RESUMEN

The Load Frequency Control (LFC) scheme, with its primary aim being the maintenance of uniform frequency, has been a heavily researched topic for decades. Achieving a consistent frequency necessitates a delicate balance between load demand and power generation. Researchers strive to find an optimal solution within the LFC domain-one that can effectively withstand drastic load fluctuations. Despite a plethora of efforts, the LFC dilemma remains unresolved, complicated by factors such as dwindling demand-supply and the rapid integration of renewables. Furthermore, the lack of innovation in controller structure design exacerbates the complexity of solving modern LFC problems. Consequently, a robust control approach capable of handling uncertainties while simultaneously regulating system frequency becomes crucial. In light of this, we propose a novel hybrid control architecture called 2DOF-PID-TD. This architecture combines Two Degrees Of Freedom Proportional-Integral-Derivative (2DOF-PID) and Tilt-Derivative (TD) controllers. To optimize the proposed controller, we employ a metaheuristic called the Artificial Gorilla Troops Optimizer (AGTO), which mimics the social behavior and intelligence of gorilla troops. The proposed approach is analyzed in a realistic multi-area multi-source hydro-thermal system, accounting for nonlinearities, random load perturbations, and system parametric uncertainties. Experimental results, when compared with current state-of-the-art optimization algorithms and traditional controller structures, demonstrate the prowess of our approach in terms of precision, robustness, and resilience.

RESUMEN

In this paper, a hybrid load frequency control (LFC) scheme is proposed for multi-area interconnected power systems to decouple the intricate double control objectives, by dividing all subareas into the responsible areas and the free areas. The LFC in the responsible area has the function of regulating both the local frequency and the tie-line power, while the control objective of the LFC in the free area is thus simplified to regulate the local frequency only. Then, addressing the complex network coupling and uncertain dynamics, an integrated LFC controller is proposed for the free areas, which consists of two parts, namely, the coupling attenuation baseline controller and the disturbance compensation controller. The coupling attenuation baseline controller satisfying the predefined bounded L2-Gain condition is derived based on the solution to a multi-player zero-sum differential game. Additionally, a novel generalized integral observer is designed to estimate the system's integrated disturbance, and the corresponding disturbance compensation controller is derived. After that, the ultimately uniformly bounded (UUB) stability of the integrated LFC controller combining baseline controller and disturbance compensation controller is proven rigorously. Finally, the performance superiority of the proposed hybrid LFC scheme is validated by the simulations in challenging operating modes.

RESUMEN

Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as "Porpoising". This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.

RESUMEN

Electricity generation in Islanded Urban Microgrids (IUMG) now relies heavily on a diverse range of Renewable Energy Sources (RES). However, the dependable utilization of these sources hinges upon efficient Electrical Energy Storage Systems (EESs). As the intermittent nature of RES output and the low inertia of IUMGs often lead to significant frequency fluctuations, the role of EESs becomes pivotal. While these storage systems effectively mitigate frequency deviations, their high costs and elevated power density requirements necessitate alternative strategies to balance power supply and demand. In recent years, substantial attention has turned towards harnessing Electric Vehicle (EV) batteries as Mobile EV Energy Storage (MEVES) units to counteract frequency variations in IUMGs. Integrating MEVES into the IUMG infrastructure introduces complexity and demands a robust control mechanism for optimal operation. Therefore, this paper introduces a robust, high-order degree of freedom cascade controller known as the 1PD-3DOF-PID (1 + Proportional + Derivative-Three Degrees Of Freedom Proportional-Integral-Derivative) controller for Load Frequency Control (LFC) in IUMGs integrated with MEVES. The controller's parameters are meticulously optimized using the Coati Optimization Algorithm (COA) which mimics coati behavior in nature, marking its debut in LFC of IUMG applications. Comparative evaluations against classical controllers and algorithms, such as 3DOF-PID, PID, Reptile Search Algorithm, and White Shark Optimizer, are conducted under diverse IUMG operating scenarios. The testbed comprises various renewable energy sources, including wind turbines, photovoltaics, Diesel Engine Generators (DEGs), Fuel Cells (FCs), and both Mobile and Fixed energy storage units. Managing power balance in this entirely renewable environment presents a formidable challenge, prompting an examination of the influence of MEVES, DEG, and FC as controllable units to mitigate active power imbalances. Metaheuristic algorithms in MATLAB-SIMULINK platforms are employed to identify the controller's gains across all case studies, ensuring the maintenance of IUMG system frequency within predefined limits. Simulation results convincingly establish the superiority of the proposed controller over other counterparts. Furthermore, the controller's robustness is rigorously tested under ± 25% variations in specific IUMG parameters, affirming its resilience. Statistical analyses reinforce the robust performance of the COA-based 1PD-3DOF-PID control method. This work highlights the potential of the COA Technique-optimized 1PD-3DOF-PID controller for IUMG control, marking its debut application in the LFC domain for IUMGs. This comprehensive study contributes valuable insights into enhancing the reliability and stability of Islanded Urban Microgrids while integrating Mobile EV Energy Storage, marking a significant advancement in the field of Load-Frequency Control.

RESUMEN

Renewable energy sources (RESs) have become integral components of power grids, yet their integration presents challenges such as system inertia losses and mismatches between load demand and generation capacity. These issues jeopardize grid stability. To address this, an effective approach is proposed, combining enhanced load frequency control (LFC) (i.e., fuzzy PID- T I λ D µ ) with controlled energy storage systems, specifically controlled redox flow batteries (CRFBs), to mitigate uncertainties arising from RES integration. The optimization of this strategy's parameters is achieved using the crayfish optimization algorithm (COA), known for its global optimization capabilities and balance between exploration and exploitation. Performance evaluation against conventional controllers (PID, FO-PID, FO-(PD-PI)) confirms the superiority of the proposed approach in LFC. Extensive testing under various load disturbances, high renewables penetration, and communication delays ensures its effectiveness in minimizing disruptions. Validation using a standardized IEEE 39-bus system further demonstrates its efficiency in power networks grappling with significant renewables penetration. In summary, this integrated strategy presents a robust solution for modern power systems adapting to increasing renewable energy utilization.

RESUMEN

A three-stage decentralized controller design algorithm is developed to achieve setpoint tracking and disturbance rejection in MIMO systems with communication time delay, and nonlinearities such as saturation and dead band. The first stage involves reference model formulation. The second stage comprises equating approximate generalized time moments/approximate generalized Markov parameters of closed-loop system model with reference model at certain expansion points in s-plane to obtain synthesis-like equation, concerning products of unknown controller numerator and denominator polynomials. This process yields simultaneous linear equations, whose solution provides the coefficients of the product polynomials. In the third stage, the controller parameters are extracted from the product polynomials using exact model matching. The proposed method is illustrated by designing load frequency controller in traditional and restructured power systems under scenarios like system parameter uncertainties, random load variation, and time-varying communication delays. Simulation studies reveal the efficacy of the proposed technique over existing techniques. Furthermore, the practical implementation feasibility of the decentralized controller designed for the restructured power system is validated using the TMS320F28379D controlCARD.

RESUMEN

Recent widespread connections of renewable energy resource (RESs) in place of fossil fuel supplies and the adoption of electrical vehicles in place of gasoline-powered vehicles have given birth to a number of new concerns. The control architecture of linked power networks now faces an increasingly pressing challenge: tie-line power fluctuations and reducing frequency deviations. Because of their nature and dependence on external circumstances, RESs are analogous to continually fluctuating power generators. Using a fractional order-based frequency regulator, this work presents a new method for improving the frequency regulation in a two-area interconnected power system. In order to deal with the frequency regulation difficulties of the hybrid system integrated with RES, the suggested controller utilizes the modified form of fractional order proportional integral derivative (FOPID) controller known as FOI-PDN controller. The new proposed controllers are designed using the white shark optimizer (WSO), a current powerful bioinspired meta heuristic algorithm which has been motivated by the learning abilities of white sharks when actively hunting in the environment. The suggested FOI-PDN controller's performance was compared to that of various control methodologies such as FOPID, and PID. Furthermore, the WSO findings are compared to those of other techniques such as the salp swarm algorithm, sine cosine algorithm and fitness dependent optimizer. The recommended controller and design approach have been tested and validated at different loading conditions and different circumstances, as well as their robustness against system parameter suspicions. The simulation outcomes demonstrate that the WSO-based tuned FOI-PDN controller successfully reduces peak overshoot by 73.33%, 91.03%, and 77.21% for region-2, region-1, and link power variation respectively, and delivers minimum undershoot of 89.12%, 83.11%, and 78.10% for both regions and tie-line. The obtained findings demonstrate the new proposed controller's stable function and frequency controlling performance with optimal controller parameters and without the requirement for a sophisticated design process.

RESUMEN

In the current power landscape, renewable energy sources (RESs) have assumed a crucial role in satisfying consumer demand. However, as the deployment of renewables increases, certain challenges arise, including issues with system frequency stability, inertia, and damping reduction. To address these concerns, an innovative approach is suggested in this study. The proposed strategy aims to maintain frequency stability in a diverse-source power system that encompasses two interconnected regions incorporating RESs. The proposed strategy comprises a new multi-degree of freedom FOTID controller known as the MDOF-TIλDµN controller in the secondary control loop (SCL) and optimally controlled fuel cells (OFCL) to enhance the system's stability under the effect of renewable energy (RESs) fluctuations. In this context, the gains of the considered strategy (optimal MDOF-TIλDµN in addition to OFCL) have been picked out by using an innovative optimization approach known as the Capuchin search algorithm (CapSA). The statistical tests are used to examine the efficacy of the considered CapSA compared to those of other optimization strategies utilized in previous studies. Furthermore, the performance of the proposed controller in the SCL is verified by contrasting its performance with that of another suggested controller known as MDOF-PIDN as well as other controllers such as PD-IT, PDµN-IλT, 2DOF-TIλDµN, 3DOF-PIDN, 3DOF-TIDN, and 3DOF-PIλDµN. Additionally, grid nonlinearities, including Boiler Dynamics, Generation Rate Constraint, Governor Dead Band, and random communication time delay (CTD), are considered. Moreover, the proposed strategy's performance is verified in the face of system constraints and nonlinearities. Different scenarios are implemented, and the simulation outcomes emphasize the superior performance of the suggested strategy. Therefore, the suggested strategy provides consistent power system adoption wherever it is implemented.

RESUMEN

The application of virtual inertia (VI) has become a novel solution and new orientation for the frequency regulation of the high variable renewable energy (VRE) penetrated low inertia systems. How to provide a frequency regulation strategy for the system with VI is a key problem. Firstly, the power system is a multi inputs multi outputs (MIMO) system, in which the coupling characteristics of VI control and the primary and secondary frequency controls can't be ignored. Secondly, the system inertia constant is time-varying and the estimation of it is crucial for gaining a satisfying regulation performance. This paper intends to provide a frequency regulation strategy for this problem. In this work, an Elman neural network (ENN) based inertia estimation with a deadband method is proposed for the identification of the system's instant inertia. And the Laguerre function-based rate of change of frequency (ROCOF) constrained MIMO-MPC is constructed to provide the collaboration strategy. Then, the control parameters are tuned by the gravitational search algorithm (GSA) considering both the system performance indexes and the operation burden indexes. The proposed strategy is testified based on a three-area power system. The results prove not only the robustness of the controller but also the effectiveness of the ROCOF constraint, the operation burden index, and the instant inertia estimation method.

RESUMEN

Due to the increased complexity and nonlinear nature of microgrid systems such as photovoltaic, wind-turbine fuel cell, and energy storage systems (PV/WT/FC/ESSs), load-frequency control has been a challenge. This paper employs a self-tuning controller based on the fuzzy logic to overcome parameter uncertainties of classic controllers, such as operation conditions, the change in the operating point of the microgrid, and the uncertainty of microgrid modeling. Furthermore, a combined fuzzy logic and fractional-order controller is used for load-frequency control of the off-grid microgrid with the influence of renewable resources because the latter controller benefits robust performance and enjoys a flexible structure. To reach a better operation for the proposed controller, a novel meta-heuristic whale algorithm has been used to optimally determine the input and output scale coefficients of the fuzzy controller and fractional orders of the fractional-order controller. The suggested approach is applied to a microgrid with a diesel generator, wind turbine, photovoltaic systems, and energy storage devices. The comparison made between the results of the proposed controller and those of the classic PID controller proves the superiority of the optimized fractional-order self-tuning fuzzy controller in terms of operation characteristics, response speed, and the reduction in frequency deviations against load variations.

Asunto(s)

RESUMEN

By taking into account sampled-data mechanism and transmission delay, the novel event-triggering load frequency control (LFC) strategy involving random dynamic triggering algorithm (RDTA) is developed for multi-area power systems in this paper. Firstly, an improved multi-area LFC model considering sampling and transmission delay (STD) simultaneously is addressed. Secondly, a modified event-triggering mechanism (ETM) with RDTA is proposed, considering parameter disturbances and a dynamic adjustment mechanism of the triggering threshold. Thirdly, a more advanced Lyapunov-Krasovskii functional (LKF) is constructed, introducing the delay-dependent matrices, more variable cross terms and the two-sided closed functional. Furthermore, two less conservative stability criteria are obtained according to the designed approach. Finally, two multi-area LFC systems are presented to verify the progressiveness of the proposed approach.

RESUMEN

This work presents design and theoretical analysis of an adaptive fractional-order sliding-mode disturbance observer (FO-SM-DOB)-aided fractional-order robust controller for frequency regulation of a hybrid wind-diesel based power system, considering endogenous/exogenous system disturbances. Adaptive FO-SM-DOB is designed to estimate unknown/uncertain lumped system disturbances, including parametric uncertainty and exogenous disturbances. Afterwards, an improved fractional-order sliding mode controller (FOSMC) augmented with the estimated output of FO-SM-DOB is designed and applied to accelerate system dynamics with minimum chattering in the control effort. The Mittag-Leffler stability theorem affirms the finite-time convergence of disturbance estimation error. Moreover, the closed-loop asymptotic stability of the overall control system has been guaranteed by applying Lyapunov argument. The effectiveness of the suggested resilient fractional-order nonlinear frequency controller is theoretically validated by performing an extensive comparative study with SMC, FOSMC (without DOB), state observer-based SMC (SOB-SMC), second-order SMC (without DOB), and conventional integer/fractional-order controllers. Simulation results establish the supremacy of the proposed resilient fractional-order nonlinear frequency controller over its other counterparts concerning fast disturbance rejection, weaker chattering, and a high degree of robustness against unknown lumped system disturbances. Further, to demonstrate the practicability and validate the effectiveness of the proposed control strategy, magnetic levitation system and IEEE 39-bus New England power system are considered and successfully tested on MATLAB platform.

RESUMEN

This work explores a frequency-domain approach to design a fractional order proportional-integral-derivative (FO-PID) controller cascaded with a first-order filter for the load frequency control (LFC) system with communication delay. The proposed method is based on suitable reference model development in the direct synthesis (DS) approach, followed by frequency response matching technique. The reference model is developed for robust control-loop performance using the stability-margin and time-domain specifications. The values of the fractional orders of the integral and derivative terms are obtained according to the dynamics of the nominal system. The proposed controllers have been designed for some LFC systems taken from the literature that have different dynamics with reheat, non-reheat and hydraulic turbines and performances with non-linearity like generation rate constraint (GRC), generation dead band (GDB) along with noise have been compared favorably with that of some controllers prevalent in the literature. The proposed controllers have been shown to work efficaciously for the decentralized multi-area IEEE 39-bus New England test system along with variable communication delay. To show the efficacy of the proposed controllers the load-disturbance responses along with the frequency and time domain performance indices have been evaluated for comparison.

RESUMEN

Load frequency regulation is one of the most vital and complex ancillary services in a deregulated power system. Increasing penetration from renewable energy sources in an integrated power system (IPS) further escalates the related control complexity due to a considerable decrement in IPS's effective inertia. This may incur additional costs and can even lead to the destabilization of IPS. To overcome these problems in frequency regulation, this work proposes and investigates the use of an intelligent, direct adaptive control scheme, i.e., self-tuning fractional order fuzzy PID (STFOFPID) controller with and without the presence of a recently devised energy storage unit, i.e., the redox flow battery. The IPS' efficacy with the STFOFPID controller is validated for various contracts in a deregulated operation mode for considered three area IPS. Extensive simulation studies are carried out, and detailed comparative studies have been drawn with conventional PID and fractional order PID controllers for load frequency regulation in Poolco, bilateral, and contract-violation mode of operation. Robustness analysis in terms of parametric variations in different nonlinearities present in a reheated thermal power plant is also carried out, and the efficacy of the STFOFPID controller is established using a thorough quantitative comparative analysis. The real-time digital simulation validation of the investigated control structure has been carried out on OPAL-RT 4150 based on Xilinx Kintex-7 FPGA board with INTEL multi-core processor.

RESUMEN

This paper investigates the problem of networked load frequency control (LFC) of power systems (PSs) against deception attacks. To lighten the load of the communication network, a new adaptive event-triggered scheme (ETS) is developed on the premise of maintaining a certain control performance of LFC systems. Compared with the existing ETSs, the proposed adaptive ETS can adjust the number of triggering packets, along with the state changes in the presence of deception attacks, which can reduce the average data-releasing rate. In addition, sufficient conditions can be derived, providing a trade-off between the limited network communication resources and the desired control performance of PSs. Finally, an application case is presented for the PSs to demonstrate the advantages of the proposed approach.

RESUMEN

This paper proposes a novel robust controller for frequency stabilization of electrical systems taken into consideration a high renewable energy sources (RESs) penetration. The suggested controller, robust PID (RPID) controller, is combination of a proportional-integral-derivative (PID) controller and a linear quadratic gaussian (LQG) controller. Furthermore, the Improved lightning attachment procedure optimization (ILAPO) technique is applied for determining the optimal setting of the parameters of the introduced RPID controller. A studied power system with RESs is used as a test system to justify the performance of the RPID controller. The superiority of the introduced robust controller is verified through a comparison of its performance under system uncertainties with those of other robust controllers presented in the literature. The results elucidate that the RPID controller can effectually enhance frequency stability and guarantee reliable performance for power grids supplied with high share of renewable energy for all studied scenarios. Consequently, the proposed RPID controller purveys creditable for modern power systems considering RESs.

RESUMEN

In this article, we develop an original high order sliding mode control (SMC) method which can be used to control single input single output (SISO) system and multi-variable system. The method has the benefit of resisting unmodelled dynamics and external disturbance. However, there exist the chattering effect in the conventional control methods. For decreasing the chattering phenomenon, a new high order SMC method is raised. Firstly, the new methodology is designed. Secondly, the method is employed to control the single input single output system with two examples. Thirdly, this new scheme is applied to control the multi-variable system. At the same time, two examples are presented to testify the validity of the raised control method, then the raised new control method has been utilized to the load frequency control. Additionally, in comparison with other recently existed high order control method, the raised control method has demonstrated better control performance in terms of fast convergence and chattering phenomenon.

RESUMEN

With high penetration of renewable energy sources in nested multiple-microgrids, conventional solutions for the integration of load frequency control and economic dispatch may degrade frequency control performance and decrease operational economy. In this paper, a fast frequency recovery-oriented distributed optimal control strategy is proposed to deal with these problems. Firstly, a partial primal-dual gradient algorithm is dynamically integrated with an active disturbance rejection control algorithm (instead of conventional Proportional-Integral (PI) controller) to realize the fast frequency recovery and enhance anti-disturbance capability. As a result, frequent adjustments of resources can be avoided and this is crucial in extending the life cycles of batteries. Then, based on the above integration, the distributed optimal control law is derived, which is independent of load measurement and fully distributed, to coordinate the microgrids to share their power economically during the frequency regulation process. This can also relieve the communication and computation burden of the system. Finally, a set of numerical simulations is presented and the effectiveness of the proposed distributed optimal control is verified by the obtained results, which include a comparison with the conventional distributed PI-based optimal control strategy.

RESUMEN

The design and control of an intelligent integrated standalone micro-grid (I-ISMG) have been proposed in this study. The ISMG system consists of solar photovoltaic (SPV), wind turbine generator (WTG), diesel engine generator (DEG) as distributed power generation (PG), and battery and flywheel as energy storage systems (ESSs). An improved incremental conductance (I-InC) maximum power point (MPP) tracking (MPPT) scheme, and a fuzzy wind power generation model (FWPGM) are utilized to obtain the power from solar, and wind energy systems respectively. The key contribution of this work is to control the power flow for synchronous micro-grid (MG) operation, which in turn resolves the problem of load frequency control (LFC). In this control strategy, an intelligent, i.e. fuzzy logic-based adaptive control scheme is proposed for the coordinated power flow among the generation, demand, and storage system. To minimize the frequency deviation (Δf) and control of PG from WTG and DEG, frequency support (FS) fuzzy logic-based droop characteristic is employed. For the droop control in WTG and DEG, fuzzy logic-based proportional-integral-derivative (F-PID), and self-tuned-fuzzy PID (STF-PID) control schemes are utilized respectively. Apart from droop controls, a fuzzy observer (FO) is designed to manage power flow to/from the storage systems. Further, the proposed control scheme has been benchmarked using single area power system (SAPS) and modified New England IEEE 39 bus system.

RESUMEN

In the traditional sliding mode control method, there always exist the singularity due to the reduced order of the control method. In order to eliminate the singularity, I propose a new full order sliding mode control method in this article, which has been firstly applied to load frequency control. The full order sliding mode control method includes the terminal sliding mode control (TSM) and the linear sliding mode control (LSM). TSM has the good characteristic of eliminating the singularity due to the avoidance of derivative of terms with fractional power factors. While the LSM is easy to design and has fast time convergence comparing to TSM. The model is based on the system with different kinds of turbine or the same kind of turbine, which contains the nonlinearities. The control purpose is to adjust the frequency deviation to zero. Through the simulation results, it is shown that the frequency deviation can be kept to zero in the condition of different load disturbances by the two approaches, which approves the robustness of the proposed methods. In addition, we compare the two methods with the traditional sliding mode control (SMC), which proves the superiority of the two methods in terms of chattering and response time.