Voltage Regulation Performance Research Articles

Investigating PID Controller Effectiveness: An Extensive Analysis and Wide-ranging Uses

This study offers an in-depth investigation of the performance of proportional-integral-derivative (PID) controllers, providing an extensive evaluation and analyzing a wide range of applications. PID controllers, essential feedback mechanisms in various domains, are recognized as foundational instruments in control systems. This study evaluates PID controllers in in scenarios such as DC motor speed regulation, power system stability, Automatic Voltage Regulator (AVR) performance optimization, time delay processes, load frequency management, DC drive control, systematic process stability, and their developments in industrial control. The purpose of the study is to highlight the adaptability and effectiveness of PID controllers in contemporary control systems, including how artificial intelligence (AI) can be integrated into PID controller tuning.

Robust control strategies applicable to DC–DC converter with reliability assessment: A review

AbstractThis paper provides an overview of various control strategies for DC–DC converters along with a brief discussion on various performance indices for evaluating the reliability of designed controller. DC–DC converters are emerging as the fastest‐growing interfacing devices in the world because of their emergent applications in almost all domains of engineering. Notably, the non‐linear behavior of DC–DC converters offers a perplexing problem in designing a robust controller. A robust controller must ensure proper closed‐loop stability with desired performance and reliable control for output voltage regulation in the event of various possible perturbations. This creates the requirement for practically implementable non‐linear controllers that can effectively overlook the drawbacks of linear controllers. The prominence of this composition is based on the expansion in tuning techniques of proportional‐integral‐derivative controller gain parameters using linear strategies and heading towards non‐linear strategies by reviewing 196 research papers. The modification in non‐linear control strategies in terms of their fundamental features associated with key benefits and limitations are comprehensively reviewed. This study mostly revolves around non‐linear internal model control (IMC) strategies for parameter tuning of IMC‐based controllers for various order of plants with an improved degree of freedom.

Cooperative control of the DC-link voltage in VSC-MTDC grid via virtual synchronous generators

Introduction: Virtual Synchronous Generators (VSGs) are used in Voltage Source Converter-based Multi-Terminal High-Voltage Direct Current (VSC-MTDC) systems to enhance power system stability. However, the MTDC framework can lead to instability due to reduced inertia in certain grid areas, especially during load switching at VSC stations. This instability is exacerbated by untimely adjustments of the VSG's power setpoint, leading to voltage and frequency oscillations.Methods: This study introduces a cooperative control approach for the DC voltage of the VSG, employing a consensus algorithm and Model Predictive Control (MPC). This method aims to achieve incremental power for the VSG and provide interactive power commands for both the grid side and the wind farm side. The consensus algorithm ensures coherent system adjustments, while the MPC algorithm tracks DC-side voltage changes in real time.Results: The application of this cooperative control approach significantly enhances DC voltage regulation performance. It effectively reduces the extent of frequency drops and mitigates secondary frequency drop (SFD) issues, particularly those arising from the use of wind farms for frequency regulation and the associated speed recovery in wind turbine units.Discussion: The increase in supplemental power effectively utilizes the energy stored in DC-side capacitors for power balance regulation and introduces additional inertial power into the system. Electromagnetic transient simulations have confirmed the effectiveness of the Consensus MPC-VSG method, demonstrating its ability to optimize the dynamic performance of VSC-MTDC systems and promote stability in DC voltage and frequency.Conclusion: The findings suggest that employing the Consensus MPC-VSG method offers a promising solution for enhancing the stability and operational efficiency of VSC-MTDC systems, addressing the challenges posed by the inherent segmentation of the grid and the integration of renewable energy sources like wind farms.

Development of AVR controller performance using exponential distribution and transit search optimization techniques

This paper attempts to obtain the optimal solution to enhance the performance of the Automatic Voltage Regulator (AVR) Controller, as it is an essential tool to control the synchronous generator output voltage. The controller improves AVR system stability and response time; moreover, it is demonstrated that the Proportional Integral Derivative (PID) controller achieves the goal by applying two artificial intelligence techniques to design the optimal values of the Automatic Voltage Regulator (AVR) PID controller for a single area model. The first is the Exponential Distribution Optimization Algorithm (EDO), and the second is the Transit Search Optimization Algorithm (TS). EDO and TS are used to determine the best PID controller parameters and have also recently been developed in the breadth of optimization problems and associated computational complexities field. The objective function, Integrated Square Error (ISE), minimizes the error voltage for improved stability and response. The outcomes are compared to various optimization techniques to prove the validation of the two proposed methods. The results show that the EDO and TS proved their superiority through their stability level to the AVR system and their steady-state error improvement. Moreover, the dominant effect of damping frequency decreases the oscillation and the reduced maximum overshoot that protects the loads from being subjected to non-permissible over-voltage levels. Finally, a robustness test is applied to the two proposed optimization methods to prove their reliability and effectiveness.

Robust Parametric Programming for Adaptive Piecewise Linear Control of Photovoltaic Inverters to Regulate Voltages in Power Distribution Systems

This paper proposes a robust parametric programming (RPP) method to adaptively obtain piecewise linear control functions of photovoltaic (PV) inverters for real-time voltage regulation in distribution systems. First, the voltage regulation problem is designed as a multi-parameter programming problem, which is transformed into single-parameter linear programming (sp-LP) problems for realizing local control of a PV inverter while considering the maximum voltage deviation caused by other PV units. Second, an alternating iterative algorithm is developed to solve the sp-LP problem of each PV unit and obtain the control functions of all the PV units. Third, considering the information on PV power correlation, a two-level parametric programming problem is established to enhance the voltage regulation performance of PV inverters. A geometric method is developed to solve the inner-level problem, and breakpoint reduction with robust interpolation is developed to improve the computational efficiency in solving the outer-level problem. Four distribution systems integrated with PV units are used to validate the effectiveness of the proposed method. Numerical results show that the performance of the proposed PV inverter control strategy is close to that of the ideal optimal solution and superior to existing piecewise linear control strategies.

One High Voltage Regulation Method and Related Control Strategy in the DC Transmission System

Background: With the development of power transmission system, the problem of small transmission capacity and low power quality of traditional AC power distribution methods is becoming increasingly prominent. The DC power distribution method promotes its own rapid development because of its suitability of connection between distributed generation and grid, high power quality, large power supply capacity, low line cost and high reliability. Objective: In order to improve the transient performance when the system power fluctuates, a control method that can perform voltage regulation to the DC system is designed in the process of calculating the power command value of each converter station at the system level control. Simulation results show that the designed control method can effectively improve the inertial characteristics and transient response of DC transmission system. Methods: Aiming at the shortcomings of slow response speed and poor stability when the traditional dual closed-loop PI controller is used as a converter level controller, a sliding mode controller is designed. Simulation results show that the designed sliding mode controller can improve transient characteristics of voltage regulation. Results: Voltage control strategy of the DC transmission network based on the converter station is verified. Conclusion: A voltage control strategy based on distributed generation and secondary load switching is designed. The simulation verifies the effectiveness of the designed control strategy.

Optimal design of controller for automatic voltage regulator performance enhancement: a survey

Optimal design of controller for automatic voltage regulator performance enhancement: a survey

Decentralized Power Sharing with Frequency Decoupling for a Fuel Cell-Battery DC Shipboard Power System

The maritime industry is under increasing pressure to reduce its carbon footprint by adopting new energy generation and storage technologies in shipboard power systems (SPS). Fuel cells (FCs) show great potential as primary power sources when hybridized with energy storage systems (ESS). Integrating different technologies in future SPS requires the coordination of power generation and storage modules, which can be facilitated by DC technology with power electronics interfaces. However, studies on FC integration have primarily focused on small-scale applications with centralized control architectures. There has been little research on the modular control of multiple FC and battery modules in SPS. This study proposes a decentralized droop-based power sharing approach with load frequency decoupling to efficiently utilize power system modules based on their dynamic capabilities. The proposed strategy further incorporates decentralized voltage regulation and state-of-charge (SoC) management functions. The methodology was applied to a short-sea cargo vessel with an FC-battery DC power system. The results indicate that the mission load profile can be satisfied while limiting fluctuations in the FC output power. Moreover, the proposed strategy achieves the same voltage regulation performance as a centralized proportional-integral (PI) controller and can be easily tuned to achieve load frequency decoupling with the desired time constant. Finally, a comparative analysis shows how the trade-off between the dynamic operation of the FC and the discharge depth of the ESS is affected by the choice of time constant.

Incentivizing Prosumer Voltage Regulation for Unbalanced Radial Distribution Networks

Voltage regulation in distribution networks is becoming extremely challenging with the increased penetration of rooftop photovoltaic (PV) generation. Many recent studies demonstrate the effectiveness of power control of smart inverters for voltage regulation purposes. However, how to fully incentivize demand-side participation in voltage regulation is yet to be answered. This paper seeks to address this challenge by designing a comprehensive voltage regulation incentive scheme for customers to control their smart inverters in unbalanced radial distribution networks. A three-phase residential network from a Distributed Network Service Provider (DNSP) in Australia is modelled in the open-source distribution system simulator OpenDSS with real load and PV data, and an control algorithm to optimize the households' smart inverters in a distributed fashion is developed using game theory. The proposed algorithm is implemented in MATLAB, which is guaranteed to approach the optimal solution. Simulation results show that the proposed scheme achieves better voltage regulation performance as the widely adopted localized voltage-var droop control method and, at the same time, with lower costs to the prosumers.

Tractable Data Enriched Distributionally Robust Chance-Constrained Conservation Voltage Reduction

This paper proposes a tractable distributionally robust chance-constrained conservation voltage reduction (DRCC-CVR) method with enriched data-based ambiguity set in unbalanced three-phase distribution systems. The increasing penetration of distributed renewable generation not only brings clean power but also challenges the voltage regulation and energy-saving performance of CVR by introducing high uncertainties to distribution systems. In most cases, the conventional robust optimization methods for CVR only provide conservative solutions. To better consider the impacts of load and PV generation uncertainties on CVR implementation in distribution systems and provide less conservative solutions, this paper develops a data-based DRCC-CVR model with tractable reformulation and data enrichment method. Even though the uncertainties of load and photovoltaic (PV) can be captured by data, the availability of smart meters (SMs) and micro-phasor measurement units (PMUs) is restricted by cost budget. The limited data access may hinder the performance of the proposed DRCC-CVR. Thus, we further present a data enrichment method to statistically recover the high-resolution load and PV generation data from low-resolution data with Gaussian Process Regression (GPR) and Markov Chain (MC) models, which can be used to construct a data-based moment ambiguity set of uncertainty distributions for the proposed DRCC-CVR. Finally, the nonlinear power flow and voltage dependant load models and DRCC with moment-based ambiguity set are reformulated to be computationally tractable and tested on a real distribution feeder in Midwest U. S. to validate the effectiveness and robustness of the proposed method.

Automatic voltage stabilization system for substation using deep learning

The operating voltage in the substation must be maintained at its rated voltage within the specified standard because a voltage outside the specified range may cause a malfunction of the power facility and interfere with the stable power supply. Therefore, the voltage regulation process to maintain the rated voltage of the substation is essential for the stability of the power system. However, the voltage regulation process is currently performed manually by resident staff. Voltage regulation based on human judgment increases the uncertainty of voltage stabilization and makes efficient operation in consideration of the economic feasibility of power facilities difficult. Therefore, this paper proposes an automatic voltage stabilization system that can automatically perform voltage regulation. Instead of predicting the electrical load or overvoltage conditions studied so far, we focus on more direct, scalable input capacity prediction for an automatic voltage stabilization system. First, the proposed system predicts the input capacity required for a given situation through a trained stacked LSTM model. Second, an optimal regulation plan is derived through an optimization process that considers the economic feasibility of power facility operation. Additionally, the development of the user interface makes it possible to visualize the operation of algorithms and effectively communicate the models? predictions to the user. Experimental results based on real substation data show that the proposed system can effectively automate the voltage regulation process.

Optimizing Automatic Voltage Regulation: A Deep Reinforcement Learning Approach

This paper presents a novel approach to enhance the performance of Automatic Voltage Regulator (AVR) systems in power systems using Deep Reinforcement Learning (DRL). The AVR plays a critical role in maintaining voltage stability and ensuring reliable power delivery. However, conventional control strategies, such as PID controllers, have limitations in handling complex and nonlinear power system dynamics. In this study, the application of DRL techniques is explored, particularly the Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm, to AVR control. This algorithm offers the advantage of handling continuous action spaces and enable the controller to learn optimal control policies directly from the system's state information. The results show that the DRL approach outperforms the traditional PID and Neural Network-based control approaches, with the shortest time response and the best voltage regulation performance. The use of DRL in AVR system control shows promising potential for improving the efficiency and accuracy of power system control. This research provides insights into the advantages of DRL for process control and highlights its potential for future applications in power system control.

A Robust High-Quality Current Control With Fast Convergence for Three-Level NPC Converters in Microenergy Systems

Three-level neutral-point-clamped (3L-NPC) power converters are necessary interfaces to form micro-energy systems. Naturally, designing a suitable control scheme, featuring superior dynamics, strong robustness, and simple structure, is a promising solution to guarantee more efficient operation of converter. This paper proposes a robust high-quality current control strategy for the 3L-NPC power converter in the stationary <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha \beta$</tex-math></inline-formula> frame. A super-twisting algorithm coupled with a Luenberger observer current controller is proposed to deal with the poor sinusoidal current tracking issue due to the existing inductance/grid frequency deviations and the disturbance of the sinusoidal dynamic nature. Additionally, an extended sliding mode disturbance observer based proportional control is built to dramatically enhance voltage regulation performance, in the case of capacitance deviations and unknown dc-loads. Experimental data confirm the effectiveness of the proposed solution outperforms the conventional proportional-resonant/-integral control in terms of accurate tracking current/voltage, anti-disturbance, and grid current total harmonic distortion.

Armature Reaction Analysis and Performance Optimization of Hybrid Excitation Starter Generator for Electric Vehicle Range Extender

The armature reaction of the hybrid excitation starter generator (HESG) under load conditions will affect the distribution of the main magnetic field and the output performance. However, using the conventional field-circuit combination method to study the armature reaction has the problem of low accuracy and inaccurate influencing factors. Therefore, this paper proposed a graphical method to analyze the armature reaction and a new type of HESG with a combined-pole permanent magnet (PM) rotor and claw-pole electromagnetic rotor. The analytical formula of the voltage regulation rate under the armature reaction was derived using the graphical method. The main influencing parameters of the armature reaction magnetic field (ARMF) were analyzed, and the overall output performance was analyzed using finite element software. On this basis, comparison analyses before and after optimization and the prototype test were carried out. The results show that the direct-axis armature reaction reactance, quadrature-axis armature reaction reactance, and voltage regulation rate of the optimized HESG were significantly reduced, the output voltage range of the whole machine was wide, and the voltage regulation performance was good.

Optimized PID Controller of DC-DC Buck Converter based on Archimedes Optimization Algorithm

This research assesses the suitability of the Archimedes Optimization Algorithm (AOA) as a metaheuristic technique to fine-tune a PID controller in a closed-loop DC-DC buck converter. The converter's core function is to regulate output voltage, ensuring stability despite load fluctuations and input voltage changes. The operational effectiveness of the converter hinges significantly on the gain settings of the PID controller and determining the optimal gain setting for the PID controller is a non-trivial task. For robust performance, the PID controller necessitates optimal gain settings, attainable through metaheuristic optimization. The algorithm aids in identifying ideal proportional, integral, and derivative gains based on varying load conditions. Leveraging the metaheuristic algorithm, the PID controller is optimized to minimize voltage errors, reduce overshoot, and enhance response time. The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). Performance evaluation involves injecting a voltage disturbance into the buck converter with load changes of up to 20%. Results demonstrate the superiority of the AOA-optimized PID controller in voltage recovery. It demonstrates a faster response time and outstanding voltage regulation performance, while also exhibiting minimal performance degradation during load changes. This study concludes that the AOA optimization algorithm surpasses other methods in tuning the PID controller for closed-loop DC-DC buck converters.

Multi-objective battery energy storage optimization for virtual power plant applications

The increasing share of renewable energy sources (RESs) in electricity generation leads to increased uncertainty of generation, frequency and voltage regulation as well as difficulties in energy management. A virtual power plant (VPP), as a combination of dispersed generator units, controllable load and energy storage system (ESS), provides an efficient solution for energy management and scheduling, so as to reduce the cost and network impact caused by the load spikes. This paper proposes a multi-objective optimization (MOO) of battery energy storage system (BESS) for VPP applications. A low-voltage (LV) network in Alice Springs (Northern Territory, Australia) is considered as the test network for this study. The BESS for each customer is used to store and release the energy when required to maintain the voltage regulation performance of the LV network and reduce the cost. To optimize the charge/discharge schedule in each battery, a multi-objective optimization tool (MOOT) is developed, where MOO can directly communicate with DIgSILENT PowerFactory platform to perform multi-time scale simulation. MOO mainly focuses on generating a set of trade-off schedule solutions for each customer over 24 h by considering the customer’s cost and network impact. Then according to the stakeholder’s prior preference, one of the solutions is selected and verified in DIgSILENT PowerFactory with a realistic LV network. We also design several scenarios with different penetrations of photovoltaics (PVs) and batteries to verify how they influence customer’s cost and LV network. With the increasing penetrations of PVs and batteries, the experimental results over the selected solution according to the customer preference show that the customers’ cost can be largely reduced by maintaining the network voltage regulation performance.

Novel TIλDND2N2 Controller Application with Equilibrium Optimizer for Automatic Voltage Regulator

Sustainability is important in voltage regulation control in grids and must be done successfully. In this paper, a novel tilt-fractional order integral-derivative with a second order derivative and low-pass filters controller, referred to as TIλDND2N2 controller, is proposed to enhance the control performance of an automatic voltage regulator (AVR). In this article, the equilibrium optimizer (EO) algorithm is used to optimally determine the eight parameters of the proposed controller. In this study, a function consisting of time domain specifications is used as the objective function. To evaluate the performance of the proposed controller, it is compared with the proportional-integral-derivative (PID), fractional order PID (FOPID), PID accelerator (PIDA), PID plus second order derivative (PIDD2), and hybrid controllers used in previous studies. Then, Bode analysis is performed to determine the achievement of the proposed controller in the frequency domain. Finally, the robustness test is realized to assess the response of the proposed controller against the deterioration of the system parameters. As a result, the proposed controller demonstrates outstanding control performance compared to studies in terms of settling time, rise time and overshoot. The proposed controller shows superior performance not only in frequency domain analysis but also in perturbed system parameters.

Voltage Control Strategy for Improving Disturbance Rejection Performance in Stationary Reference Frame During Parallel Operation of Multimodular UPS

This paper proposes a voltage control strategy to improve the disturbance rejection performance during the parallel operation of multi-modular uninterruptible power supply (UPS). In the standalone operation of UPS, feed-forward control can improve the dynamic performance of output voltage regulation. However, a circulating current can occur when feedforward control is applied in the parallel operation of UPS modules, causing uneven load sharing among the modules. In this study, the reason for the occurrence of the circulating current was analyzed using a circulating current impedance model. A partial feedforward control technique was proposed, which compensates for a portion of the load current by considering the circulating current impedance in the parallel operation of the UPS. However, this reduced the disturbance rejection performance compared with the standalone operation of the UPS, which uses full feedforward compensation gain. Therefore, an additional feedforward control technique was proposed to enhance the disturbance rejection performance. The effectiveness of the proposed control strategy was verified through the experimental result of the parallel operation of 500 W modular double-conversion UPSs.

Design and Control of Two-Stage DC-AC Solid-State Transformer for Remote Area and Microgrid Applications

The critical challenges with integrating renewable energy into the grid are smooth power flow control, isolation between the high-voltage and low-voltage networks, voltage regulation, harmonic isolation, and power quality regulation. This paper considers the design and construction of a two-stage DC-AC solid-state transformer based on wide bandgap (WBG) semiconductor technologies, an optimized medium-frequency transformer, and PI and dq controllers for supplying urban area electric drive systems and microgrid applications. The designed SST consists of a dual active bridge (DAB) DC-DC converter followed by a DC-AC three-phase inverter. Each stage of the SST was simulated with independent controllers. The proposed system was initially developed in MATLAB/Simulink and a laboratory prototype was constructed to verify the results experimentally. Resistive and inductive load were used to test the load disturbance to evaluate the voltage regulation performance. This work has comprehensively provided the performance of a double stage (DC-DC and DC-AC converter) by taking into consideration input voltage, load disturbance, and voltage tracking both in simulation and experiment. The dual active bridge with its controller is able to maintain the desired output reference voltage with minimal voltage ripples under input voltage fluctuations and load variations. Similarly, the three-phase DC-AC converter’s controller exhibits better performance in tracking the desired reference voltage and producing well-regulated AC voltage with low harmonic distortion.

Improve the performance of automatic voltage regulator for power system using self-tuning fuzzy-PID controller

The optimal design of the automatic voltage regulators for a synchronous machine are positively reflected on the quality of voltage stability. This paper is concerned with the design of an AVR by adopting three control techniques. The first one was designed according to the traditional proportional integration-derived (PID) controller while the fuzzy logic was adopted in design the second powerful controller, finally the fuzzy PID controller for an automatic voltage regulator (AVR) based on fuzzy logic technology, selftuning fuzzy proportional integration-derived (STFPID) have been designed to tuning the gains of the PID controller (KP, KI and KD). To confirm the efficiency of the proposed control systems, a simulation was carried out, and the results showed that the designed STFPID controller achieves the best performance of the AVR system, and gives the preferable tracking low rise time, lower overshoot, least stetting time, minimal steady state error, and gives the ideal response against PID and fuzzy logic technology.