A Novel Secretary Bird Optimization‐Based Frequency and Voltage Control of Single Area and Multi Area Power Systems With Hydrogen‐Based Energy and Electric Vehicle Integration

In this study, a new meta-heuristic based evolutionary computational technique is reported for solving Automatic Generation Control (AGC) or Load Frequency Control (LFC) issue in multi-area power system with nonlinearity and an energy storage unit. Multi-area power system consists of two area equal reheat thermal power systems with Governor Dead Band (GDB) and Generation Rate Constraint (GRC) nonlinearity and boiler dynamics and energy storage element. During normal operating conditions, there no change in system parameters (Frequency and tie-line power flow) and stability. When sudden load demand occurs in any one of interconnected power, it affects system parameters and stability and system yield damping oscillation in their response with steady state error and settling time. In order to mitigate this biggest pose the proper selection of the controller is a major issue. In power system Automatic Voltage Regulator (AVR) loop is a primary control loop and in addition Proportional-Integral-Derivative (PID) controller is proposed as a secondary controller in AGC. The better performance of power system depends on proper selection of controller gain and also depends on the selected objective function for optimization of controller gain values. A new meta-heuristic based Ant Colony Optimization (ACO) evolutionary computational technique is used for tuning of PID controller with different operating conditions. Three different objective functions Integral Square Error (ISE), Integral Time Absolute Error (ITAE) and Integral Absolute Error (IAE) are used in ACO for tuning of controller gain. An electromechanical oscillation of power system is effectively damp out by introducing an energy storage unit in two area interconnected power system because of their inherent energy storage capacity with kinetic energy of the rotor. In this study Hydrogen generative Aqua Electroliser (HAE) with a fuel cell is incorporated into the investigated power system. The response of the proposed approach with different cost functions are obtained and compared with and without considering the effect of energy storage unit in LFC problem.

In the continually increasing size and configuration of the modern power system with unpredictable load and integration of electric vehicles (EVs), the usage of intelligent and effective scheme is essential to control system frequency. This work suggests a hybrid African vultures optimization algorithm (AVOA) and pattern search (hAVOA-PS)-based fuzzy proportional integral derivative (FPID) structure for frequency control of a nonlinear power system with EVs. To illustrate the dominance of the projected hAVOA-PS algorithm, initially, PI controllers are considered and results are equated with AVOA, particle swarm optimization, and genetic algorithm methods. To further enhance the dynamic performance, PID and FPID controllers are considered. The dominance of FPID over PID and PI controllers is shown. In the next step, EVs are integrated into the test system and a comparative investigation of hAVOA-PS-based PI/PID/FPID and FPID+EV is presented. To exhibit the superiority of projected frequency control scheme in maintaining the stability of system under different disturbance conditions like load increase in area-1 only, load decrease/increase in all areas and large load increase in all areas are considered. It is noticed that the proposed hAVOA-PS-based FPID controller in the presence of EV is able to maintain system stability for all the considered cases, whereas other compared approaches fail to maintain stability in some cases. The effectiveness of the projected frequency control method is equated with some recently suggested approaches in a standard two-area system. At last, MATLAB results are equated with Open Real-Time Digital Simulators (OPEN-RT) outcomes to validate the feasibility and effectiveness of the proposed scheme for practical applications. Cite this article as: P. Mohan Dash, A. Kumar Baliarsingh and S.K. Mohapatra, “Application of fuzzy proportional integral derivative controller in automatic generation control using hybrid African vultures optimization algorithm-pattern search optimization algorithm for frequency control of power system with electric vehicles,” Electrica, 23(3), 414-428, 2023.

This paper deals with automatic generation control (AGC) and Automatic voltage regulator (AVR) in a two-area interconnected deregulated power system with and without direct current (DC) link. Now a day, increase in generation from renewable energy sources (RES) in an integrated power system is keep on increasing significantly. This present work describes a system dynamic model, with thermal generating sources and RES (Solar and wind Power model) for studying the AGC and AVR of system. The secondary controller in the AGC loop is optimally designed and compared by considering the Proportional integral (PI), Proportional integral derivative (PID) and Fuzzy logic controller (FLC). The results show that the FLC with DC link gives the better results as compared with other two controllers. The simulation result reveals that FLC gives better performance with respect to number of overshoots, settling time, peak deviations, and oscillations in both constant and variable distributed participation matrix. All the control strategies are implemented and the simulation results are showed using MATLAB/Simulink.

Frequency, tie-line power, and the terminal voltages of synchronized generators must all be kept within prescribed limits to ensure the stability of an interconnected power grid through combined automatic generation control (AGC) and automatic voltage regulator (AVR) loops. Thermal power plants, electric vehicles, and renewable energy sources—including solar and wind, geothermal, and solar thermal power plants—form the two-area integrated power system in present research. A new cascade controller named the cascaded proportional integral derivative (PID) and fractional-order PID (CPID-FOPID) controller is proposed for the first time, whose performance is compared with the PID and FOPID controller. The results show that the proposed cascade controller outperforms PID and FOPID in delivering superior dynamic characteristics, including short settling times and low oscillation amplitudes. A new metaheuristic algorithm named the coot algorithm was applied to optimize the parameters of these controllers. The suggested controller outperforms FOPID in the combined AGC and AVR problem under uncertain conditions (random load disturbance, variable input of solar irradiation, and wind power). Robustness of the controller is tested with significant variation in the turbine time constant of the thermal and geothermal power plant. In this study, authors also investigated the best possible coordination between the superconducting magnetic energy storage (SMES) and gate-controlled series capacitor (GCSC) devices to control both voltage and frequency simultaneously. The effect of communication time to the power system is analyzed in this study. Additionally, the obtained results are satisfactorily validated using OPAL-RT real-time digital simulator.

Improved load frequency control of power system using LMI based PID approach

The modern electric grid is one the most complex man-made control systems. Proportional–integral–derivative (PID) controllers are widely used in a variety of applications including automatic generation control (AGC), automatic voltage regulators, power system stabilizers and flexible AC transmission system devices. Automatic generation control plays an important role in power system operation to maintain the frequency within an acceptable range and to properly respond to load changes under normal conditions. Using the PIDs, AGC keeps the balance between generation and load demand in order to minimize frequency deviations. Furthermore, the AGC regulates the tie-line power exchange and facilitates bilateral contracts spanning over several control areas, thus ensuring reliable operation of the interconnected transmission system. Since the power system load variations occur continually, generation control is set to automatic to restore the frequency after disturbances. The PID controllers have the advantage of simple structure, good stability, and high reliability. However, a robust and efficient tuning of PID parameters are still being investigated using different techniques. One of the recent areas of such studies is nature-inspired algorithms. The main objective of utilizing nature-inspired algorithms is to optimize parameters of several controllers simultaneously. This paper reviews the latest applications of various nature-inspired algorithms for optimal design of AGC control in power systems. Different algorithms, proposed in the recent literature, are classified based on the type of controller, objective function and test systems.

This paper introduces the Walrus Optimization Algorithm (WaOA) to address load frequency control and automatic voltage regulation in a two-area interconnected power systems. The load frequency control and automatic voltage regulation are critical for maintaining power quality by ensuring stable frequency and voltage levels. The parameters of fractional order Proportional-Integral-Derivative (FO-PID) controller are optimized using WaOA, inspired by the social and foraging behaviors of walruses, which inhabit the arctic and sub-arctic regions. The proposed method demonstrates faster convergence in frequency and voltage regulation and improved tie-line power stabilization compared to recent optimization algorithms such as salp swarm, whale optimization, crayfish optimization, secretary bird optimization, hippopotamus optimization, brown bear optimization, teaching learning optimization, artificial gorilla troop optimization, and wild horse optimization. MATLAB simulations show that the WaOA-tuned FO-PID controller improves frequency regulation by approximately 25%, and exhibits a considerable faster settling time. Bode plot analyses confirm the stability with gain margins of 5.83 dB and 9.61 dB, and phase margins of 10.8 degrees and 28.6 degrees for the two areas respectively. The system modeling and validation in MATLAB showcases the superior performance and reliability of the WaOA-tuned FO-PID controller in enhancing power system stability and quality under step, random step load disturbance, with nonlinearities like GDC and GDB, and system parameter variations.

This technical write-up emphasizes on combined regulation of frequency - voltage in a restructured renewable energy integrated power system under PoolCo and bilateral transactions. A two area coordinated modeling of area load frequency control (ALFC) and automatic voltage regulator (AVR) is carried out in presence of thermal, hydro, systems. Non linearities are incorporated to get a realistic insight with scheduled delay, rate constraint, and dead band. A powerful algorithm namely Firefly Algorithm based Industrial controllers serve the purpose of classical controller as Secondary control in the considered two area power system. Selection of best secondary controller among integral (I), proportional-integral (PI) and proportional-integral - derivative (PID) controller is carried out based on a fair comparison under Pool Co Transaction Scenario. PID controller serves better. Further investigations are carried out with excitation in AVR loop along with step load perturbation at ALFC in both control areas. PID outperforms I and PI in stabilizing the system responses such as frequency deviation, tie-power deviation and voltage deviations.

Networked load frequency control of multi-area uncertain power systems via adaptive event-triggered communication scheme

This paper presents a comparative study between Active Disturbance Rejection Control (ADRC) based Load Frequency Control (LFC) and proportional-integral-derivative (PID) based LFC. Both, single-area power system and multi-area power system have been considered where area control error (ACE) has been regulated in the presence of uncertainties in system dynamics and external disturbances. The ADRC proves to be a capable replacement of PID with unmistakable advantage in performance for load frequency control in power system.

An interconnected power system requires specific restrictions to be maintained for frequency, tie-line power, and the terminal voltage of synchronized generators to avoid instability. Therefore, frequency stability and voltage regulation issues are covered individually and jointly in the current research work. Initially in test system 1, automatic generation control (AGC) investigations are done on two interconnected systems with thermal plants and electric vehicles in one area and distributed generation and electric vehicles in other area. The automatic voltage regulator (AVR) problem alone is chosen for investigation in test system 2. The third test system addresses the combined AGC and AVR issues. The performance of the fractional-order tilt-integral-derivative (TID) controller is compared with that of a widely used proportional integral derivative (PID) controller in all three test systems studies. The findings demonstrate better performance of the TID controller than PID in terms of providing superior dynamic metrics, such as low peak overshoots, undershoots, and settling time, as well as decreased oscillations amplitudes. Additionally, TID performs better than PID despite randomized load disturbance, system non-linearities, and time delays in AGC and the combined AGC and AVR problem. The PSO-tuned TID controller is insensitive to variation in load damping factor and time constants of the AVR system. Finally, the results are validated by an OPAL-RT 4510 real-time digital simulator.

This article presents the performance comparison of various tilt controllers in coalesced frequency and voltage control of multi-area multi-unit interconnected power system with their Automatic Load Frequency Control (ALFC) and Automatic Voltage Regulator (AVR) structures. Every area has a thermal plant, along with a Wind turbine plant in Area-1, solar thermal plant in Area-2, and Dish-Stirling solar thermal unit in Area-3. The two degrees of freedom Integral minus Tilt-Derivative with filter (2DOF I-TDF) controller is perceived as supplementary and core controller of ALFC and AVR structures. The optimal controller values are achieved with Harris Hawks Optimization (HHO) technique. The proposed 2DOF I-TDF controller is found superlative in comparison to TID, TIDF, I-TDF controllers concerning all time-domain indices. Likewise, the system dynamics are also investigated with various controllers in AVR system. The supremacy of the proposed controller is assessed with random load perturbation. In the end, the sensitivity analyses are achieved with different system loading conditions which convey the robustness of the proposed controller.

The integration of plug-in electric vehicles (PEVs) has a number of benefits, due to which the number of PEVs integration to the power system is likely to rise. One major benefit of PEVs integration is their contribution in the frequency regulation of the system under load fluctuations. This paper presents an aggregate model of a power system with the integration of renewable energy sources (RES) and PEVs. For the purpose of secondary frequency control, Wind Driven Optimized two degree of freedom Proportional-Integral-Derivative (2DOF-PID) controller is applied. The impact of integrating RES and PEVs to the multi-area interconnected power system has been studied vigorously under nominal system conditions in this paper. It is found out from the studies that PEVs play a very vital role in frequency regulation. Also, the effect of PEVs and RES has been studied under random loading conditions, and it is revealed that the impact is very effective.

This paper addresses an unequal interconnected multi-area multi-source power system whose frequency, voltage, and tie-line power are regulated in the conventional scenario. The proposed system consists of three areas with common thermal and wind plants. Besides these plants, Area-1, 2 and 3 have gas turbine, diesel and DSTS plant respectively. A maiden attempt was made to implement the cascaded Proportional-Integral-Derivative with Filter (PIDN)-Tilt-Integral-Derivative with Filter (TIDF) controller in both Automatic Load Frequency Control (ALFC) and Automatic Voltage Regulator (AVR) loops. A nature-inspired meta-heuristic algorithm called Harris Hawks Optimization (HHO) is successfully applied to the unified ALFC and AVR studies to optimize the controller parameters showing that PIDN-TIDF controller predominates in all time-domain indices. AVR impact proclaims a substantial increase in system dynamics. The system dynamics is studied with the impact of wind turbines and system nonlinearities. System performance is measured by Integral Squared Error (ISE) with 1% disturbance in Area-1.

The frequency and terminal voltages in power systems are the two critical operating points that balance active and reactive powers, which must be maintained within predefined limits through automatic generation control (AGC) and automatic voltage regulator (AVR) control loops. To address this issue, in this manuscript, the problem of a combined AGC and AVR is solved using a non-integer order PID controller. Its parameters are adjusted using the recently proposed equilibrium optimiser (EO) technique. Along with conventional sources, renewable energy sources such as geothermal power plants and electric vehicles are considered. The EO-tuned non-integer order PID controller outperformed the traditional integer order PI and PID controllers in view of peak overshoots, undershoots and settling times. The performance of EO is evaluated and found superior against widely used particle swarm optimisation and firefly algorithms in the presence of non-integer order PID controller. Different case studies such as random load disturbance, the effect of nonlinearities, the impact of communication time delay and sensitivity analysis have been performed, which also test the heftiness of the non-integer order PID controller. The obtained results are verified using the real-time digital simulator OPAL-RT (OP4510) for nominal conditions.