Multi-area Automatic Generation Control Research Articles

Performance Analysis of Automatic Generation Control for a Multi-Area Interconnected System Using Genetic Algorithm and Particle Swarm Optimization Technique

The primary focus of this paper is to assess an interconnected power system using different optimization techniques. The main purpose is to employ different optimization techniques, including genetic algorithms (GA) and particle swarm optimization (PSO), to systematically enhance the performance of a multi-area or two-area automatic generation control (AGC) system, aiming to optimize the three PID controllers gain values and improve system performance under diverse loading conditions. Two case studies are conducted exploring different loading conditions in the megawatt (MW) range, including increasing load demand and decreasing load demand. The analysis involves four scenarios, covering without any kind of controller, another with solely a proportional integral derivative (PID) controller, a PID controller enhanced through a genetic algorithm (GA), and lastly, a PID controller improved through particle swarm optimization (PSO). The optimization process utilizes the integral time absolute error (ITAE) as the objective function to evaluate the system's performance. The simulation outcomes for ITAE, settling time, overshoot, and undershoot for frequency deviation of area one, area two, and power deviation in the tie-line are compared with previous similar studies to assess the novelty of this work. The article highlights the importance of the multi-area AGC system and the significance of different optimization techniques in improving its performance.

Inertia Emulation Control Strategy of an Accurate Model of HVDC Link in a Multi-area Automatic Generation Control System Integrated Precise Wind Turbine System

Inertia Emulation Control Strategy of an Accurate Model of HVDC Link in a Multi-area Automatic Generation Control System Integrated Precise Wind Turbine System

Multi-area automatic generation control of a renewable energy-based hybrid power systems using JAYA optimized model predictive control

This study uses JAYA optimized model predictive control to address a three-area load frequency regulation problem that actively involves stochastic renewable energy sources. Some physical constraints employed in the system model, such as the generation rate constraint, dead band, and time delay by governor-turbine, negatively impact the control performance of the classical MPC technique. As such, a more robust control scheme is required to get rid of this flaw. The JAYA algorithm is adopted to dynamically tune the parameters of MPC, which is a parameter-driven controller for optimal system performance. The performance indices such as the integral of square error (ISE), integral of time multiplied by square error (ITSE), integral of the absolute value of error (IAE), and integral of time multiplied by the absolute value of error (ITAE) have been used to compare the effectiveness of the proposed controller with the classical MPC with constant tuning parameters. The suggested controller is superior to the conventional MPC, as demonstrated by the results from the MATLAB/Simulink environment.

Dominant mode identification and influence mechanism investigation of frequency oscillations as affected by automatic generation control

Several frequency oscillation events have recently been observed in practical power grids, which are strongly related with dynamic process of AGC (automatic generation control). This kind of oscillations are caused by the phase relation mismatching between mechanical powers and rotational speeds and the detailed dynamic performance and oscillation mechanism are not clear and deserve in-depth investigations. Motivated by this, this paper establishes the state-space model of multi-area AGC systems containing different kinds of generator units and time-scale dynamics. Without distinguishing AGC and PFR (primary frequency regulation) modes, Homotopy method is applied to identify the dominant mode and thus analyze the key influencing factors of frequency oscillations affected by AGC dynamics. The method can clearly establish the congruent relationship between eigenvalues and state variables and is more rapid and intuitive to identify the dominant mode for AGC oscillations. The correctness and feasibility of the proposed method are validated by time-domain simulations and results analysis. Finally, simulations are performed in single-area as well as four-area system based on real data to demonstrate the proposed model and method. And relevant parameter influence mechanism and oscillation performances are investigated for AGC system oscillations.

Mitigation of false data injection attacks on automatic generation control considering nonlinearities

As the main frequency controller in the electrical grid, the Automatic Generation Control (AGC) is one of the critical components that requires high level of security. A cyber attack on the AGC system does not only affect the operation of the AGC, but it also affects the whole system frequency. Previous research works have ignored the nonlinearities of the AGC when conducting cyber-physical threats assessment. In this paper, we first demonstrate that AGC nonlinearities cannot be ignored while studying the AGC cyber-physical security. In particular, we investigate the False Data Injection (FDI) and Time Delay (TD) attacks against a multi-area AGC systems. Second, to protect against these threats, we propose a Deep Learning (DL) approach based on Long-Short Term Memory (LSTM) framework. The two-stage LSTM framework first detects data anomalies from FDI and TD attacks and then mitigates the compromised signals in order to minimize the attacks effect on the system. We evaluate and quantify the performance of our model using a two-areas AGC system. The results confirm the accuracy of the detection model and its ability to detect and determine the compromise signals. Additionally, the mitigation model significantly reduces the attacks effect on the AGC system.

Impact of PLL and Virtual Inertia on Deregulated AGC System Integrated with Parallel AC/HVDC

This article investigates the impact of phase-locked loop (PLL) systems along with virtual inertia on system dynamics of a parallel AC/HVDC tie-line integrated two-area automatic generation control (AGC) system under a deregulated scenario. The multi-area AGC system comprises two thermal and hydro-gas in area-1, 2. An attempt is made to utilize a new secondary controller named the two-degree-of-freedom tilt-integral-derivative (2DOF-TID) controller. Its gains and PLL parameters are optimized by a novel meta-heuristic algorithm called a bird swarm algorithm (BSA). The system dynamics corresponding to the proposed 2DOF-TID are compared with 2DOF-PID, 2DOF-PI explored better system dynamics with a 2DOF-TID controller. The system dynamics are compared with AC alone, AC/HVDC, AC/HVDC tie-line incorporating with PLL, virtual inertia revealed the better performance of the latter. Moreover, the effect of variation in PLL parameter on the system dynamics are also analyzed and studies suggested that the obtained response at the nominal value of natural frequency (ωn ) and damping coefficient (ζ) reduces the subsequent oscillation and provides better dynamics other than varying condition.

Multi-area multi-source automatic generation control in deregulated power system

The restructuring of the interconnected power systems under the Independent System Operator (ISO) managing to get an unforced and independent electricity market is the ultimate goal for the federal energy regulatory commission (FERC). Therefore, it is converted a common topic of general studies for the period of last years. Therefore, FERC presents various ancillary services such as frequency control based on load following under automatic generation control (AGC) in the deregulated environment. This paper presents a multi-area multi-source AGC in a deregulated power system that operates under deregulation platform on the bilateral policy having the thermal power plants with reheat turbine, gas, diesel and hydro power units in the form of a four-area interconnected power system with various of the possible contracts. Since damping of frequency oscillation under unexpected faults is very important to grantee system stability, therefore, the optimal tuning of proportional-integral-derivative controller with low pass filter is converted a single objective function optimization problem considering system parameter’s uncertainties and eigenvalues. The important benefit of this approach is its high insensitivity to large load changes and disturbances in the existence of unit parameter discrepancy and model’s nonlinearities. To cope with the disadvantage of the conventional controllers in the AGC power system, the proposed optimization problem is solved by a new modified virus colony search (MVCS). Simulations are carried out for a large-scale AGC power system under the deregulated regime with the various possible contracts and load distributions.

Power transfer limit calculation for multi-area interconnected power networks

Multi-area interconnected schemes are beneficial for power networks to coordinate energy resources and have created the need to identify the critical conditions for transferring power among multiple subareas. This study proposes an improved continuation power flow (CPF) model to calculate the power transfer limits (PTL) among interconnected networks corresponding to either saddle node bifurcation (SNB) or limit-induced bifurcation (LIB). Formulations of the cooperation in multi-area automatic generation control (AGC) systems are proposed to express the power balance in each subarea and the adjustments of power exchange. The predictor-corrector scheme for the improved CPF is derived and restated. Moreover, a practical step size control method is proposed in accordance with polynomial fitting analysis with the relevant computational variables to enhance the performance and efficiency of CPF steps. Case studies based on an IEEE 5-bus, IEEE 118-bus and Polish 2383-bus test system demonstrate the efficiency of the proposed CPF model and its ability to generate reliable PTL results.

Multi-Area Automatic Generation Control Scheme Considering Frequency Quality in Southwest China Grid: Challenges and Solutions

Southwest China Grid (SCG) is one of the hydropower-rich power grids around the world. SCG has recently been into asynchronous operation mode, it is expected to face challenges in low inertia and frequency stability issues caused by the hydraulic turbine governing system (HTGS), which brings profound changes to the validity and stability for the multi-area automatic generation control (AGC) power systems. This article analyzes the frequency control problems of SCG according to the operation data from asynchronous operation tests. To overcome the large overshoot and reverse regulation for external disturbances, frequency-based segment values of frequency bias for areas under TBC mode are developed considering multi-deadband effects, and a switching method of control modes for supporting large-disturbance recovery is proposed. Based on the complex and nonlinear of AGC systems, a fuzzy PD+I controller is proposed to reduce the excessively large overshoot. Furthermore, the rule for tuning D gain is established by the sign of change of area control error (ACE), and flexible I-part is applied to the control process based on the relationship between ACE and frequency. Then, we also provide filter-based control strategies with adaptive parameters to effectively coordinate hydropower and thermal power generators. The filter coefficients are computed considering various delays within AGC systems. Some case studies and actual operating conditions demonstrate the efficiency and accuracy of the proposed ideas compared with current control strategies.

Stability Analysis in RECS Integrated Multi-area AGC System with Modified- SOS Optimized Fuzzy Controller

Background: Automatic Generation Control (AGC) of multi-area nonlinear power system integrated with wind energy based Renewable Energy Conversion System (RECS). Methods: A fuzzy PID controller has been proposed for AGC of a three equal area thermal system integrated with RECS. Different physical nonlinear constraints like Governor Dead Band (GDB) and boiler dynamics are introduced in the model for realization of non linear and realistic of proposed multi area power system. To determine the optimum gain parameter, a Modified Symbiotic Organism Search (M-SOS) algorithm has been used along with a fitness function which based on Integral of Time Multiplied Absolute Error (ITAE). Results: For performance analysis, the performance of proposed M-SOS optimized fuzzy-PID controller is compared with PI, PID and fuzzy PI controllers. For technique comparison, performance of proposed M-SOS technique is compared with original SOS and conventional PSO algorithms. Robustness of proposed controller has also been verified by varying applied load and system parameters. Conclusion: It is observed that M-SOS technique exhibits improved performance over original SOS and PSO algorithms. It is also observed that proposed Fuzzy-PID controller provides better system performance than PI, PID and fuzzy PI controllers. It has been observed that the proposed M-SOS tuned fuzzy PID controller improves settling time of frequency response in area 1 by 11.30%, 15% and 17.75% compared to M-SOS tuned fuzzy PI, PID and PI controllers respectively. Significant improvements in settling time, peak overshoot and peak undershoot of the frequency response in area 2 and tie line power are observed with the implementation this proposed approach.

Bi-Level Model Predictive Control for Optimal Coordination of Multi-Area Automatic Generation Control Units under Wind Power Integration

With the high degree of wind power penetration integrated into multi-area AC/DC interconnected power grids, the frequency regulation capacity of automatic generation control (AGC) units is not sufficient in the wind power-penetrated area, making it difficult to effectively suppress the frequency stability caused by the fluctuation of wind power. Therefore, a coordinated control strategy for AGC units across areas based on bi-level model predictive control is proposed in this paper to achieve resource sharing. The control scheme uses economic model predictive control to realize steady power optimal allocation of the AGC units across areas in the upper layer and distributed model predictive control to realize dynamic frequency optimization control of the multi-area AGC units in the lower layer. Taking a three-area AC/DC interconnected power grid with a wind farm as an example, the simulation results show that, compared with model predictive control using tie-line frequency bias control (TBC) mode, the proposed control strategy can not only effectively maintain tie-line safety and frequency stability, but can also reduce the regulation cost of multi-area AGC units.

Optimal automatic generation controllers in a multi‐area interconnected power system with utility‐scale PV plants

The centralised utility-scale photovoltaic (PV) plants installation has greatly enlarged their percentage in the bulk power systems, along with the nature uncertainty for the balance of system power and loads. Consequently, the successful integration of solar PV power in large-scale power systems requires a reliable and efficient multi-area automatic generation control (AGC) system within the control centre. Specifically, area-AGCs that perform tie-line bias control, in which the area frequency regulates the tie-line power flow, must balance the operational control area supply power-and-demand loads within a pre-tuned parameter set. Traditional AGC control systems have area linear controllers that must be periodically tuned to manage the high fluctuation of PV power. A practical two-step tuning method to determine the optimal parameters of existing multi-area AGCs is presented. The proposed method is demonstrated on a five-area multi-machine power system with two large PV plants. The power system was equipped with the synchrophasor-based monitoring system, with a real-time simulation platform serving as the application host. Results indicated that the two-step tuning method provides optimal parameters for all the system AGCs over a wide range of PV penetration levels. Typical results demonstrated the effectiveness of the tuned multi-area AGCs under dynamic conditions and disturbances.

Mitigation of cyber-physical attacks in multi-area automatic generation control

In recent years, several cyber-attacks have been recorded against sensitive monitoring systems. Among them is the automatic generation control (AGC) system, a fundamental control system used in all power networks. AGC systems keep the network frequency at its desired value and maintain the tie-line power exchanges at their scheduled values. Motivated by the increasing need for robust and safe operation of AGCs, we introduce an attack resilient control scheme for the AGC system based on attack detection using state estimation. The proposed approach requires redundancy of sensors available at the transmission level in the power network and leverages recent results on attack detection using mixed integer linear programming (MILP). The proposed algorithm detects and identifies the sensors under attack in the presence of noise. The non-attacked sensors are then averaged and made available to the feedback controller. No assumptions about the nature of the attack signal are made. The proposed method is simulated using a large range of attack signals and uncertain sensors measurements.

Maiden application of two degree of freedom cascade controller for multi-area automatic generation control

Maiden application of two degree of freedom cascade controller for multi-area automatic generation control

Multi Area AGC Problem of T.G.U Solved Through GA (Using Tuning of PID) Controller

Major issue of modern power system having complex power structure, it is necessary for Thermal Generating Unit (TGU) to continuous supplying an electric power with the increasing demand. Owing to this Automatic Generation Control (AGC) play a key role for maintaining the frequency oscillation and tie-line power due to unpredictable load changes. This paper help to solve the settling time issue of load frequency and tie-line power for multi area (Five area) AGC interconnected TGU Reheat and Non-Reheat system using different controllers like GA (Using Tuning of PID) controller, Fuzzy controller and PID controller. For better results the combined response of frequency and tieline deviation has been obtained separately for multi areas reheat and non-reheat T.G.U system and the comparative Tables of the entire controller’s response is taking place separately. The results obtain from the combined response and comparative table, shows that GA controller gives the better dynamic performance due to settle down frequency and tie-line power deviation in less time and satisfy the automatic generation control requirements.

Power Flow Analysis Considering Automatic Generation Control for Multi-Area Interconnection Power Networks

In addition to maintaining the power balance, the major tasks of multi-area automatic generation control (AGC) involve regulating the power exchange among subareas. This study presents a new power flow model allowing for multi-area AGC that achieves cooperation among the participating generators, which are deployed separately in the interconnected subarea networks. The formulations of the power exchange among the subareas are derived from the active power flow equations of the tie-lines. The node parameters representing the level and allocation of the unbalanced power are introduced. Then, the proposed power flow model is established by integrating the formulations of the node power injection and power exchange. Meanwhile, the unknown variables in the integrated model can be synchronously adjusted by the Newton iteration method, which depends on the integrated Jacobian matrix. Furthermore, being improved based on the integrated formulations, some related algorithms, including but not limited to sensitivity analysis, are expected to produce more precise solutions. The case studies of the IEEE 5 bus test system, the IEEE RTS-1996 test system, and the IEEE 300 bus test system illustrate the convergence and efficiency of the proposed power flow method. Moreover, the case studies also demonstrate that the integrated formulations based sensitivity analysis can generate more reliable results.

Multiarea Deregulated Automatic Generation Control Scheme of Power System Using Imperialist Competitive Algorithm Based Robust Controller

ABSTRACTThis paper is focused on design and application of proportional integral derivative (PID) controller for deregulated multiarea automatic generation control (AGC) scheme utilizing the imperialist competitive algorithm (ICA) under various electricity market transactions. A multiarea hydro thermal 75-bus real power system is considered as a test system for deregulated AGC scheme. Simulation study results demonstrate the effective performance of controller on various load disturbance scenarios. The performance of ICA-tuned PID controller is also compared with genetic algorithm (GA)-tuned PID controller. The comparative results show that ICA–PID controller has higher convergence rate, smaller settling time, reduced oscillations than GA-tuned PID controller, i.e. reaching to better solution. Robustness of ICA–PID controller is also checked to determine its response towards system parameters uncertainties through sensitivity analysis. It is seen that the performance of PID controller tuned by ICA algorithm is robust for the system parameter uncertainties while GA–PID controller performance degrades.

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs’ commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takes into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible, and, thus, reduce the size and extend the lifetime of the BESS. The effectiveness of the control strategy is validated with an innovative multi-area interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators’ dynamic response.

ARMC-AGC strategy for multi-area optimal cooperation to cover the variability of renewable energy resources

The integration of large-scale variable renewable energy (VRE) has increased the demand for additional regulation capacity to manage the variability of renewable generation. This problem can be solved by exploiting regulation flexibility from neighboring areas; however, this solution is restricted by the existing automatic generation control (AGC) strategy. In this paper, an AGC strategy based on the area regulation marginal cost is presented for multi-area AGC optimal cooperation. A multi-area system dynamic model for AGC is improved, and the formulation of the multi-area AGC optimal cooperation model considering tie-line power security, which is the objective of the proposed control strategy, is developed. Next, the stability and optimality of the proposed strategy are studied based on the linear theory. Finally, comparative simulations based on a simple three-area system show that the proposed strategy is effective in enabling further VRE penetration and can improve the economic efficiency of regulation in multi-area power systems. A case study using a real multi-area power system demonstrates the benefits of the proposed strategy in practice.

Application of fractional order PID controller for AGC under deregulated environment

In this paper, a fractional order proportional integral derivative (FOPID) controller for multiarea automatic generation control (AGC) scheme has been designed. FOPID controller has five parameters and provides two additional degrees of flexibility in comparison to a proportional integral derivative (PID) controller. The optimal values of parameters of FOPID controller have been determined using Big Bang Big Crunch (BBBC) search algorithm. The designed controller regulates real power output of generators to achieve the best dynamic response of frequency and tie-line power on a load perturbation. The complete scheme for designing of the controllers has been developed and demonstrated on multiarea deregulated power system. The performance of the designed FOPID controllers has been compared with the optimally tuned PID controllers. It is observed from the results that the FOPID controller shows a considerable improvement in the performance as compared to the conventional PID controller.