Interconnected Power System Research Articles

Co-Design of Dynamic Event-Observer-Based Security Control for Interconnected Nonlinear Power Systems Under Actuator Deception Attacks

Co-Design of Dynamic Event-Observer-Based Security Control for Interconnected Nonlinear Power Systems Under Actuator Deception Attacks

A General Resiliency Enhancement Framework for Load Frequency Control of Interconnected Power Systems Considering Internet of Things Faults

A General Resiliency Enhancement Framework for Load Frequency Control of Interconnected Power Systems Considering Internet of Things Faults

Distributed Economic Model Predictive Load Frequency Control for the Multiarea Interconnected Power System With WTs

Distributed Economic Model Predictive Load Frequency Control for the Multiarea Interconnected Power System With WTs

OPTIMAL LOAD FREQUENCY CONTROL OF INTERLINKED NONLINEAR POWER SYSTEM INTEGRATED WITH SMES-TCSC AND HVDC

In this article Multi-Area Multi-Source Interconnected Power System (MAMS-IPS) incorporated with an Automatic Voltage Regulator (AVR) in both the areas is considered for Load Frequency Control (LFC) study. Nonlinearity such as Governor Rate Constraints (GRC), Governor Dead Band (GDB), and Boiler are introduced with the thermal reheat generating unit. The effect of energy storage device (SMES) and fact device (TCSC) on the dynamic responses of IPS is also tested. PD-PID controller is suggested along with PID/PI-PD controller for minimizing the Automatic Control Error (ACE). The parameters of the proposed controller are optimized through a nature-inspired algorithm (PSO). PD-PID is superior then other suggested PID/PI-PD controllers. Objective functions ITAE, IAE, ISE, and ITSE are taken into consideration for finding the optimized values of the suggested controller as well as of TCSC and SMES devices. A step load of 10% is applied in both IPS areas. The rigidness of the suggested controller is verified by varying the loading condition of the IPS. A 10% increment in step load form is introduced for each area. The effect of renewable energy sources such as solar and a wind unit is also taken into consideration in this article. Varying step input is applied to this renewable unit to absorb its effect on the output responses of MAMS-IPS. The superiority of the PD-PID controller is verified by comparing its result with the recently published optimal controllers results described in the literature. SMES helps in improving the dynamic responses of the MAMS-IPS. Based on performance indices and Settling-time (ST) results of proposed controllers are compared with each other. For commenting on the stability of the introduced Power system (PS) eigenvalue analysis is also conducted. MATLAB version 2018 @ simulation software is used for simulation and for creating .m files

Retraction Note: Analysis of antlion optimizer-based ABT for automatic generation control of an interconnected power system

Retraction Note: Analysis of antlion optimizer-based ABT for automatic generation control of an interconnected power system

2DOF-PID-TD: A new hybrid control approach of load frequency control in an interconnected thermal-hydro power system

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.

Tube-based MPC strategy for load frequency control of multi-area interconnected power system with HESS

With the rapid development of power generation technology and the increasing demand from power users, multi-area interconnected power systems have become a development trend. This article proposes a new robust tube-based model predictive control strategy (MPC) for multi-area interconnected power systems with hybrid energy storage systems (HESS), based on the application of HESS to optimize the performance of load frequency control in power systems. The proposed strategy is mainly based on a new robustness constraint, which effectively handles uncertain disturbances within interconnected power system by compressing the disturbance invariant set. This strategy effectively alleviates the problems caused by inconsistency in multi-area interconnection modes. In addition, a sufficient stability criterion is derived to ensure the robust stability of the system, even under uncertain disturbances. By modeling a four-area interconnected power system with HESS, the frequency fluctuations of different methods are compared and discussed in each area. Based on the constructed software-in-the-loop setup, the effectiveness and feasibility of the proposed strategy are verified by experiments.

A Low-Frequency Oscillation Suppression Method for Regional Interconnected Power Systems with High-Permeability Wind Power.

With the integration of large-scale wind power into the power grid, the impact on system stability, especially the issue of low-frequency oscillations caused by small disturbances, is becoming increasingly prominent. Therefore, this paper proposes a damping quantitative analysis method for regional interconnected power systems incorporating large-scale wind power. Using the cross-entropy particle swarm optimization (CE-PSO) algorithm, the control parameters of wind turbines are optimized to suppress low-frequency oscillations in interconnected systems. The method begins with the state equation of the interconnected power system in two regions; it deduces the characteristic polynomial of the interconnected system, including wind farms, and takes into account the influence of wind power integration on the electrical connectivity of the system. Subsequently, the influence of wind turbine control parameters on the system is quantified, and a quantitative analysis model of the impact of wind power integration on system damping characteristics is constructed. Based on this, an optimization model for wind turbine control parameters is established, and the CE-PSO algorithm is utilized to achieve suppression of low-frequency oscillations in interconnected power grids with wind power integration. Finally, the accuracy and effectiveness of the proposed method are verified through a typical electromagnetic transient simulation model of the two-region interconnected power system.

АНАЛІЗ НАЛАШТУВАННЯ ПРИСТРОЇВ АВТОМАТИЧНОГО ЧАСТОТНОГО РОЗВАНТАЖЕННЯ З УРАХУВАННЯМ ЄВРОПЕЙСЬКИХ ВИМОГ

The paper deals with the structure of under-frequency load shedding (UFLS) relays in the interconnected power system (IPS) of Ukraine. The equivalent power system model to study the UFLS operation is developed, and UFLS configuration scenarios considering the requirements of ENTSO-E, are configured. The frequency stability for different scenarios of UFLS settings considering planned and emergency active power imbalances are studied. The plots illustrating the frequency change in the power system under these conditions are presented. References 4, table 1, figures 5.

Frequency regulation controller for multi‐area interconnected power system

AbstractBy increasing the number of electric vehicles (EVs) to achieve a less carbon environment, not only they consume power from the grid to be charged, but also do they deliver power to the grid, and this can play a significant role in load frequency control. However, EVs take part in frequency regulation based on their state of charge (SoC) which will cause uncertainties. In order to manage these uncertainties, EV aggregator (EVA) concept has been introduced. The EV owner participates in the demand response program provided by the EVA arbitrarily considering her/his requirements. Accordingly, EVA calculates the up and down power reserve for the power system operator. Following any frequency deviation, EVA sends the proper commands to each EV to consume or to inject power to the system. There are also communication delays between different parts, uncertainties, and non‐linearities that existed in the power system. To overcome these issues, this study proposes a new robust load frequency controller based on feedback theory and artificial neural network which is designed through the non‐linear multi‐machine power system. Simulation results on IEEE 39‐bus power system show that the proposed controller regulates frequency more desirably in comparison with other methods.

Enhancing Load Frequency Control of Interconnected Power System Using Hybrid PSO-AHA Optimizer

The integration of nonconventional energy sources such as solar, wind, and fuel cells into electrical power networks introduces significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can adversely affect the quality and reliability of power supplied to consumers. This paper addresses this issue by proposing a Proportional–Integral–Derivative (PID) controller optimized through a hybrid Particle Swarm Optimization–Artificial Hummingbird Algorithm (PSO-AHA) approach. The PID controller is tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control performance. The PSO-AHA-PID controller’s effectiveness is evaluated in two networks: a two-area thermal tie-line interconnected power system (IPS) and a one-area multi-source power network incorporating thermal, solar, wind, and fuel cell sources. Comparative analyses under various operational conditions, including parameter variations and load changes, demonstrate the superior performance of the PSO-AHA-PID controller over the conventional PSO-PID controller. Statistical results indicate that in the one-area multi-source network, the PSO-AHA-PID controller achieves a 76.6% reduction in overshoot, an 88.9% reduction in undershoot, and a 97.5% reduction in settling time compared to the PSO-PID controller. In the dual-area system, the PSO-AHA-PID controller reduces the overshoot by 75.2%, reduces the undershoot by 85.7%, and improves the fall time by 71.6%. These improvements provide a robust and reliable solution for enhancing the stability of interconnected power systems in the presence of diverse and variable energy sources.

Droop Frequency Limit Control and Its Parameter Optimization in VSC-HVDC Interconnected Power Grids

With the gradual emergence of trends such as the asynchronous interconnection of power grids and the increasing penetration of renewable energy, the issues of ultra-low-frequency oscillations and low-frequency stability in power grids have become more prominent, posing serious challenges to the safety and stability of systems. The voltage-source converter-based HVDC (VSC-HVDC) interconnection is an effective solution to the frequency stability problems faced by regional power grids. VSC-HVDC can participate in system frequency stability control through a frequency limit controller (FLC). This paper first analyses the basic principles of how VSC-HVDC participates in system frequency stability control. Then, in response to the frequency stability control requirements of the sending and receiving power systems, a droop FLC strategy is designed. Furthermore, a multi-objective optimization method for the parameters of the droop FLC is proposed. Finally, a large-scale electromagnetic transient simulation model of the VSC-HVDC interconnected power system is constructed to verify the effectiveness of the proposed droop FLC method.

Optimization of dual-stage controllers in renewable energy sources-based interconnected power systems through refinement of the African Vultures Optimization Algorithm

With an emphasis on a three-region system, this paper explores automaticgeneration control within a conventional framework. Area 2 uses thermal-thermal sources, Area 3 uses gas-thermal sources, and Area 1 uses thermal-biodiesel sources. IPD(1 + I) is a unique cascade controller that combines integral-proportional-derivative (IPD) components with one-plus-integral (1 + I) components. To find the best gains and settings for the IPD(1 + I) controller, a meta-heuristic method called the African Vulture Optimization Algorithm (AVOA) is applied. Reducing the integral squared error (ISE), as determined by the performance index (Pi), is the main goal. The performance of the IPD(1 + I) controller is evaluated by contrasting it with a range of secondary controllers. Hybrid Peak Area-ISE (hPA-ISE), a novel performance metric, is also assessed in addition to the conventional ISE. The incorporation of renewable energy sources, such solar thermal energy and solid oxide fuel cells, significantly improves the system’s performance. Interestingly, under normal conditions, the IPD(1 + I) controller’s parameter settings continue to work for both sinusoidal and random load situations, obviating the need for additional tuning.

Spiral-refraction mutation prairie dog algorithm: Optimization framework for engineering design of interconnected multimachine power system

Many real-world engineering problems, characterized by high-dimensionality, nonlinearity, nonconvexity, and multi-modality, demand advanced optimization methods. Traditional algorithms may struggle with these challenges. Prairie dog optimization (PDO) was proposed for function optimization but faces limitations in balancing exploration and exploitation due to two reasons. The first one is related to diversity features which may not be efficient, and the second one is related to having no leading mechanism for direct search feature towards the promising regions. With that in mind, this study introduces an enhanced PDO variant, improved PDO (IPDO), addressing PDO's drawbacks through two key strategies: refraction-based learning (RBL) and spiral search learning (SSL). RBL enhances exploration by generating refraction solutions, while SSL conducts deep local searches around the best solution, strengthening exploitation. IPDO's performance is evaluated on benchmarks, IEEE CEC2017/CEC2020 test suites, and real-world constraint engineering optimization problems. Comparative analyses, including statistical measures, convergence analysis, and boxplot analysis, demonstrate IPDO's superiority. Besides, the IPDO is applied to estimate more promising parameters of power system stabilizer utilized in an interconnected multimachine power system using Western System Coordinating Council three-machine, nine-bus power system. Results illustrate that the IPDO harvests the better estimation among the other methods, making it to be an efficient and powerful tool for dealing with the efficient operation of an interconnected multimachine power system which is a challenging real-world engineering problem.

Multi-source coordinated low-carbon optimal dispatching for interconnected power systems considering carbon capture

The overall electricity consumption of electrolytic aluminum and ferroalloy loads is significant, and some of these loads have dispatch potential that can be used to locally absorb wind power while reducing dependence on conventional thermal power. To characterize the uncertainty of wind power, a fuzzy set of wind power forecasting error probability distribution based on the Wasserstein distance was first established, and the approximate radius of the fuzzy set was corrected under extreme scenarios. By introducing joint chance constraints, the inequalities of uncertain variables were established at the lowest confidence level to improve the reliability of the model. Next, a two-stage distributed robust optimal scheduling model for source-load coordination was developed. In the first stage, wind power forecasting information was fully utilized to schedule the electrolytic aluminum load and optimize unit commitment. In the second stage, the uncertainty of wind power output was considered to schedule the ferroalloy load and optimize unit output. The model was approximately transformed into a mixed-integer linear programming problem and solved using a sequential algorithm. The IEEE 24-bus system was used for case validation. The validation results show that the model can effectively improve wind power absorption capacity, reduce overall operating costs, and achieve a balance between low carbon emissions and robustness.

Improving Frequency Control Strategy of Interconnected Power Systems with Renewable Energy Integration Using an Adaptive Neuro-Fuzzy Inference System Controller

Improving Frequency Control Strategy of Interconnected Power Systems with Renewable Energy Integration Using an Adaptive Neuro-Fuzzy Inference System Controller

Leveraging Pumped Storage Power Plants for Innovative Stability Enhancement of Weakly Interconnected Power Systems

The hybrid AC/DC grid, based on a significant share of renewable energy sources, is gradually becoming an essential aspect of the modern energy system. The integration of intermittent renewable generators into contemporary energy systems is accompanied by the decommissioning of power plants containing synchronous generators. Consequently, this leads to a reduction in system inertia and an increase in the risk of stability disruption. The abrupt disconnection of the primary generator or power line can result in an unanticipated mismatch between power generation and consumption. This discrepancy can trigger substantial and swiftly evolving alterations in power distribution, angular speed, load flow, and the frequency of generators. The risks of an energy system collapse can be mitigated through automation, enabling rapid adjustments to generation and load capacities, as well as power flows, in the electrical network. This article justifies the utilisation of a power control method for high-voltage power line interconnections. The technology of hydro storage power plants and measurements of voltage phasors are employed. The potential for easing power flow restrictions and realising substantial economic benefits is supported by the results obtained using simplified dynamic model of the Baltic power system and Nord Pool electricity market model.

Distributed observer for fault estimation in Load-Frequency Control of multi-area power systems with communication delays

This paper proposes an innovative approach to designing a distributed observer for fault and state estimations in Load Frequency Control (LFC) of time-delayed multi-area interconnected power systems. To reach this goal, the paper first provides exhaustive information and analysis on the structure, disturbances, and faults in multi-area power systems. Then, an L1 observer with the capability to simultaneously estimate the system’s states, process/actuator faults, and sensor faults is proposed. This observer exhibits robustness against various types of disturbances as well as time delays present within both the system and the communication network. The sufficient conditions for designing the proposed observer, guaranteeing the system stability, and minimizing the L1 performance index, are expressed as optimization problems employing Linear Matrix Inequality (LMI) techniques. Additionally, the effectiveness and credibility of the proposed distributed observer in estimating all states and faults in all areas are validated through simulation results.

Trade-off between frequency stability and renewable generation – Studying virtual inertia from solar PV and operating stability constraints

The significant increase in solar PV and wind capacity worldwide has raised growing concerns about power system frequency stability in several countries. One reason for this is that these renewable technologies offer almost no inertial response. However, there are some options available to address this issue. Renewables could now offer virtual inertia. Also, power system operators could impose frequency stability constraints as part of the generation Unit Commitment (UC). These options could potentially have a large impact on renewable generation and hence also on energy costs and system emissions. In this paper, we study two key options improving stability, inertia from solar PV generators supplied by virtual synchronous machines, and frequency stability constraints as part of the UC. We assess N-1 generation contingencies for the interconnected power systems of Chile, Argentina, and Peru. We found that the option of virtual inertia reduces the violation of the RoCoF in hours of high solar generation, without affecting renewable generation. On the other hand, frequency stability constraints ensure non-violation of all stability parameters but reduce renewable generation by 12 %. This reduction increases total operating costs by about 35 %, even when the constraints are combined with virtual inertia and battery support.

System Frequency Response Models for the Ecuadorian Interconnected Power System

System Frequency Response Models for the Ecuadorian Interconnected Power System