flow Battery Coordinated Diverse Link on Frequency Regulation in Multi-Area Multi-Source Power System with Decentralized Optimal Control

Impact Assessment of Redox Flow Battery Coordinated Diverse Link on Frequency Regulation in Multi-Area Multi-Source Power System with Decentralized Optimal Control

A MODIFIED SALP SWARM OPTIMIZATION ALGORITHM BASED ON THE LOAD FREQUENCY CONTROL OF MULTIPLE-SOURCE POWER SYSTEM

This work proposes a modified Salp Swarm Optimization Algorithm (SSA) for addressing a multi-source power state's Load Frequency Control (LFC). A controller parameter tuning of the SSA method and its application to the LFC of a multi-source power system with several power generating sources. Derive to the controller parameters, a single area telecommunications device that permits two power system with integrated controlles according to each unit is considered first, and the SSA approach is used. The tunned SSA algorithm is used to optimize the integral (I), proportional integral (PI), and proportional integral derivative (PID) parameters. The research is expanded to include a multi-area multi-source power system, as well as an HVDC link is proposed for connectivity of two regions in addition to the current AC point of intersection. This same tunned SSA method is used to improve the parameters of the Integral (I), Proportional Integral (PI), and Proportional - integral - derivative Derivative (PID). Consequently, the suggested system is shown to be resilient and unaffected by changes of the loading situation, system parameters, or SLP size.

An Improved Whale Optimization Algorithm Based PIDF–(1+PI) Cascade Automatic Generation Control for Multi-Area Multi-Source Power System With Capacitive Energy Storage

An Improved Whale Optimization Algorithm Based PIDF–(1+PI) Cascade Automatic Generation Control for Multi-Area Multi-Source Power System With Capacitive Energy Storage

Advanced Sliding Mode Observer Design for Load Frequency Control of Multiarea Multisource Power Systems

Recently, to balance the increased electricity demands and total generated power, the multiarea power system (MAPS) has been introduced with multipower sources such as gas, nuclear, hydro, and thermal, which will impact the load frequency control (LFC). Therefore, the LFC of the two-area gas-hydro-thermal power system (TAGHTPS) is introduced by applying the single-phase sliding mode control-based state observer (SPSMCBSO). In this scheme, the TAGHTPS is the first model that considers the uncertainties of the parameters in the state and the interconnected matrix. Second, the state observer is employed to estimate the state variables for the feedback control. Third, the SPSMCBSO is developed to modify the basic sliding mode control to improve the performance of TAGHTPS in terms of overshoot and settling time. In addition, the SPSMCBSO is established to rely fully on the state observer so that the difficulty in the state variable measurement is solved. Fourth, the TAGHTPS stability analysis is performed using a new linear matrix inequality (LMI) scheme—Lyapunov stability theory. Lastly, the simulation results are shown and compared to recently established classical control methods to validate the SPSMCBSO choice of application for the LFC of the multiarea multisource power system (MAMSPS).

Design of an Optimized Fractional High Order Differential Feedback Controller for Load Frequency Control of a Multi-Area Multi-Source Power System With Nonlinearity

Load frequency control (LFC) is one of the essential process in interconnected power systems. To provide high quality, reliable and stable electrical power, designed controller should perform satisfactorily, i.e. suppress area frequency and tie-line power deviations. Within this scope, in this study, a high order differential feedback controller (HODFC) and a developed fractional high order differential feedback controller (FHODFC) are proposed for LFC problem in multi-area power systems for the first time. The gains of the HODFC and FHODFC are optimally tuned by particle swarm optimization (PSO) algorithm aiming to minimize integral of time weighted absolute error (ITAE) performance index. The superiority of the developed FHODFC are verified by comparing reported controller structures in the recent state-of-the-art literature and HODFC for two identical non-reheat thermal power system and two-area multi-source power system consisting of gas, thermal and hydro generation units with/without consideration of HVDC link. To test the robustness of the designed controllers, varying system parameters and loading conditions are investigated. The governor dead band (GDB) and generation rate constraint (GRC) limitations are also considered for the system under study to examine non-linearity handling success of the proposed controllers. Performance results indicate that the developed FHODFC provides better dynamic response and robustness than other published techniques under nonlinearities, random load pattern, and variations in system parameters and loading conditions.

Grasshopper optimization algorithm for optimal load frequency control considering Predictive Functional Modified PID controller in restructured multi-resource multi-area power system with Redox Flow Battery units

Load frequency control (LFC) is a well-established issue in design and operation of power systems considering to the extension, restructuring, and complexity of the interconnected power systems and also the emergence utilization of renewable energy resources. This paper studies the frequency control of multi-area multi-source power system based on the importance of the LFC in the stability of the power system which includes various generation units of thermal, hydroelectric, wind, natural gas and diesel under the restructured environment. In this system, non-linear physical constraints, governor dead band (GDB) and generation rate constraint (GRC) are considered. In this paper, a new Predictive Functional Modified PID (PFMPID) controller is proposed that the effectiveness of this controller is verified compared to the traditional one. In order to optimize and demonstrate the superiority of the proposed control method, Grasshopper Optimization Algorithm (GOA) is proposed as a suitable solution. To further improve the performance of the under study system, the use of the Redox Flow Battery (RFB) energy storage unit has also been proposed. Since the operation evaluation of the proposed process is necessary in different system conditions, the performance of the proposed method is studied under various disturbances and simulation results are presented.

Load Frequency Control of Multi-Area Multi-Source Power System using Teaching Learning Optimization Technique

Load Frequency Control of Multi-Area Multi-Source Power System using Teaching Learning Optimization Technique

Whale optimisation algorithm tuned fractional order PI<SUP align="right">λ</SUP>D<SUP align="right">μ</SUP> controller for load frequency control of multi-source power system

This paper deals with the design and optimisation of a fractional order PIλDμ (FOPID) controller implemented for load frequency control (LFC) of a multi-area multi-source power system having the nonlinearities of time delays, generation rate constraint (GRC) and governor dead band (GDB). Whale optimisation algorithm (WOA), arguably for the first time in this area, is applied for optimal tuning of the parameters of FOPID controller. The comparative analysis of the performance of WOA vis-a-vis other recent evolutionary optimisation approaches is carried out from which it is observed that WOA optimised FOPID controller gives the best dynamic performance in terms of settling time and maximum overshoot in frequency and tie-line power deviations. Further, investigations carried out against system parametric variations within the range of ± 25% reveal that WOA tuned FOPID controller is the most effective and robust against wide variations in system parameters.

An Online Q-learning Based Multi-Agent LFC for a Multi-Area Multi-Source Power System Including Distributed Energy Resources

An Online Q-learning Based Multi-Agent LFC for a Multi-Area Multi-Source Power System Including Distributed Energy Resources

Effect of TCPS, SMES, and DFIG on load frequency control of a multi-area multi-source power system using multi-verse optimized fuzzy-PID controller with derivative filter

In this paper, a novel multi-verse optimized fuzzy-PID (proportional–integral–derivative) controller with derivative filter (fuzzy-PIDF) is proposed for load frequency control of a two-area multi-source power system, with each area consisting of a reheat thermal and a hydro unit. The superiority of the Multi-Verse Optimizer algorithm is demonstrated against some recently published modern heuristic optimization techniques. For comparative analysis of the proposed control scheme, the conventional integral, proportional–integral, and PIDF controllers are also implemented. The effect of the thyristor-controlled phase shifter, superconducting magnetic energy storage, and doubly fed induction generators, considered individually and in various combinations, is investigated. Further, with an integral controller optimized using Multi-Verse Optimizer, the value of the integral of time multiplied absolute error, one of the performance indicators, is reduced by 85.61%, 83.91%, 70.42%, 67.69%, and 73.15% compared with optimization of the integral controller using Ant Lion Optimizer, Grey Wolf Optimizer, Differential Evolution, Bacterial Foraging, and Particle Swarm Optimization, respectively. Also, to quote a representative case, with Multi-Verse Optimizer, the settling times in respect of frequency deviations of area-1, area-2, and tie-line power are improved by 94.36%, 98.28%, and 95.44%, respectively, as compared with the results obtained using Ant Lion Optimizer. Further, robustness of the proposed control scheme is also investigated against variation of system parameters within ±10% besides random step load disturbances. Of all the controllers implemented here, the proposed optimized fuzzy-PIDF controller exhibits the best performance. Modeling and simulations were carried out using MATLAB/Simulink.

Firefly algorithm optimized fuzzy PID controller for AGC of multi-area multi-source power systems with UPFC and SMES

In this paper, a Firefly Algorithm (FA) optimized fuzzy PID controller is proposed for Automatic Generation Control (AGC) of multi-area multi-source power system. Initially, a two area six units power system is used and the gains of the fuzzy PID controller are optimized employing FA optimization technique using an ITAE criterion. The superiority of the proposed FA optimized fuzzy PID controller has been demonstrated by comparing the results with some recently published approaches such as optimal control and Differential Evolution (DE) optimized PID controller for the identical interconnected power system. Then, physical constraints such as Time Delay (TD), reheat turbine and Generation Rate Constraint (GRC) are included in the system model and the superiority of FA is demonstrated by comparing the results over DE, Gravitational Search Algorithm (GSA) and Genetic Algorithm (GA) optimization techniques for the same interconnected power system. Additionally, a Unified Power Flow Controller (UPFC) is placed in the tie-line and Superconducting Magnetic Energy Storage (SMES) units are considered in both areas. Simulation results show that the system performances are improved significantly with the proposed UPFC and SMES units. Sensitivity analysis of the system is performed by varying the system parameters and operating load conditions from their nominal values. It is observed that the optimum gains of the proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Finally, the effectiveness of the proposed controller design is verified by considering different types of load patterns.

A hybrid DE–PS algorithm for load frequency control under deregulated power system with UPFC and RFB

Abstract In this paper, a Modified Integral Derivative (MID) controller is proposed for Load Frequency Control (LFC) of multi-area multi-source power system in deregulated environment. The multi-source power system is having different sources of power generation such as thermal, hydro, wind and diesel generating units considering boiler dynamics for thermal plants, Generation Rate Constraint (GRC) and Governor Dead Band (GDB) non-linearity. The superiority of proposed hybrid Differential Evolution and Pattern Search (hDE-PS) optimized MID controller over GA and DE techniques is demonstrated. Further, the effectiveness of proposed hDE-PS optimized MID controller over Integral (I) and Integral Derivative (ID) controller is verified. Then, to further improve the system performance, Unified Power Flow Controller (UPFC) is placed in the tie-line and Redox Flow Batteries (RFBs) are considered in the first area. The performance of proposed approach is evaluated at all possible power transactions that take place in a deregulated power market.

A novel hybrid DEPS optimized fuzzy PI/PID controller for load frequency control of multi-area interconnected power systems

In this paper, a novel hybrid Differential Evolution (DE) and Pattern Search (PS) optimized fuzzy PI/PID controller is proposed for Load Frequency Control (LFC) of multi-area power system. Initially a two-area non-reheat thermal system is considered and the optimum gains of the fuzzy PI/PID controller are optimized employing a hybrid DE and PS (hDEPS) optimization technique. The superiority of the proposed controller is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as DE, Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA) and conventional Ziegler Nichols (ZN) based PI controllers for the same interconnected power system. Furthermore, robustness analysis is performed by varying the system parameters and operating load conditions from their nominal values. It is observed that the optimum gains of the proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Additionally, the proposed approach is further extended to multi-area multi-source power system with/without HVDC link and the gains of fuzzy PID controllers are optimized using hDEPS algorithm. The superiority of the proposed approach is shown by comparing the results with recently published DE optimized PID controller and conventional optimal output feedback controller for the same power systems. Finally, Reheat turbine, Generation Rate Constraint (GRC) and time delay are included in the system model to demonstrate the ability of the proposed approach to handle nonlinearity and physical constraints in the system model.

Controller parameters tuning of differential evolution algorithm and its application to load frequency control of multi-source power system

This paper presents controller parameters tuning of Differential Evolution (DE) algorithm and its application to Load Frequency Control (LFC) of a multi-source power system having different sources of power generation like thermal, hydro and gas power plants. Initially, a single area multi-source power system with integral controllers for each unit is considered and DE technique is applied to obtain the controller parameters. Various mutation strategies of DE are compared and the control parameters of DE for best obtained strategy are tunned by executing multiple runs of algorithm for each parameter variation. The study is further extended to a multi-area multi-source power system and a HVDC link is also considered in parallel with existing AC tie line for the interconnection of two areas. The parameters of Integral (I), Proportional Integral (PI) and Proportional Integral Derivative (PID) are optimized employing tunned DE algorithm. The superiority of the proposed approach has been shown by comparing the results with recently published optimal output feedback controller for the same power systems. The comparison is done using various performance measures like overshoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than optimal output feedback controller. Furthermore, it is also seen that the proposed system is robust and is not affected by change in the loading condition, system parameters and size of SLP.