Power System Regulation Research Articles

Advanced Neural Network-Based Load Frequency Regulation in Two-Area Power Systems

In this paper, enhancing dynamic performance in power systems through load frequency control (LFC) is explored across diverse operating scenarios. A new Neural Network Model Predictive Controller (NN-MPC) specifically tailored for two-zone load frequency power systems is presented. ” Make your paper more scientific. The NN-MPC marries the predictive accuracy of neural networks with the robust capabilities of model predictive control, employing the nonlinear Levenberg-Marquardt method for optimization. Utilizing local area error deviation as feedback, the proposed controller's efficacy is tested against a spectrum of operational conditions and systemic variations. Comparative simulations with a Fuzzy Logic Controller (FLC) reveal the proposed NN-MPC's superior performance, underscoring its potential as a formidable solution in power system regulation.

A blockchain consensus mechanism for real-time regulation of renewable energy power systems

With the ongoing development of renewable energy sources, information technologies and physical energy systems are further integrated, which leads to challenges in ensuring the secure and stable operation of renewable energy power systems in the face of potential cyber threats. The strengths of blockchain in cybersecurity make it a promising solution to these challenges. However, existing blockchains are not well-suited for control tasks due to their low real-time performance. Here, we present a consensus mechanism that enables real-time security control of systems, called Proof of Task. Instead of solving meaningless hash puzzles in Proof of Work, Proof of Task addresses problems closely related to the stable operation and control performance of these systems. With the proposed verification mechanism, Proof of Task significantly enhances the real-time performance of blockchain while mines its computational resources for tasks of interest. To demonstrate the effectiveness and necessity of Proof of Task, it is deployed across three renewable energy power systems. The results show that Proof of Task markedly fortifies the security and computing capability of these systems, ensuring their reliable and stable operation. This work highlights the promise of blockchain to facilitate security control and trusted computing of large-scale, complex-dynamic systems.

Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller

Maintaining a stable balance between generated power and load demand is a critical challenge in modern power systems, especially with the increasing integration of renewable energy sources like photovoltaic (PV) systems. This study introduces a novel hybrid educational competition optimizer with pattern search (hECO-PS) algorithm to optimally tune a cascaded proportional-derivative with filter and proportional-integral (PDN-PI) controller for load frequency control (LFC) in a two-area power system comprising a PV system and a reheat thermal power system. The proposed hECO-PS algorithm enhances both global exploration and local exploitation capabilities, resulting in superior convergence rates and solution accuracy. The controller's performance was evaluated under various scenarios, including a 10% step load change and solar radiation variations, demonstrating significant improvements in frequency regulation. The hECO-PS tuned PDN-PI controller achieved a minimum integral of time-weighted absolute error (ITAE) value of 0.4464, outperforming conventional methods like the modified whale optimization algorithm and sea horse algorithm, which yielded ITAE values of 2.6198 and 0.8598, respectively. Furthermore, the proposed controller reduced settling time by up to 46% and minimized overshoot by up to 40%. These results confirm the efficacy of the proposed approach in enhancing system stability and reliability under dynamic operating conditions, suggesting it as a promising solution for LFC in modern power systems with high renewable energy penetration.

Optimal Sliding Speed and Contact Pressure Design of On-Load Tap Changer Based on Multivariate Nonlinear Regression

During the voltage regulation of on-load tap changers (OLTCs), the movement of the contacts can easily cause arcing, which may lead to erosion or malfunction. To reduce the energy and probability of arcing, we focus on designing an optimal range for the sliding speed and contact pressure of the contacts to minimize arc energy. Initially, our research introduces a novel OLTC arc testing platform to simulate the motion of static and dynamic contacts, exploring the relationship between different sliding speeds, contact pressures, and factors like arc voltage waveform, arcing rate, arc resistance, and arc energy. Subsequently, by employing multiple nonlinear regression methods, we establish functional relationships between sliding speed and arc energy, as well as contact pressure and arc energy, evaluating the fit using correlation coefficients. Finally, through analyzing their nonlinear behaviors, we determine the ideal sliding speed and contact pressure. The results indicate that when the OLTC contacts slide at an optimal speed between 89 and 103 mm/s and optimal contact pressure between 1.5 and 1.7 N, the arc energy can be minimized, thereby enhancing the performance and lifespan of the on-load tap changer. This study offers feasible insights for the design and operation of OLTCs, aiding in the improvement of power system regulation.

Two-Layer Optimal Scheduling and Economic Analysis of Composite Energy Storage with Thermal Power Deep Regulation Considering Uncertainty of Source and Load

A two-layer scheduling method of energy storage that considers the uncertainty of both source and load is proposed to coordinate thermal power with composite energy storage to participate in the peak regulation of power systems. Firstly, considering the characteristics of thermal power deep peak regulation, a cost model of thermal power deep peak regulation is constructed and fuzzy parameters are used to manage the uncertainty of wind, photovoltaics, and load. Secondly, based on the peaking characteristics and operating costs of composite energy storage, a two-layer optimal scheduling model of energy storage is constructed. The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. Finally, we verify the effectiveness of the proposed strategy based on an IEEE 39-node system.

Improved frequency regulation of dual-area hybrid power system with the influence of energy storage devices

Improved frequency regulation of dual-area hybrid power system with the influence of energy storage devices

A method for selecting the type of energy storage for power systems with high penetration of renewable energy with multi-application scenarios

Energy storage (ES) configurations effectively relieve regulatory pressure on power systems with a high penetration of renewable energy. However, it is difficult for a single ES type to satisfy the complex regulatory demands of a power system. There has been little research on the selection methods for multiple types of ES that meet the demands of multiple application scenarios of power systems. This study introduces a method for the selection of ES types for power systems with a high penetration of renewable energy to determine the optimal ES types for multi-application scenarios. First, a generation method for ES schemes is proposed based on K-means clustering and combination theory. Then, considering the demands of peak shaving, frequency regulation and reserve of power systems with high penetration of renewable energy, an optimisation model of the expected indices of the ES is constructed to meet the demands of multi-application scenarios. Finally, the comprehensive evaluation method for ES schemes based on the error mean and the selection method for optimal ES types based on projection technology are proposed. Numerical studies show that for the power system in the example whose demand coefficients for peak shaving, frequency regulation and reserve are 30.59 %, 26.29 % and 43.11 %, respectively, a combination of pumped storage and colloidal battery, lithium iron phosphate battery, or lithium titanate battery is the most suitable ES type for the power system. This study offers a reference for the selection of ES types when an ES is configured.

Construction of a photovoltaic low-voltage grid connected power regulation system based on partition control

Abstract Photovoltaic power generation is a green and renewable power generation mode and has been widely used. However, the power fluctuation of photovoltaic power generation has a significant impact on the power grid, which is very important. Based on the concept of regional control, this paper studies the photovoltaic low-voltage grid-connected power regulation system. The photovoltaic power generation system is divided into multiple regions, and each region is provided with an independent control unit and regulation strategy under the control of multiple control areas. The regional factors are combined, such as light intensity and power voltage. In the case of the city, the impact of the area on the whole is dynamically adjusted to achieve the overall balance of power and the stability of the system. The experimental results show that the photovoltaic low-voltage grid-connected power regulation system constructed by regional control performs well and has a high degree of stability. According to the change in light intensity and load demand, the system can achieve accurate control and distribution of photovoltaic power generation.

Exponential PID controller for effective load frequency regulation of electric power systems

Load frequency regulation (LFR) is an indispensable scheme in planning electrical power production to provide consumers with stable, reliable and uninterrupted power. In the face of complicated power system (PS) structures with increasing and intricate power demand, new controllers that offer not only good performance, but also easy commissioning in practice are required. To this end, this research introduces an exponential PID (EXP-PID) controller as a new control scheme to ameliorate the LFR performance of PSs. This controller is simple to design and has a nonlinear feature inherited from two tunable exponential functions, which are placed in front of the PID controller and act on the error signal and its time derivative individually. To achieve the utmost performance, the EXP-PID controller’s parameters are procured by a corrected variant of the snake optimizer (co-SO). To validate the proposed control scheme, various single-/multi-area single-/multi-source PSs favored in the area are considered as test benches. A thorough comparison with the state-of-the-art approaches is performed to disclose the true efficacy of our proposal. Among the rivals, co-SO tuned EXP-PID controller, despite its simplicity, is found to render credible and promising performance in mitigating frequency and tie-line power deviations effectively.

Enhancing hydrogen generation through advanced power conditioning in renewable energy integration

Producing hydrogen using renewable energy is a pivotal move towards cleaner and eco-friendlier energy generation, playing a vital role in safeguarding the environment. This method merges power electronic tools with electrolysers, which are key in enhancing hydrogen creation efficiency. Given that electrolysis operate on direct current (DC) voltage, there's a need for DC-DC or AC-DC converters to guarantee the right voltage and current for optimal electrolysis. This study aims to present a power regulation system tailored for hydrogen production powered by renewable resources. This system consists of two main stages: the matrix converter and the 12-pulse diode rectifier. The matrix converter ensures a controlled intake of current from the alternating current (AC) side, leading to a sinusoidal output with limited harmonic disruption. Additionally, it produces an AC voltage with a controlled magnitude and frequency, designed to suit the 12-pulse diode rectifier that follows. This meticulous voltage control is fundamental, granting enhanced operational adaptability and producing a high-quality waveform to support the electrolysis. Finally, the 12-pulse diode rectifier's task is to transform the AC from the matrix converter into a consistent DC voltage, crucial for effective hydrogen production.

Frequency regulation feasible region assessment and optimization of wind farm based on data-driven model predictive control

With the integration of large-scale wind turbines (WTs) into grids via electronic interfaces, power system operators have necessitated frequency support from wind farms. Due to the large number of WTs and their complex dynamic characteristics, it is necessary to assess the primary frequency regulation (PFR) capability and construct feasible region of wind farms. In order to cope with the problems of incomplete parameters, analytical solving complexity and the coupling influence of power system regulation characteristics, this paper develops a data-driven state space mapping linear model predictive control (MPC) to assess the maximum PFR capability of wind farms and reasonably distribute coefficients to WTs. Besides, a coordinated iteration framework between dispatching center and wind farms is proposed to further optimize the wind farm regulation feasible region. The simulation results verify that the proposed method has the advantages of independence from physical parameters, fast analytical solution, and lower requirements of training samples on limited scenarios.

Quantum model prediction for frequency regulation of novel power systems which includes a high proportion of energy storage

As the proportion of renewable energy generation continues to increase, the participation of new energy stations with high-proportion energy storage in power system frequency regulation is of significant importance for stable and secure operation of the new power system. To address this issue, an energy storage control method based on quantum walks and model predictive control (MPC) has been proposed. First, historical frequency deviation signals and energy storage charge–discharge state signals are collected. Simulation data are generated through amplitude encoding and quantum walks, followed by quantum decoding. Subsequently, the decoded data are inputted into the MPC framework for real-time control, with parameters of the predictive model continuously adjusted through a feedback loop. Finally, a novel power system frequency regulation model with high-proportion new energy storage stations is constructed on the MATLAB/Simulink platform. Simulation verification is conducted with the proportional–integral–derivative (PID) and MPC methods as comparative approaches. Simulation results under step disturbances and random disturbances demonstrate that the proposed method exhibits stronger robustness and better control accuracy.

Development of Active Wind Vane for Low-Power Wind Turbines

This paper proposes the development of an active control system to control the power output of a low-power horizontal-axis wind turbine (HAWT) when operating at wind speeds above the rated wind speed. The system is composed of an active articulated vane (AAV) in charge of the orientation of the wind turbine, which is driven by an electric actuator that changes the angle of the AAV to maintain a constant power output. Compared with the passive power regulation systems most often used in low-power HAWTs, active systems allow for better control and, therefore, greater stability of the delivered power, which reduces the structural stresses and allows for controlled braking in any wind condition or during system failures. The control system was designed and simulated using MATLAB R2022b software, and then built and evaluated under laboratory conditions. For the control design, the transfer function (TF) between the pulse width modulation (PWM) and the AAV angle (θ) was determined via laboratory tests using MATLAB’s PIDTurner tool. For the simulation, the relationship between the power output and the AAV angle was determined using the vector decomposition of the wind speed and wind rotor area. Wind speed step and ramp response tests were performed for proportional–integral–derivative (PID) control. The results obtained demonstrate the technical feasibility of this type of control, obtaining settling times (ts) of 6.7 s in the step response and 2.8 s in the ramp response.

Numerical investigation of hydraulic instability of pump-turbines in fast pump-to-turbine transition

The fast pump-to-turbine transition of a pumped storage unit is highly responsive to electrical power system regulation demands and is a critical process for the unit itself. The correct prediction of this hydraulic transient process is crucial to avoid issues during machine operation. In this study, a three-dimensional numerical model of the transition process of a pumped storage hydraulic system was proposed and analyzed. Numerical simulations were performed to investigate the variations in external parameters, pressure pulsations, and the evolution of internal flow patterns and vortical structures in the pump turbine. The results showed that the stepwise variations in the flow rate, torque, and force were synchronized with the movement of the guide vanes. Notably, during the pump braking operation and runner speed reversal, a considerable time period with significant force oscillations and intense torque fluctuations occurred, particularly in the vaneless region, where pressure fluctuations were notable. Vortical structures that induce vibrations and intense pressure fluctuations were localized near the runner inlet and at the leading and trailing edges of the guide and stay vanes. This study offers theoretical insights that are crucial for enhancing the stability of the fast pump-to-turbine transitional process, thus optimizing its control strategies.

Real-time V2G simulator for grid system frequency and voltage regulation with fault ride-through capabilities

Electric vehicles (EVs) have become one of the promising power grid ancillary services. They can help reduce the intermittent of renewable energy sources by supporting active power and frequency control services. Additionally, bi-directional chargers included into EV batteries can supply/consume reactive power for voltage regulation. To improve voltage quality, a unique control approach is devised to offer fault ride-through. In this study, real-time charging optimization schemes based on particle swarm optimization are developed to coordinate the EVs charging/discharging power with the grid power dispatches depending on the charging priority and preferential electricity prices. Five different car user profiles including different initial state of charge and plug in state have been depicted. Different optimum issues are carried out with comprehensive simulations employing hardware in the loop via real-time simulation for a modified IEEE 14-bus test system. Where different frequency and voltage controls, management strategies, variant fault scenarios, benefits, and challenges for power system regulation with EVs are illustrated. According to the simulation results, the proposed optimized charging strategies reduce the total expenses of EV parking station by 40 % compared to other cases, hence maximizing EV owner satisfaction. The net load curve is smoothed and reduced by 11 %, particularly during peak period.

Transient voltage performance and protection design of variable frequency ac three-stage generator for more electric aircraft

Abstract Nowadays, variable frequency AC generation system is widely used on more electric aircraft because of their advantages of simple structure, high power density, and high reliability. However, a variable frequency system has a wide range of operating speeds and frequencies, and its exciter field is designed to be highly saturated at low speed. Under the condition of a saturated exciter field at high speed, the generator can produce a very high voltage, which will cause damage to aircraft utilization equipment, leading to catastrophic failures. Therefore, to protect the safety of the aircraft, transient voltage regulation performance and voltage protection design are critical in the system design of variable frequency AC generation. This paper focuses on the design of voltage regulation and protection of variable frequency electrical power systems that can meet airworthiness requirements.

Cascaded Fractional Control Approach for Frequency Regulation of Multi-Source Power System Integrating Renewable Energy Resources

Cascaded Fractional Control Approach for Frequency Regulation of Multi-Source Power System Integrating Renewable Energy Resources

Analysis of power system frequency and active power based on wind-storage combined frequency modulation system

Abstract To solve the problem of frequency and active power regulation of power systems, this paper proposes a wind-storage combined frequency modulation strategy. The mathematical models of doubly-fed induction machines, pump turbines, and wind turbines are established. Based on wind power frequency modulation, the doubly-fed variable-speed pumped storage unit is added to establish a combined frequency modulation system, and a simulation model on Simulink to analyze the participation of different parts of the combined system in frequency modulation and the active power output of the unit when the load changes. The simulation results show that when the load increases or decreases, the addition of a doubly-fed variable speed pumped storage unit can effectively improve the frequency modulation performance of the system, reduce the fluctuation numbers and amplitude, and reduce the deviation after stabilization. By changing its active power output, a new balance of the system power can be reached, which is conducive to the secure and steady functioning of the power system.

Distance optimization and directional overcurrent relay coordination using edge-powered biogeography-genetic algorithms

The effective functioning and regulation of power systems crucially rely on the coordination of distance and directional overcurrent relays. Accurate fault detection and successful clearing sequences require support for each relay and the maintenance of the coordination time interval (CTI) between major distance relays, directional overcurrent relay support, and other relay zones. Efficiently initiating relays while adhering to complex coordination limitations poses a challenging task that demands innovative solutions. This study addresses the intricate problem of relay coordination by employing heuristic methods, specifically genetic algorithms (GA) and biogeography-based optimization (BBO), in both a 9-bus and 39-bus system. The primary objective is to determine the most efficient time setting factor (TSM) that minimizes the duration of relay operation. Additionally, the intelligent features of the overcurrent relay are carefully chosen to enhance the research's results. The integration of edge computing capabilities plays a significant role in advancing this coordination method. By incorporating advanced algorithms and communication technologies at the edge, the prompt activation of relays becomes possible, thereby meeting coordination demands. This study explores the combination of edge-based servers with genetic algorithms (GA) and biogeography-based optimization (BBO) techniques to enhance relay coordination. The findings indicate a notable enhancement compared to conventional approaches. However, comparative research suggests that BBO's performance is similar to GA, without a distinct advantage in achieving higher outcomes.

Techno-Economic Analysis of Electric Heating Load Participation in Power System Power Regulation

People are beginning to develop and use new energy sources, but it leads to a lack of power system regulation, so it is crucial to analyse the change of load power. In this paper, the electric heating load is taken as an example, and firstly, the properties of the steady state solution of the differential equation are analysed by changing the parameters of the indoor and outdoor equivalent heat capacity and equivalent thermal resistance, and it is found that the indoor equivalent heat capacity and thermal resistance have a significant effect on the results. Then, after differentiating the differential equations, the indoor temperature changes and the electric heating equipment switching state curves for one day were plotted, and it was found that the daily electricity cost increased as the temperature difference between indoor and outdoor increased. Then, the remaining switchable time values are analysed based on the load's current switch-on state and temperature-limited intervals, and the power upward and downward adjustments of the sustainable time are plotted schematically. In order to enhance the model universality so that it is no longer limited by the current switch on/off state, the switching value of each state is set to change dynamically to obtain a new power regulation diagram, and finally in this paper, we extend the model to multi-family, plot their one-day indoor temperature changes and equipment switching state diagrams and analyse the economic benefits.