Improving load frequency control in autonomous microgrid via Fick's law-based demand optimization.

Recent methodology based Harris Hawks optimizer for designing load frequency control incorporated in multi-interconnected renewable energy plants

Load frequency control is always a crucial aspect in delivering quality power in integrated power system. This paper proposes an optimally tuned Proportional-Integral-Derivative (PID) controller to remove frequency errors caused by unexpected load fluctuations while ensuring tie-line power exchange. Moreover, the threearea power system with non-linearities such as Generation Rate Constraint and Governor Dead Band has been investigated. For tuning the parameters of PID controller Improved Grey Wolf Optimization (IGWO) has been used. The dynamic response of optimized PID controller have been compared with the result obtained from Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Sine Cosine Algorithm (SCA).

An adaptive CGPC based anti-windup PI controller with stability constraints for the intermittent power penetrated system

This paper describes the load frequency control (LFC) of two area interconnected hydro-thermal system using conventional proportional - integral (PI) controller and fuzzy logic controller (FLC). The thermal system is incorporated with governor dead band, generation rate constraint and boiler dynamics. The hydro system is incorporated with generation rate constraint. The conventional PI controller does not yield adequate control performance with the consideration of non-linearities and boiler dynamics. To overcome this drawback FLC has been employed in the system. The aim of FLC is to restore the frequency and tie line power in very smooth way to its nominal value in the shortest possible time. Time domain simulations are used to study the performance of the power system. System performance is examined considering 1% step load perturbation in either area of the system.

In this paper, automatic generation control (AGC) problem of an interconnected two-area multi-source power system is investigated. Each control area includes generations from reheat thermal, gas, and hydro units. Appropriate dynamic models are used for simulation of physical constraints of governor dead band (GDB) effect in the reheat thermal and generation rate constraint (GRC) in the reheat thermal and hydro generating units. This paper demonstrates that evaluating the dynamic performance of AGC without regarding these issues does not show precise and realistic results. A simple integral (I) controller is considered as secondary load frequency controller (LFC) loop. The LFC design is formulated as an optimization problem in which integral of time multiplied squared error (ITSE) performance index is minimized by an improved particle swarm optimization (IPSO) algorithm to adjust I controller. The LFC performance is evaluated under step, sinusoidal and random load perturbation patterns. To show the robustness of the proposed approach, sensitivity analyses are performed under various uncertainty scenarios. All simulations are performed in MATLAB/SIMULINK environment. The results are compared with the case of without considering the GDB and GRC non-linearity effects. The results demonstrate that with considering the GRC and GDB, the oscillations are not damped effectively and even they are increasing under uncertainty conditions.

Unpredictable high renewable shares in standalone microgrid (MG) system with stochastic load demands introduces an unavoidable mismatch among loads and sources. This mismatch directly impacts the system frequency that can be mitigated via applying a suitable load frequency control (LFC) scheme. This brief proposes a maiden attempt of marine predator algorithm (MPA) assisted one plus proportional derivative with filter-fractional order proportional-integral ((1+PDF)-FOPI) controller to obtain the proper power flow management among loads and sources. The investigated MG system consists of a photovoltaic (PV) system, a wind turbine (WT) generator (WTG), and a diesel engine generator (DG) as the distributed energy sources, and an ultracapacitor (UC) and a flywheel are chosen as the energy storage elements (ESEs). Various system nonlinearities such as governor dead-band (GDB) and generation rate constraint (GRC) are also considered reflecting the practical scenario. Five state-of-the-art optimization techniques and three traditional controllers, PID, FOPID, and PI-PD, are vividly compared to assess the proposed scheme’s performance. The parametric uncertainties are considered to obtain the robust performance of the proposed control scheme. An eigenvalues-based stability evaluation of the considered plant employing the proposed LFC scheme is also included in this work. In the worst situation, the maximum frequency deviation is obtained as -0.016 Hz, which is entirely satisfactory and under the range of the IEEE standard. Finally, a modified New England IEEE-39 test bus system is chosen to perform the real-time validation.

Load frequency control (LFC) remains a critical challenge in ensuring the stability of modern power grids. The integration of nonlinear dynamics into LFC design is paramount to achieving robust performance, which directly underpins grid reliability. This study introduces a novel hybrid control strategy—a fuzzy fractional-order proportional–integral–derivative (Fuzzy FOPID) controller augmented with a proportional–integral (PI) compensator—for LFC applications in two distinct dual-area interconnected power systems. To optimize the controller’s parameters, the recently developed Catch Fish Optimization Algorithm (CFOA) is employed, leveraging the Integral Time Absolute Error (ITAE) as the primary cost function for precision tuning. A comprehensive comparative analysis is conducted to benchmark the proposed controller against the existing methodologies documented in the literature. Nonlinear elements’ impact on the system stability is also investigated. The investigation evaluates the impact of critical nonlinearities, including governor dead band (GDB) and generation rate constraints (GRCs), on system performance. The simulation results demonstrate that the CFOA-tuned Fuzzy FOPID + PI controller exhibits superior robustness and dynamic response compared to conventional approaches, effectively mitigating frequency deviations and maintaining grid stability under nonlinear operating conditions. Furthermore, the CFOA demonstrates marginally superior convergence and tuning accuracy relative to the widely adopted Particle Swarm Optimization (PSO) algorithm. These findings underscore the proposed controller’s potential as a high-performance solution for real-world LFC systems, particularly in scenarios characterized by nonlinearities and interconnected grid complexities. This study advances the field by bridging the gap between fractional-order fuzzy control theory and practical power system applications, offering a validated strategy for enhancing grid resilience in dynamic environments.

A fuzzy cascaded PI−PD (FCPIPD) controller is proposed in this paper to optimize load frequency control (LFC) in the linked electrical network. The FCPIPD controller is composed of fuzzy logic, proportional integral, and proportional derivative with filtered derivative mode controllers. Utilizing renewable energy sources (RESs), a dual-area hybrid AC/DC electrical network is used, and the FCPIPD controller gains are designed via secretary bird optimization algorithm (SBOA) with aid of a novel objective function. Unlike the conventional objective functions, the proposed objective function is able to specify the desired LFCs response. Under different load disturbance situations, a comparison study is conducted to compare the performance of the SBOA-based FCPIPD controller with the one-to-one (OOBO)-based FCPIPD controller and the earlier LFC controllers published in the literature. The simulation’s outcomes demonstrate that the SBOA-FCPIPD controller outperforms the existing LFC controllers. For instance, in the case of variable load change and variable RESs profile, the SBOA-FCPIPD controller has the best integral time absolute error (ITAE) value. The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. Furthermore, the work is expanded to include electric vehicle (EV), high voltage direct current (HVDC), generation rate constraint (GRC), governor dead band (GDB), and communication time delay (CTD). The result showed that the SBOA-FCPIPD controller performs well when these components are equipped to the system with/without reset its gains. Also, the work is expanded to include a four-area microgrid system (MGS), and the SBOA-FCPIPD controller excelled the SBOA-CPIPD and SBOAPID controllers. Finally, the SBOA-FCPIPD controller showed its superiority against various controllers for the two-area conventionally linked electrical network.

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller’s robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller’s robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics.

In this paper Load Frequency Control (LFC) of a two area power system is discussed considering three power plants viz. thermal power plant, hydro power plant and wind power plant. For the control purpose, a Proportional-Integral-Derivative (PID) controller with derivative filter is used to attenuate the noise additionally. Redox Flow Battery (RFB) in feedback in each area and Interline Power Flow Controller (IPFC) with tie-line is used to enhance the system performance. For realistic discussion of the proposed system certain physical non-linearities like Generation Rate Constraints (GRC) and governor dead band is added in the system. Finally, a new powerful meta-heuristic Whale optimisation Algorithm (WOA) in LFC mechanism is used to optimise PID gains and filter coefficients of the system and minimise Performance Index (PI) i.e., Integral Square Error (ISE).

DE optimized parallel 2-DOF PID controller for load frequency control of power system with governor dead-band nonlinearity

This paper presents dynamic performance comparison of a fuzzy logic-based proportional, integral, and derivative controller (FPID) with different membership functions such as triangular, trapezoidal, and Gaussian for load frequency control (LFC) in an interconnected two-area thermal power system. The parameters of controller are optimized by using spider monkey optimization (SMO) algorithm. The superiority of the proposed algorithm is established by comparing the results with popularly used algorithms like particle swarm optimization (PSO) and teaching–learning-based optimization (TLBO). Initially, the linearized model of the system is considered with reheat turbine; then, the study is extended by imposing nonlinearity such as generation rate constraints (GRC) and governor dead band (GDB). The result comparison is analyzed using various time domain specifications like peak undershoot, peak overshoot, and settling time of different area frequencies and tie-line power deviation between them applying a step load perturbation (SLP) of 1%.

Load frequency control (LFC) for power systems with governor deadband (GDB) and generation rate constraint (GRC) non‐linearities is discussed in this study, with the objective to add anti‐windup schemes for any designed LFC controller, so that the stability and performance of the existing LFC controller can be retained when there are non‐linearities. Effects of GDB and GRC on the performance of LFC controllers are first analysed via describing function method. Anti‐windup schemes are then proposed to compensate the GDB and GRC non‐linearities. For GDB, the error between the realistic and the ideal outputs of the generator is added to the output of LFC controller for rejection, and for GRC, the error between the realistic and the ideal outputs of the turbine is fed back to the observer of the LFC controller for estimation and elimination. Simulation results show that the compensation schemes are effective in overcoming the adverse effects of GDB and GRC.

The increasing integration of regional power grids, rising penetration of multi-generation sources, and day-ahead power agreements have raised the operational challenges on deregulated modern electric energy systems. Among various challenges, frequency regulation becomes more prominent in the restructured power system (RPS) due to increased uncertainties and intricacies among other operational challenges. A minor deviation in system frequency affects the safety, quality, stability, and operation of the interconnected power system (IPS). An appropriate control mechanism and energy storage device are essential to regulate the system's dynamic responses during continuously varying loading conditions. This study proposed a novel Salp swarm algorithm (SSA) optimized fuzzy-based proportional-integral-derivative filter (FPIDF) controller with redox flow battery (RFB) to regulate the frequency of a realistic multi-area multi-source (thermal-hydro-gas) interconnected power system. All probable contract transaction scenarios are simulated that can be possible in a deregulated power industry. Various nonlinearities such as time delay (TD), governor dead band (GBD), and generation rate constraint (GRC) are incorporated to resemble the realistic operational conditions of the IPS. The effectiveness of the suggested controller has been validated by comparing the system performances with a recently published sine-cosine algorithm (SCA) based proportional-integral (PI) controller and SSA-PID controller. The investigation has been further extended by incorporating RFB in the proposed system. The study reveals that the suggested controller provided superior system control under various system uncertainties in all contact scenarios of the competitive electricity market. Additionally, the system performances have been significantly enhanced due to quick response and precise control offered by RFB.

Renewable energy sources (RES) which are the integral part of the microgrid rise the challenges in controlling the frequency owing to their intermittent nature. The distributed generation (DG) that includes RES may rise to stability issue, frequency deviation or power mismatch issues, hence it is requisite to balance the above said parameters. This work explores the studies on two area microgrid system in which one area comprises of small hydro and another one is having DG. The electric vehicle (EV) is added in both the areas. The EV can be implemented as V2G (source) or G2V (load). The DG contains solar photovoltaic (PV), aqua electrolyzes (AE), fuel cell (FC), wind turbine system (WTS) and diesel engine generator (DEG). The system is also considered the effect due to communication delay. To check over the control on load frequency, integral (I) and proportional-integral (PI) controllers are tested under various loading conditions like step load disruption (SLD) in both the areas and random load disruption (RLD) in Area 1. To obtain the gains of these controllers prevalent firefly algorithm (FA) technique is used. The results are taken in MATLAB/Simulink platform which shows that PI controller shows excellent result in comparison to I in terms of peak overshoot (PO), peak undershoot (PU) and setting time (ST).