Multi-source Interconnected Power System Research Articles

LFC performance advancement of two-area RES penetrated multi-source power system utilizing CES and a new CFOTID controller

This study addresses the challenges of load fluctuations and the assimilation of renewable energy sources (RES) causing undesirable frequency deviations. To avoid widespread deviations in frequency, an intelligent, competent and robust load frequency control (LFC) scheme and energy storage system are obligatory for disturbance rejection in RES penetrated realistic interconnected multi-source power system (IMSPS). Hence, a new cascade fractional order tilt integral derivative (CFOTID) controller is suggested with capacitive energy storage (CES) for a pragmatic RES based thermal-hydro-gas IMSPS having governor dead-band and generation rate constraint nonlinearities. The salp swarm algorithm (SSA) is utilized successfully for fine-tuning of the controller parameters. Scrutiny of the outcome results reveals the sovereignty of the CFOTID controller over several existing well proven controllers and SSA-based FOTID. It is observed that power generation due to CES further advance the system results in terms of minimized overshoot, undershoot, and settling time. Lastly, a sensitivity analysis is conducted to confirm the robustness of the controller.

A Novel Hybrid IGSA-BPSO Optimized FOPID Controller for Load Frequency Control of Multi-source Restructured Power System

Background: An investigation of Automatic Generation Control (AGC) for a two-area, multi-source, interconnected power system under deregulation is presented in this article. For a more realistic approach, physical constraints namely Generation Rate Constraints (GRC) and Time Delay (TD) are incorporated into the system. Objective: This article proposed a novel hybrid Improved Gravitational Search Algorithm – Binary Particle Search Optimization (IGSA-BPSO) optimized Fractional Order Proportional-Integral- Derivative (FOPID) controller to regulate the frequency of a multi-area multi-source (thermalhydro- gas) interconnected power system in a deregulated environment. Methods: Integral Time Multiplied by Absolute Error (ITAE) is used as the objective function to be minimized by optimization techniques for getting optimum parameters of FOPID controllers installed in each area. Results: To inspect the efficacy of the suggested method, the dynamics of the system are investigated for poolco, bilateral and contract violation cases and the comparative results are also presented and analyzed. The supremacy of the recommended technique is studied by comparing with other well-known techniques namely GSA and PSO. Conclusion: The robustness of the proposed system is examined by sensitivity analysis after variations in different system parameters. In this paper, the AC-DC tie-line model is incorporated for the AGC mechanism. Dynamic load changes condition is also tested and verified. The study found that the proposed controller provides improved system dynamics in all competitive electricity market contract situations under varied system uncertainties.

PSO tuned interval type-2 fuzzy logic for load frequency control of two-area multi-source interconnected power system

Nowadays, most of modern power systems integrate concentrated renewable energy resources power plants like solar and wind parks in addition to central conventional plants. The output power from these concentrated renewable energy resources varies continuously according to weather conditions like solar irradiance value or wind speed and direction, the variation for their output power may be in mega watts. In this work, Robust secondary load frequency controller (LFC) based on one of artificial intelligent technique which called interval type-2 fuzzy logic controller (IT2FLC) has been proposed for two-area multi-source interconnected power system with central solar park power plants in each area while considering non-linearities in the power system. IT2FLC has accommodated vagueness, distortions and imprecision for the power system input signals which caused by weather fluctuations and system non-linearities. In addition to LFC, another controller based also on IT2FLC has been proposed to control the output power from the central solar parks in each area of generation during cloudy periods instead of maximum power point tracking method (MPPT) in order to enhance the stability for the power system during disturbance periods. In order to enhance the performance of the proposed LFC, particle swarm optimization technique (PSO) has been utilized to optimize the proposed LFC gains to minimize the steady state error, over/under shooting value, settling time and system oscillation for the investigated power system frequency. The performance and the superiority of the proposed PSO tuned IT2FLC is evaluated and compared with another LFC based on PSO tuned cascaded PID controller while applying severe demand load and solar irradiance changes. the simulation has been carried out using matlab/simulink program.

Coordinated AGC control strategy for an interconnected multi-source power system based on distributed model predictive control algorithm

The erratic and random characteristics of wind power and wind-thermal replacement significantly degrade the performance of AGC in an interconnected, multi-source power system. For the lack of cooperation between wind power and thermal plants in AGC of interconnected power system as well as the heavy computational burden and inflexible information interaction of centralized AGC architecture, a novel coordinated AGC control strategy for an interconnected multi-source power system based on distributed model predictive control (DMPC) algorithm is proposed in this research. Under the DMPC architecture, the dimension of centralized AGC problem is reduced in each subsystem, and the overall AGC performance can be enhanced through inter-area communication between subsystems. In the meantime, based on the proposed coordinated control strategy, the active AGC response capability of wind farms and energy storage in the interconnected system is exploited to realize the dynamic cooperation between the wind generation and thermal AGC plants, and the overall AGC control performance can be further improved. In this paper, local DMPC controllers are deployed in each subsystem to address the drawbacks of a centralized control architecture by exchanging forecast and state measurement information with neighboring subsystems. In addition, considering the current operating status of multiple kinds of energy sources with different features, a fuzzy-based coordinated control strategy is designed for the purpose of dynamically allocating the AGC demand inside the wind-storage system, and the wind farm’s reliability for AGC response in diverse operation scenarios can be guaranteed. Finally, comparative analysis with existing works has been conducted on a three-area power system, and numerical results demonstrate that the proposed coordinated AGC control strategy has better performance in AGC performance and the dynamic cooperation can be achieved between wind power and thermal plants in AGC response through the designed wind-storage system and coordinated DMPC AGC control strategy.

Dandelion Optimizer-Based Combined Automatic Voltage Regulation and Load Frequency Control in a Multi-Area, Multi-Source Interconnected Power System with Nonlinearities

Frequency, voltage and power flow between different control zones in an interconnected power system and are used to determine the standard quality of power. Therefore, the voltage and frequency control in an IPS is of vital importance to maintaining real and reactive power balance under varying load conditions. In this paper, a dandelion optimizer (DO)-based proportional-integral-proportional-derivative (PI-PD) controller is investigated for a realistic multi-area, multi-source, realistic IPS with nonlinearities. The output responses of the DO-based PI-PD were compared with the hybrid approach using artificial electric field-based fuzzy PID algorithm (HAEFA), Archimedes optimization algorithm (AOA)-based PI-PD, learning performance-based behavior optimization (LPBO)-based PI-PD and modified particle swarm optimization (MPSO)-based PI-PD control schemes in a two-area network with 10% step load perturbation (SLP). The proposed strategy was also investigated in a two- and three-area IPS in the presence of different nonlinearities and SLPs. The simulation results and the comprehensive comparison between the different control schemes clearly confirm that the proposed DO-based PI-PD is very effective for realistic, multi-area multi-source IPS with nonlinearities.

Optimal design of fuzzy-PID controller for automatic generation control of multi-source interconnected power system

This paper suggests a fuzzy logic controller (FLC) structure from seven membership functions (MFs) and its input–output relationship rules to design a secondary controller to reduce load frequency control (LFC) issues. The FLC is coupled to a proportional–integral–derivative (PID) controller as the proposed FPID controller, which is tuned by an optimized water cycle algorithm (WCA). The proposed WCA: FPID scheme was implemented with two models from the literature under the integral time absolute error cost function. Initially, a two-area non-reheat unit was implemented, and the gains of PID and FPID controllers were adjusted to verify the suitability of WCA in solving LFC issues. Then, in order to identify the robustness of the closed-loop system, sensitivity analysis is carried out. Additionally, a two-area non-reheat unit was tested under the governor dead band nonlinearity. To guarantee the suitability of the proposed FPID controller, a model with a mixture of power plants, such as reheat, hydro, and gas unit in each area was carried out with and without the HVDC link, which can increase practical issues with LFC. The proposed controller's robustness was studied for all models under numerous scenarios, step load perturbations (SLP), and different objective functions. Simulation results proved that the proposed FPID controller provided superior performance compared to recently reported techniques in terms of peaks and settling time.

Impact of energy storage and flexible alternating current transmission devices in combined voltage and frequency regulation of multiarea multisource interconnected power system

AbstractThis article emphasizes the impact of coordinated energy storage (ES) and flexible alternating current transmission (FACTS) devices in the combined voltage and frequency control of multi‐area systems having hydro, thermal, geothermal, and solar thermal power plants. Appropriate realistic constraints are equipped with both hydro and thermal units. A novel fuzzy logic controller‐based cascade PI and PID with filter coefficient (N), FCPI‐PIDN controller is proposed and optimized various controller parameters using artificial flora algorithm. Comparative analysis of FCPI‐PIDN, Cascade PI and PIDN (CPI‐PIDN), and PIDN controllers show the superiority of the FCPI‐PIDN controller to others. Integration of ES devices (ESDs), such as redox flow battery (RFB), capacitive energy storage (CES), and superconducting magnetic energy storage (SMES) indicates that the incorporation of ESDs enhance the system performance and RFB is superior to SMES and CES. Moreover, integration of FACTS devices, such as interline power flow controller (IPFC), thyristor control series capacitor (TCSC), and unified power flow controller (UPFC) indicates the incorporation of FACTS devices improve the system dynamic and coordination of IPFC‐RFB provide better response than TCSC‐RFB and UPFC‐RFB. Investigation reveals that the optimal location of RFB is Area 1 and IPFC is in between Areas 1 and 3. Sensitivity analysis validated the robustness of the FCPI‐PIDN controller.

Modified TID controller for load frequency control of a two-area interconnected diverse-unit power system

In this work, a modified structure of the tilted integral derivative (TID) controller, i.e. an integral derivative-tilted (ID-T) controller, is developed for the load frequency control issue of a multi-area interconnected multi-source power system. Moreover, a new optimization algorithm known as Archimedes optimization algorithm (AOA) is used to fine-tune the proposed ID-T controller parameters. The performance of the proposed ID-T controller based on AOA is evaluated through a two-area interconnected power system, each area containing various conventional generation units (i.e., thermal, gas, and hydraulic power plants) and renewables (wind and solar power). Furthermore, system nonlinearities (i.e., generation rate constraints, governor deadband, and communication time delays), system uncertainties, and load/renewables fluctuations are considered in designing the proposed controller. The effectiveness of the proposed ID-T controller based on AOA is verified by comparing its performance with other control techniques in the literature (i.e. integral controller, proportional integral derivative (PID) controller, fractional-order PID controller, TID controller, and I-TD controller). The AOA's optimization superiority has also been verified against a variety of other sophisticated optimization methods, including particle swarm optimization and whale optimization algorithm. The simulation results exhibit that the proposed ID-T controller based on the AOA presents a great improvement in the system frequency stability under several contingencies of different load perturbations, system uncertainties, physical constraints, communication time delays, high renewables penetration.

Design and analysis of the performance of multi-source interconnected electrical power system using resilience random variance reduction technique

Design and analysis of the performance of multi-source interconnected electrical power system using resilience random variance reduction technique

Application of a New Fusion of Flower Pollinated With Pathfinder Algorithm for AGC of Multi-Source Interconnected Power System

As the world's population grows and energy demand increases, it is necessary to increase the scale of the electrical system, which is more complicated. Consequently, adopting automatic generation control (AGC) scheme to meet the demand becomes inevitable. In this article, the fusion of flower pollinated algorithm (FPA) and pathfinder algorithm (PFA), named hereafter as hFPAPFA, is proposed to achieve maximum control efficiency by combining the exploitation of FPA with the exploration capacity of PFA. The proposed hFPAPFA is meant to regulate two unequal multi-area interconnected power system with different generating units such as thermal, hydro, wind power and diesel plants. The proposed control scheme aims to achieve this by using the new algorithm to optimize the fractional-order set-point weighted PID (FOSWPID) parameters under time domain-based fitness functions namely, integral time square error (ITSE) and integral time absolute error (ITAE) while simultaneously minimizing the power losses. Employing the same interconnected power systems, a comparative study with some recent approaches in renowned journals is conducted. The performance of the proposed method is observed under diverse load conditions scenarios. Moreover, three nonlinearities including boiler dynamics, the governor dead band (GDB) and generation rate constraints (GRC) are further integrated into the system from a pragmatic context. Finally, sensitivity tests involving various parameter changes and the introduction of random step load perturbations are carried out. From the results, the proposed approach outperformed other approaches under different load condition scenarios, incorporation of nonlinearities and random load perturbation, demonstrating the proposed technique's efficacy and reliability.

Frequency stabilization in deregulated energy system using coordinated operation of fuzzy controller and redox flow battery

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.

Modified PID controller for automatic generation control of multi-source interconnected power system using fitness dependent optimizer algorithm.

In this paper, a modified form of the Proportional Integral Derivative (PID) controller known as the Integral- Proportional Derivative (I-PD) controller is developed for Automatic Generation Control (AGC) of the two-area multi-source Interconnected Power System (IPS). Fitness Dependent Optimizer (FDO) algorithm is employed for the optimization of proposed controller with various performance criteria including Integral of Absolute Error (IAE), Integral of Time multiplied Absolute Error (ITAE), Integral of Time multiplied Square Error (ITSE), and Integral Square Error (ISE). The effectiveness of the proposed approach has been assessed on a two-area network with individual source including gas, hydro and reheat thermal unit and then collectively with all three sources. Further, to validate the efficacy of the proposed FDO based PID and I-PD controllers, comprehensive comparative performance is carried and compared with other controllers including Differential Evolution based PID (DE-PID) controller and Teaching Learning Based Optimization (TLBO) hybridized with Local Unimodal Sampling (LUS-PID) controller. The comparison of outcomes reveal that the proposed FDO based I-PD (FDO-I-PD) controller provides a significant improvement in respect of Overshoot (Osh), Settling time (Ts), and Undershoot (Ush). The robustness of an I-PD controller is also verified by varying parameter of the system and load variation.

Automatic generation control of multi source interconnected power system using adaptive neuro-fuzzy inference system

LFC (Load Frequency Control) difficulty is created by load of power system variations. Extreme acceptable frequency distinction is ±0.5 Hz which is extremely intolerable. Here, LFC is observed by PID controller (PID-C), Fuzzy and ANFIS controller (ANFIS-C). To control different errors like frequency and area control error (ACE) in spite of occurrences of load disturbance and uncertainties of system is checked by MATLAB/SIMULINK software. Proposed Controller offers less, and small peak undershoot, speedy response to make final steady state. LFC is mandatory for reliability of large interconnected power system. LFC is used to regulate power output of generator within specified area to maintain system frequency and power interchange. Here, two area multi source LFC system is analyzed. ANFIS is utilized for tie-line power deviation and controlling frequency. Proposed controller is compared with other controller and it is found that proposed controller is better than other controller. Proposed controller is better in terms of Robustness. The output responses of interconnected areas have been compared on basis of peak-undershoot, peak-overshoot and settling time (Ts). Result of FLC is compared to that of with classical controller such as proportional derivative plus integral (PID) controller which suggests that conventional controller is slow.
 Keywords: LFC, Fuzzy, PID, ANFIS, LFC; FLC; ACE; PID-C, AGC.

LFOPI controller: a fractional order PI controller based load frequency control in two area multi-source interconnected power system

PurposeIn computer application scenario, data mining task is rarely utilized in power system, as an enhanced part, this work presented data mining task in power systems, to overcome frequency deviation issues. Load frequency control (LFC) is a primary challenging problem in an interconnected multi-area power system.Design/methodology/approachThis paper adopts lion algorithm (LA) for the LFC of two area multi-source interconnected power systems. The LA calculates the optimal gains of the fractional order PI (FOPI) controller and hence the proposed LA-based FOPI controller (LFOPI) is developed.FindingsFor the performance analysis, the proposed algorithm compared with various algorithm is given as, 80.6% lesser than the FOPI algorithm, 2.5% lesser than the GWO algorithm, 2.5% lesser than the HSA algorithm, 4.7% lesser than the BBO algorithm, 1.6% lesser than PSO algorithm and 80.6% lesser than the GA algorithm.Originality/valueThe LFOPI controller is the proposed controlling method, which is nothing but the FOPI controller that gets the optimal gain using the LA. This method produces better performance in terms of converging behavior, optimization of controller gain, transient profile and steady-state response.

Load frequency controller for multisource interconnected nonlinear power system incorporating FACTs devices

The load frequency control for two area multisource interconnected power system model incorporating flexible AC transmission system (FACTs) devices is presented in this paper. The slow response of governor, the power swings and frequency oscillations tend to take longer time to settle to normal condition post disturbances. To overcome this condition, application of FACTs devices for frequency stabilisation under a small perturbation is studied and investigations are carried out on two area multisource interconnected power system model. The controller gains are tuned using genetic algorithm and the effect of FACTs devices for damping of power swings and frequency oscillations in an interconnected power system is studied and compared by the detailed analysis of power system dynamics. The power system model consists of thermal, hydro and doubly fed induction generator (DFIG)-based wind plant in each area. Governor deadband (GDB) and generation rate constraint (GRC) is also considered to study the effect of nonlinearity on the power system dynamics. It has been observed that FACTs enabled power system is very effective in damping out the power swings and local frequency oscillations caused due to disturbance in load. An improvement in the transient response and tie-line power oscillations is also quite appreciable.

Load frequency controller for multisource interconnected nonlinear power system incorporating FACTs devices

Load frequency controller for multisource interconnected nonlinear power system incorporating FACTs devices

Improved-Fitness Dependent Optimizer Based FOI-PD Controller for Automatic Generation Control of Multi-Source Interconnected Power System in Deregulated Environment

This paper presents a Fractional Order Integral-Proportional Derivative (FOI-PD) controller for Automatic Generation Control (AGC) of two-area Interconnected Power System (IPS) with six multiple generations units in a restructured environment. Further, the two-area IPS is composed of multiple non-linearities with Time Delay (TD), Boiler Dynamic (BD), Governor Dead Zone/Band (GDZ/GDB) and Generation Rate Constraint (GRC). The gains of the proposed controller are optimized by a most recent powerful meta-heuristic algorithm known as Improved-Fitness Dependent Optimizer (I-FDO). The efficiency of the proposed approach is compared with other techniques such as Firefly Algorithm (FA), Fitness Dependent Optimizer (FDO) and Teaching Learning Based Optimization (TLBO) algorithms. Further, to enhance the performance of the system, Redox Flow Batteries (RFB) is incorporated in each area and Thyristor Controlled Series Compensator (TCSC) in the tie-line of the power system. Results reveal that our proposed approach performs superior in terms of less Overshoot (Os), Settling time (Ts) and Undershoot (Us). Robustness of the proposed controller is verified by changing system parameters within a range of ± (25) %.

Fitness Dependent Optimizer-Based Automatic Generation Control of Multi-Source Interconnected Power System With Non-Linearities

This paper proposed an improved structure of Proportional Integral Derivative (PID) controller called as Integral Proportional Derivative (I-PD), applied for Automatic Generation Control (AGC) of Multi-Source Interconnected Power System (IPS). The parameters of the proposed controller are optimized with a newly developed, powerful, nature-inspired meta-heuristic technique known as Fitness Dependent Optimizer (FDO). To show the efficacy of the proposed controller and the technique used, they have been tested on three different system models. Initially, a two-equal area of diverse source generation including reheat-thermal, gas, and hydro power system is considered. In the second scenario, the same power system model is used with addition of two non-linearities; Generation Rate Constraint (GRC) and Governor Dead Band (GDB). Lastly, multiple non-linearities including Governor Dead Band (GDB), Time Delay (TD), Generation Rate Constraint (GRC), and Boiler Dynamics (BD) have been considered to make the initial system more realistic and practical. The outcome from the proposed techniques is also compared with some recently meta-heuristic algorithms such as Teaching Learning Based Optimization (TLBO), Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). From the results, it has been perceived that the proposed technique shows superior performance in respect of Overshoot (Osh), Undershoot (Ush) and Settling Time (Ts) of the system frequency.

A Novel Hybrid Salp Swarm Differential Evolution Algorithm Based 2DOF Tilted-Integral-Derivative Controller for Restructured AGC

This article elevates the study of Automatic Generation Control (AGC) for a multisource interconnected power system under the restructured environment. Physical constraints such as Generation Rate Constraints (GRC), Governor Dead Band (GDB) and Boiler Dynamics (BD) are incorporated into the system for a more realistic approach. Distribution Generation (DG) system is also considered to incorporate the effects of renewable energy sources penetration. A novel cascaded topology of 2-Degree of Freedom Tilted-Integral-Derivative Controller with filter (2DOF-TIDN) is proposed for anticipated AGC mechanism. A maiden application of Hybrid Salp Swarm Differential Evolution Algorithm (HSSDEA) has been successfully applied to get the different optimum gains of the proposed controller. Capacitive Energy Storage (CES) system is also incorporated for the proposed system for the AGC mechanism. The supremacy of the proposed controller is examined by comparing with other well-known or benchmark controllers. The robustness of the proposed system has been analyzed for the contract violation case of deregulation. Finally, the efficacy of the proposed work has been verified by comparing with the previously published work of literature on same platform.

Maiden application of cascade tilt‐integral–tilt‐derivative controller for performance analysis of load frequency control of interconnected multi‐source power system

This study presents a maiden application of cascade tilt-integral–tilt-derivative (CC-TI-TD) controller for the performance analysis of load frequency control (LFC) of interconnected multi-source power system (MSPS). The studied controller is realised based on cascade control theory and fractional order calculus. TI controller is used as a master controller and TD controller served as slave controller in the proposed CC-TI-TD controller. To demonstrate the performance of proposed CC-TI-TD controller, first, it is applied to single-area MSPS followed by two-area MSPS in the presence of electric vehicles (EVs). The proposed controller gains' parameters are optimised by state-of-the-art water cycle algorithm (WCA) according to the minimisation of fitness function. First, the effectiveness of proposed WCA-tuned CC-TI-TD controller over the WCA-tuned cascade proportional-integral–proportional-derivative (CC-PI-PD) controller and modified grey wolf optimisation-based tuned proportional-integral derivative and CC-PI-PD controllers has been explored in single-area-studied power system. Second, the performance of WCA-tuned CC-TI-TD controller with and without presence of EVs in a two-area interconnected MSPS is assessed with respect to another class of the fractional order controller termed as integral tilt-derivative controller. Lastly, sensitivity analysis and the effect of time delay on LFC performance are carried out to show the robustness of proposed CC-TI-TD controller.