A Robust Discrete FuzzyP+FuzzyI+FuzzyD Load Frequency Controller for Multi-Source Power System in Restructuring Environment

This paper deals with the maiden application of opposition-based interactive search algorithm (OISA) for a multi-area, multi-source power system having thermal, hydro and gas generating units. For realistic approach, physical constraints like boiler dynamics (BD), governor dead band (GDB) and generation rate constraint (GRC) have been considered in the thermal system, while the effects of GRC and GDB are included in hydro and gas systems. Since modern power systems are focussing more towards renewable energy resources, for the purpose of analysis distributed generation (DG) and electric vehicle (EV) units are also incorporated in the system. A novel cascade combination of two-degree-of-freedom proportional–integral–derivative with a filter (PIDN) and fractional order integral–derivative (FOID) is used as the proposed controller for the system (2DOF-PIDN-FOID). The parameters of the proposed controller are optimised using the OISA algorithm. For analysis of the proposed system in deregulated environment, a step load perturbance (SLP) of 0.01 per unit is done in area-1. The effect of integration of distributed generation (DG) and electric vehicle (EV) on the system is analysed in both combined manner and separately. In both the cases, the system dynamics show marked improvement in comparison with previous cases. Analysis of system dynamics for various cases reveals the superiority of the proposed control scheme. Further, the superiority of the proposed algorithm is proven among other well-known evolutionary techniques like genetic algorithm (GA), particle swarm optimisation (PSO), interactive search algorithm (ISA) and whale optimisation algorithm (WOA) by comparison under same test conditions. Moreover, the robustness of the system is validated against system parameter variations. Finally, the superiority of the proposed control scheme is shown by comparison with published results in the literature under same test conditions.

This paper presents a Fractional Order Proportional-Integral-Derivative (FOPID) controller optimized using Social Spider Optimization (SSO) algorithm to Load Frequency Control (LFC) of a two-area multi-source power system in the presence of Distributed Generations (DGs). Here, the effect of DGs consist of wind and diesel power plants for damping frequency deviation of two-area multi-source power system including thermal, hydro and gas units considering nonlinearities such as generation rate constraint and governor dead band has been investigated. The FOPID controller has three main control parameters as known gain, fractional orders of integrator and derivative part that provide the better performance in comparison with the PID controller. On the other hand, to achieve the good performance in the power system, tuning of these parameters is very important. Therefore, the SSO algorithm has been used to optimal tuning of the FOPID based LFC controller. One of the important specifications of the employed algorithm is that it can balance the local and global solutions in the search space that cause to overcome the local optimal and premature convergence. Also, a High Voltage Direct Current link (HVDC) is used to improve the dynamic performance of the LFC task. Finally, the proposed controller has been applied on a two case studies and analyzed based on investigated performance criteria. Results show the good effect of DGs for the solution of LFC task and enhancing system performance characteristics under different operating conditions and considering system nonlinearities.

ABSTRACTOne of the key challenges in interconnected power systems is developing an effective control strategy to mitigate frequency and power deviations caused by the intermittency of renewable energy sources (RESs) and varying load demands. This research introduces an innovative cascade control strategy featuring a PPD controller followed by a PI controller (PPD‐PI) for load frequency control (LFC) in a two‐area power system with photovoltaic (PV), wind, and thermal reheat power sources. The walrus optimization algorithm (WaOA) is employed to fine‐tune the parameters of both the PIDn and PPD‐PI controllers, with the goal of minimizing the integral time absolute error (ITAE). The study first applies the WaOA‐tuned PID with filter (PIDn) controller to showcase WaOA's effectiveness in LFC, achieving the lowest objective function value of 0.3862, surpassing MFO (0.3921) and GA (0.4127). The robustness of the WaOA‐tuned PPD‐PI controller is then evaluated under various conditions, including step load disturbances, random load patterns, and parameter uncertainties. The proposed controller achieves significant improvements, with a 36.8% reduction in ITAE compared to the second‐best CGO‐tuned PIDn‐PI controller in Case 2, and a 54.45% reduction in ITAE compared to the second‐best COA‐tuned PDn‐PI controller in Case 3. To further highlight the advantages of the proposed scheme, the analysis also includes nonlinearities such as governor dead band (GDB), boiler dynamics (BD), and generation rate constraints (GRC), along with sensitivity analysis and stability testing under a change in system parameters. The results strongly demonstrate the superior performance of the WaOA‐optimized PPD‐PI controller over existing methods.

Multistage control for frequency and voltage stability in a multi-area power network with nonlinear dynamics

This study focuses on designing an effective intelligent control method to stabilize the net frequency against load variations in multi-control-area interconnected power systems. Conventional controllers (e.g. Integral, PI, and PID) achieve only poor control performance with high overshoots and long settling times. They could be replaced with intelligent regulators that can update controller parameters for better control quality. The control strategy is based on fuzzy logic, which is one of the most effective intelligent strategies and can be a perfect substitute for such conventional controllers when dealing with network frequency stability problems. This paper proposes a kind of fuzzy logic controller based on the PID principle with a 49-rule set suitable to completely solve the problem of load frequency control in a two-area thermal power system. Such a novel PID-like fuzzy logic controller with modified scaling factors can be applied in various practical scenarios of an interconnected power system, namely varying load change conditions, changing system parameters in the range of ±50%, and considering Governor Dead-Band (GDB) along with Generation Rate Constraint (GRC) nonlinearities and time delay. Through the simulation results implemented in Matlab/Simulink software, this study demonstrates the effectiveness and feasibility of the proposed fuzzy logic controller over several counterparts in dealing with the load-frequency control of a practical interconnected power system considering the aforesaid conditions.

A reliable approach based on a multi-verse optimization algorithm (MVO) for designing load frequency control incorporated in multi-interconnected power system comprising wind power and photovoltaic (PV) plants is presented in this paper. It has been applied for optimizing the control parameters of the load frequency controller (LFC) of the multi-source power system (MSPS). The MSPS includes thermal, gas, and hydro power plants for energy generation. Moreover, the MSPS is integrated with renewable energy sources (RES). The MVO algorithm is applied to acquire the ideal parameters of the controller for controlling a single area and a multi-area MSPS integrated with RES. HVDC link is utilized in shunt with AC multi-areas interconnection tie line. The proposed scheme has achieved robust performance against the disturbance in loading conditions, variation of system parameters, and size of step load perturbation (SLP). Meanwhile, the simulation outcomes showed a good dynamic performance of the proposed controller.

AGC of a multi-area power system under deregulated environment using redox flow batteries and interline power flow controller

In this paper, a two-degree-freedom (TDF) internal model control (IMC) method is applied to the load frequency control (LFC) of multi-area power systems with of wind turbines. TDF-IMC needs only to tune two parameters and can achieve good disturbance rejection performance. For implementation, IMC controllers are approximated with PID controllers. A frequency response dynamic model including simplified wind turbine is used in the design and simulation, and the physical constraints such as generation rate constraint (GRC) and speed governor dead band are considered. Simulation results show that the proposed method can damp the frequency and tie-line exchange power deviation quickly, and is robust to parameter variations. Furthermore, the participation of wind turbines in LFC can enhance the total system performance.

Since a Superconducting Magnetic Energy Storage (SMES) unit with a self–commutated converter is capable of controlling both the active and reactive powers simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This paper presents a novel control method of SMES with a self-tuned Fuzzy Proportional Integral (FPI) controller associated with the Automatic Generation Control (AGC) for improving Load Frequency Control (LFC) in a single area power system. Boiler dynamics and nonlinearities such as governor dead band (DB) and generator rate constraints (GRC) are considered in the developed comprehensive mathematical model of a single area isolated power system. The effects of the self–tuning configuration of FPI controller in AGC on SMES control is compared with that of fixed gain PI controlled AGC. It is seen that with addition of FPI controller, SMES can perform a more effective primary frequency control for single area power system. Key words: Load frequency control; single area power system; automatic generation control; superconducting magnetic energy storage unit; fuzzy proportional integral controller

Improved load frequency control in power systems with high penetration of wind farms using robust fuzzy controller

Fractional order phase lead-lag controller (FOPLC) is a generalization of classical phase lead-lag controller (CPLC) using fractional calculus. Nowadays, fractional order controllers (FOC) have found wide applications in various aspects of power system control and operation. In this paper, FOPLC are used in structure of flexible ac transmission system (FACTS) based frequency stabilizer to enhance the dynamic performance of automatic generation control (AGC) system. So, Thyristor controlled series capacitor (TCSC) based damping controller with FOPLC structure is proposed in coordination with secondary integral load frequency controller (LFC). The controller is optimized via an improved particle swarm optimization (IPSO) algorithm. The dynamic performance of the proposed controller is compared with CPLC using eigenvalue analysis and time domain simulations. An interconnected multi-source realistic power system with TCSC in series with the tie-line is investigated considering the nonlinearity effects of generation rate constraint (GRC) and governor dead band (GDB). Simulation results reveal that FOPLC based TCSC damping controller achieves superior dynamic performance under various load perturbation patterns in terms of decreased performance index, settling time and amplitude of oscillations. Furthermore, the robustness of the proposed controller has been tested for large uncertainties in system parameter and loading condition.

This paper presents the simulation of multi area multi source restructured power system for Load Frequency Control (LFC). Initially, a more practical multi area diverse source power system with the consideration of non-linearities such as Time Delay (TD) and Generation Rate Constraint (GRC) are considered. PID controller with derivative filter (PIDF) is evaluated to solve the LFC problem. Each generating source is provided with different controller which gives better control action and hence better dynamic performance of the system. The gains of the PIDF controller are optimized using an Integral of Time multiplied by Absolute value of Error (ITAE) criterion employing of Differential Evolution (DE) algorithm. Finally, Fuzzy-PID controller with derivative filter coefficient (Fuzzy PIDF) is proposed and better dynamic performance is obtained compared to PIDF controller.

Load frequency control (LFC) is vital for balancing power generation with fluctuating power demand. It ensures that the system frequency and tie-line power are maintained at their desired levels. The design of an LFC system is crucial for the automation of power systems. This article introduces a Fuzzy Proportional-Integral-Derivative (FPID) control approach for LFC in an interconnected reheat thermal power system, utilizing a Particle Swarm Optimization (PSO) method and incorporating the Generation Rate Constraint (GRC) as nonlinearities. The proposed controller offers the advantage of effectively managing system nonlinearities while being better than classical controllers. The response of the FPID controller is contrasted with both the conventional Proportional-Integral (PI) controller and the Fractional Order PID (FOPID) controller, in scenarios both including and excluding the Generation Rate Constraint (GRC). The response of the system is analyzed by considering load disturbances in each region of the integrated power network.

Transmission networks face continuous electrical and mechanical stresses due to increasing system challenges and power losses. Transmission networks require special focus and detailed studies each time a load or a generator emerges to the grid. The interline power flow controller (IPFC) is a relatively new scheme that is implemented in the transmission network to improve transmission efficiency, decrease transmission losses, and enhance voltage profile. In this paper, the interline power flow controller’s impact on transmission network performance is investigated as it is implemented within the IEEE 5-bus, 14-bus, and IEEE 57-bus systems. In addition, the whale optimization algorithm (WOA) is used to optimize the interline power flow controller locations within the system to achieve optimal transmission system performance. WOA performance is also compared to genetic algorithm (GA) and particle swarm optimization (PSO) algorithms, and the superiority of the proposed WOA-based control is proved. The robustness of the optimized system against load variations is investigated and the results introduced affirm the capability of the interline power flow controller to enhance transmission network efficiency.

This paper proposes a novel load frequency control (LFC) approach formulated on an optimal structure of the coefficient diagram method (CDM) in a two-area thermal power system. As part of a realistic analysis, nonlinearities related to governor dead band (GDB) and generation rate constraint (GRC) have been considered. In this article, a hybrid CDM method is combined with the optimization of its mathematical equations to achieve an innovative controller. Furthermore, a new metaheuristic optimization technique called the water cycle algorithm (WCA) is used to determine the optimal coefficients of the CDM controller. For the purpose of demonstrating the validity of the proposed scheme, a wide range of uncertainties in the dynamic parameters of a nonlinear power system were tested. In addition, a comparative study is presented between the results obtained from a classical integral, CDM alone, optimized fuzzy, optimized PID, and the suggested controller. In this new approach to improved control, algebraic support provides a robust and responsive controller that can provide fast and stable dynamic responses and effectively overcome the detrimental effects of nonlinearities and uncertainties in the parameters of the power system.