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Load frequency control is an important factor of supplying quality electricity in an interconnected power system. As a result, an optimally tuned Proportional-Integral-Derivative (PID) controller is proposed in this work to eliminate frequency errors caused by unexpected load changes while maintaining tie-line power exchange. The PID controller is tuned using several optimization techniques such as GA, PSO, SCA, and GWO. A two-area power system with Generation Rate Constraint is studied in the first instance, and a three-area thermal power system with both generation rate constraint and dead band effect is considered in the second case. In both scenarios, a PID controller is employed for each area. When compared to the results of other optimization approaches for the same integrated power system, such as Genetic Algorithm, Particle Swarm Optimization, and Sine Cosine Algorithm, the GWO-based PID controller outperforms them in both scenarios.  According to the simulation findings, the GWO technique gives better dynamic responses in terms of overshoot value, settling time, and Integral Time Absolute Error.  Finally, to evaluate the robustness of the suggested optimization strategies, sensitivity analysis is done by modifying the system parameters (turbine time constant, governor time constant, and both simultaneously) in the range of 25% from their nominal values.

Power systems are the most complex systems that have been created by men in history. To operate such systems in a stable mode, several control loops are needed. Voltage frequency plays a vital role in power systems which need to be properly controlled. To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems. Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance. Likewise, the power exchanges between different control areas are controlled by LFC approaches. In recent decades, many control approaches have been suggested for LFC in power systems. This paper presents a comprehensive literature survey on the topic of LFC. In this survey, the used LFC models for diverse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems. Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups. The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC.

This work presents the power generation control of a two-area, hybrid, deregulated power system integrated with renewable energy sources (RES). The incorporation of appropriate system non-linearities and RES into the power system makes it complex, but more practical. The hybrid deregulated power system with RES is a complex nonlinear system that regularly exposes the major issue of system dynamic control due to insufficient damping under varying loading circumstances. The generation-demand equilibrium point of the power system varies following a contingency; hence, it becomes difficult to maintain the appropriate equilibrium point via traditional control approaches. To solve this problem, novel control approaches, along with rapid-acting energy storage devices (ESD), are immediate need for advanced power systems. As a result, various secondary controllers are inspected for improvements in system dynamics. A performance comparison infers the cascaded ID-PD controller as the optimum one. The secondary controller gains are successfully optimized by the powerful satin bowerbird optimization (SBO) technique. Additionally, the impact of a super-conducting-magnetic-energy-storage (SMES) device in system dynamics and control of developed power system is analyzed in this study. A sensitivity evaluation (SE) infers that SBO-optimized cascaded ID-PD controller gains are strong enough for alterations in load perturbations, system loading, inertial constant (H), solar irradiance and the DISCO involvement matrix (DIM).

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to demonstrate the superiority of the proposed controller, the dynamic performance is compared with previous work based on an optimized controller in the third case study. Finally in the fourth case study, a sensitivity analysis is carried out through parameters variations in the nonlinear PV-thermal hybrid system. The novel application of the adaptive controller into the LFC leads to enhance the system performance under disturbance of different sources of renewable energy. Moreover, a robustness test is presented to validate the reliability of the proposed controller.

This paper proposes a design of Sliding Mode Control (SMC) for Load Frequency Control (LFC) in a two-area electrical power system. The mathematical model design of the SMC is derived based on the parameters of the investigated system. In order to achieve the optimal use of the proposed controller, an optimisation tool called the Bees Algorithm (BA) is suggested in this work to tune the parameters of the SMC. The dynamic performance of the power system with SMC employed for LFC is studied by applying a load disturbance of 0.2 pu in area one. To validate the supremacy of the proposed controller, the results are compared with those of recently published works based on Fuzzy Logic Control (FLC) tuned by Teaching–Learning-Based Optimisation (TLBO) algorithm and the traditional PID optimised by Lozi map-based Chaotic Optimisation Algorithm (LCOA). Furthermore, the robustness of SMC-based BA is examined against parametric uncertainties of the electrical power system by simultaneous changes in certain parameters of the testbed system with 40% of their nominal values. Simulation results prove the superiority and the robustness of the proposed SMC as an LFC system for the investigated power system.

This paper presents the design of an H∞-based Restricted Static Output Feedback (RSOF) controller with regional pole placement in Linear Matrix Inequality (LMI) framework for Load Frequency Control (LFC) of a 2-area Interconnected Power System (IPS). The motivation behind the RSOF controller is to develop a controller with a predefined structure for implementing centralized and decentralized control strategy as per need. In this work a new stabilization criterion is developed by choosing circle and strip LMI regions for pole-placement along with the use of Particle Swarm Optimization (PSO) technique to tune the scalar parameters for the feasibility of the developed LMI criterion. The designed controller (both centralized and decentralized structure) with the above modifications improves the transient response of the frequency output. The designed controller is tested on a 2-area LFC model incorporating both conventional and renewable energy sources. Simulation results validate the effectiveness of the designed controller in attenuating disturbance and also enhancing the transient response. A comparative analysis is presented for various controllers, highlighting their performance differences.

The mismatch between power generation and load demand causes unwanted fluctuations in frequency and tie-line power, and load frequency control (LFC) is an inevitable mechanism to compensate the mismatch. For this issue, this paper explores the influence of energy storage device (ESD) on ameliorating the LFC performance for an interconnected dual-area thermal and solar photovoltaic (PV) power system. Initially, to alleviate the frequency and tie-line power deviations, a proportional-integral (PI) controller is chosen and utilized in the system due to its effectiveness and simplicity in practice. For achieving the highest performance from this controller, salp swarm algorithm (SSA) is employed to search for optimal controller parameters by using integral of time-multiplied absolute error (ITAE) criterion. To affirm the contribution of SSA optimized PI controller, it is contrasted with a recent approach utilizing PI controller optimized by genetic algorithm (GA) and firefly algorithm (FA). It is observed that the results acquired for SSA are better than for GA and FA. To improve the system performance further, ESD such as redox flow battery (RFB) famous for its excellent disturbance rejection capability is integrated with the thermal power unit for the first time in the literature. It is divulged from the results that the system performance with RFB has boosted considerably with regard to shorter settling time, less undershoot/overshoot and smaller ITAE value of the frequency and tie-line power fluctuations. According to the sensitivity analysis, our proposal is found robust against system parameters variations and different loading conditions.

In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G) technique, electric vehicles (EVs) can act as mobile energy storage units, which could be a solution for load frequency control (LFC) in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC) theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG) are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances.

In this article, a novel methodology is proposed by utilizing a technique which, in light of the change in the African vulture optimization known as Sine Cosine, adopted an African vulture optimization algorithm (SCaAVOA)-based tilt integral derivative (TID) regulator for the load frequency control (LFC) of a five-area power system with multi-type generations. At first, the execution of the Sine Cosine-adopted calculation is tried by contrasting it with the standard AVOA calculation while considering different standard benchmark functions. To demonstrate the superiority of the proposed SCaAVOA algorithm, the results are contrasted using different standard approaches. In the next stage, the proposed method is used in a five-area thermal power system and is likewise applied to a five-area, ten-unit system comprising different conventional sources as well as some renewable energy sources. The performance analysis of the planned regulator is completed for various system boundaries and loading conditions. It is seen that the said regulator is more viable in comparison to the other standard controllers.