Active Power Control Strategy Research Articles

Enhancing power quality in contemporary utility systems: A comprehensive analysis of active power filters and control strategies

In contemporary power distribution systems, a substantial proportion of the loads not only utilize active power but also extract reactive power and harmonic currents from the AC source. The increased extraction of power components is a result of the widespread usage of fast-switching devices in utility systems. These devices contribute to an escalation in harmonic issues and problems related to reactive power. Furthermore, power quality disturbances have a range of negative repercussions on the utility system, impacting its overall performance and reliability.In order to address these difficulties and enhance the quality of electricity, Active electricity Filters (APFs) have been created and refined throughout the years. These filters are specifically engineered to identify sudden shifts in the reference current and counterbalance the harmonic currents produced by the voltage source inverter (VSI). The efficacy of these filters mostly relies on the selected current control procedures, which are essential for attaining adequate performance levels.This study provides a comprehensive examination of control mechanisms designed to improve power quality (PQ) in utility systems. Additionally, it examines the choice of filter components, taking into account both technical and economic factors. The paper explores the factors involved in selecting filters that are customized for individual applications, in order to achieve the best possible performance and cost efficiency.Based on an extensive analysis of more than 200 research publications, this study presents unique insights and discussions on the topic, providing readers with a full grasp of the difficulties and remedies associated with enhancing power quality in modern power distribution networks.

Hierarchical Coordinated Control Strategy for Active Power in Distribution Networks with Scaled Distributed Generation Access

Promoting scaled distributed wind turbines and photovoltaic, and other distributed generations access to the distribution network is an important measure for realize the goal of carbon peaking and carbon neutrality and to build new-type power systems. However, as the installed capacity of wind turbine, photovoltaic and other intermittent renewable energy sources climbs dramatically, the security and consumption problems of the distribution network are becoming increasingly prominent, and there is an urgent requirement to improve the active power control capability of distributed generation. To optimize the operation stability and consumption economy of the distribution network, a hierarchical coordinated control strategy for active power of scaled distributed generation is proposed based on the principle of unified control and hierarchical management, including peaking control, frequency control, mesh control and market trading control, to coordinate and optimize the system operation safety and consumption economy. The proposed strategy optimizes active power control instructions in the layer of distribution network layer, mesh layer, and functional area layer, thus fully expanding the depth and breadth of the consumption for distributed generation. The effectiveness of the proposed strategy is proved by the actual operation of Liaoning power grid.

Inverter PQ Control With Trajectory Tracking Capability for Microgrids Based on Physics-Informed Reinforcement Learning

The increasing penetration of inverter-based resources (IBRs) calls for an advanced active and reactive power (PQ) control strategy in microgrids. To enhance the controllability and flexibility of the IBRs, this paper proposed an adaptive PQ control method with trajectory tracking capability, combining model-based analysis, physics-informed reinforcement learning (RL), and power hardware-in-the-loop (HIL) experiments. First, model-based analysis proves that there exists an adaptive proportional-integral controller with time-varying gains that can ensure any exponential PQ output trajectory of IBRs. These gains consist of a constant factor and an exponentially decaying factor, which are then obtained using a model-free deep reinforcement learning approach known as the twin delayed deeper deterministic policy gradient. With the model-based derivation, the learning space of the RL agent is narrowed down from a function space to a real space, which reduces the training complexity significantly. Finally, the proposed method is verified through numerical simulation in MATLAB-Simulink and power HIL experiments in the CURENT center.With the physics-informed learning method, exponential response time constants can be freely assigned to IBRs, and they can follow any predefined trajectory without complicated gain tuning.

Generalized Predictive Control of the Active and Reactive Stator Powers of the DFIG for Wind Energy Generation

This paper proposes a Generalized Predictive Control (GPC) strategy for Wind Power Generation (WPG) based on a doubly fed induction generator (DFIG). The objective is to study and apply a robust active and reactive power control strategy based on GPC of the DFIG, this is likely to optimize the energy production and improve the quality of the energy produced. In order to maximize the amount of WPG taken even when the turbine is uncertain or the wind speed varies abruptly, the design is built utilizing the Maximum Power Point Tracking (MPPT) theory. Through numerical modeling with the aid of the Matlab/Simulink software, the predictive control (GPC) of the active and reactive stator powers of the DFIG was validated. A comparison between the GPC of the GADA and the indirect method based on a typical PI controller is developed in order to illustrate the viability of the suggested method. According to the simulation results of this comparison, the suggested method is viable and has promising results.

Adaptive active and reactive power control strategy for virtual synchronous generator

SummaryWith the increase in the penetration level of renewables into the grid, the virtual synchronous generator (VSG) concept has emerged as an attractive solution for controlling grid‐tied inverters. The variation in reactive power also affects the real power of the system as well. To address the voltage variations and phase angle variations occurring because of the energy storage elements, the control of the reactive power loop (RPL) is important. Also, it is used to maintain voltage regulation and improve the power factor of the VSG system. This paper focuses on the damping of oscillations occurring because of load variation by proper adjustment of the rotational inertia, damping coefficient, droop coefficient, and regulatory coefficient of reactive power with a proposed adaptive control strategy. Small‐signal analysis of the active and reactive power and point of common coupling (PCC) have been derived, and the detailed dynamic performances are analyzed. The influences of parameters perturbation on PCC voltage and reactive power were investigated. Furthermore, adaptive control includes optimizing dynamic indexes such as rise time, delay time, and response settling time. Finally, the performance and improvement in the results of VSG with and without adaptive control are compared.

Active disturbance rejection control and multi-objective optimization for wind turbine active power regulation

Wind energy is anticipated to become a backbone of the future energy system and provide active power ancillary services. In this paper, a novel active power control (APC) scheme is proposed to deal with the active power regulation problem for the wind turbine. Firstly, an APC strategy dual-activating the pitch action and the rotor kinetic energy is designed to specify the reference signals of pitch angle and rotor speed. Next, a multi-variable controller based on active disturbance rejection control (ADRC) theory is proposed to implement the APC strategy, wherein the theoretical proof of the convergence result is provided. Then, a multi-objective coronavirus herd immunity optimization algorithm is proposed to find out the Pareto solution of controller parameter tuning, in which the power tracking accuracy and fatigue load mitigation are considered. Finally, the performance superiority of the proposed APC strategy is verified on a 5 MW OpenFAST wind turbine simulator in case of the IEC turbulence wind field and the reg-D standard test signal into account. Compared with the conventional pitch angle control and rotor speed control strategies, our APC scheme is able to accomplish the task of power regulation with smaller tracking root mean square error, shorter pitch travel and lighter fatigue load.

A Unified Active Frequency Regulating and Maximum Power Point Tracking Strategy for Photovoltaic Sources

In order to optimize the extraction of solar energy, photovoltaic sources are commonly operated under the control of the so-called maximum power point (MPPT) strategy. However, as the rate of PV installations increases explosively, traditional MPPT algorithms may cause problems such as frequency deviation and power fluctuations, making system frequency stability a challenge due to the inherent intermittent and stochastic nature of PVs. Consequently, in order to reduce the investment and maintenance costs of storage systems, innovative control is expected for PV sources to provide ancillary services for the system, especially for weak systems such as microgrids. In this paper, a novel active power control (APC) strategy, based on characteristic curve fitting, is proposed to flexibly regulate the PV output power. The transient process performance and robustness of the system are improved with the proposed APC strategy. In conjunction, an f–P droop mechanism is designed to provide a frequency regulating (FR) service for the AC microgrid. The comprehensive control strategy unifies the FR function with the traditional MPPT function in a single control structure, allowing the PV source to operate either in the MPPT mode when the system frequency is nominal or in FR mode when the frequency exceeds it. The transition between MPPT and FR is autonomous and fully decentralized, which improves the PV generation efficiency as well as ensuring generation fairness among different parallel PV sources. Importantly, the proposed control strategy does not require any internal bundled energy within the PV generation system to achieve FR capability, but it effectively collaborates with the system-level energy storage system, thus reducing the necessary battery capacity. A detailed dynamic model of a PV generation system is constructed to validate the feasibility and effectiveness of the proposed control strategy.

Exploiting Photovoltaic Sources to Regulate Bus Voltage for DC Microgrids

DC microgrids are highly compatible with photovoltaic (PV) generation because of their direct-current properties. However, with the increasing integration of PV sources into DC microgrids, traditional maximum power point tracking (MPPT) algorithms may cause problems such as overvoltage and power fluctuation, which makes it challenging to keep the stability of the DC-bus voltage due to the intermittent and stochastic nature of PVs. Consequently, in order to reduce the investment and maintenance costs of storage systems, innovative control methods are required for PVs to provide DC-bus voltage regulation services. In this paper, a novel active power control (APC) strategy, based on characteristic curve fitting, is proposed to flexibly regulate the PV output power. The transient process performance and robustness of the system are improved with the proposed APC strategy. Based on it, a V-P droop mechanism is designed to provide voltage regulating (DVR) service for the DC microgrid. The overall control strategy unifies the DVR function with the traditional MPPT function in the same control structure; thus, the PV source either works in the MPPT mode if the DC-bus is at its nominal value, or it works in the DVR mode if the DC-bus exceeds it. Switching between MPPT and DVR is autonomous, and it is fully decentralized, which improves the PV generation efficiency as well as ensures generation fairness among different parallel PV sources. Case studies including a real-world project analysis are carried out to validate the feasibility and effectiveness of the proposed strategy.

Active power control strategy based on characteristic curve fitting for photovoltaic sources

AbstractWith the explosive growth of photovoltaic (PV) penetration, there is an increasingly urgent expectation for PV sources to provide a full range of ancillary services to the utility. The most critical issue for a PV source to support the power system is the flexible power regulating capability, whereas the PV sources generally operates in the maximum power point tracking (MPPT) mode to maximize the solar harvest. This paper proposes an active power control strategy for PV sources based on a characteristic curve fitting method. With the proposed control strategy, PV sources can operate in the MPPT mode or adaptively switch to the power dispatch mode to flexibly regulate its output power to track the power reference. The characteristic curve fitting method does not require an irradiation sensor, but it has a more stable performance under rapid and continuous change in irradiation with simple calculation and error control since its extremely high similarity with the P–U characteristics of the PV source. Simulation is performed based on a detailed PV dynamic model to validate the proposed control strategy.

Fault Ride-Through for PMVG-Based Wind Turbine System Using Coordinated Active and Reactive Power Control Strategy

This study investigates a fault ride-through capability for grid-connected permanent magnet vernier generator (PMVG)-based wind turbine system (WTS) using coordinated active and reactive power control strategy. To do this, the generator peak current and speed limitation schemes are proposed for the machine-side converter to satisfy grid code requirements during grid fault conditions. At the same time, the reactive power control is implemented on the grid-side converter to meet the reactive current requirement of the grid code. And then, to suppress the DC-link power unbalance during grid fault conditions, an efficient variable exponential reaching law-based sliding mode control is designed. Further, the coordinated control schemes are employed to ensure the stable DC-link voltage and maintain the converter's maximum peak current during grid faults. Finally, the proposed control methods demonstrate their superiority through simulations on 5-kW PMVG, 1.5 MW PMSG-based WTS, and its application potential is shown through the experimental prototype of a 5-kW PMVG-based WTS.

Analysis of single-phase cascaded H-bridge multilevel inverters under variable power conditions

Easy modular I action is one of the benefits of a cascaded H-bridge (CHB) inverter. This study proposes an only one multilevel inverter comes with a unique H-bridge unit. The structure of the proposed topology is then enhanced in order to make use of switching devices and DC-link voltage inputs while creating a massive number of voltage steps. A cooperative active and reactive power control strategy is offered to earn a better real and reactive power management for every DC voltage source of a photovoltaic (PV) module, as well as boost systems power quality and reliability. A unique control approach and proportional pulse width modulation (PWM) modulation are described for the cascaded H-bridge multilevel inverters for grid-connected systems. Each Hbridge module can give different power levels thanks to this control. To supply the DC source, use the system's proportional, integral and derivative (PID) controller. The functionality and achievements of the proposed scheme with its associated algorithms in production of all operating voltage have been proven using experimental data from a nine-level single-phase inverter. Finally, to construct a cascaded H-bridge nine-level inverter, the proposed control strategy is developed and implemented in MATLAB software.

Coordinated active and reactive power management for enhancing PV hosting capacity in distribution networks

AbstractThis paper proposes an operational planning model based on optimal active and reactive power control strategies to enhance solar photovoltaics (PV)’ hosting capacity in distribution networks. Reactive power control is carried out through optimum static VAr compensators (SVCs) placement, while active power control is performed through flexible loads, particularly shiftable and interruptible loads. The first stage of the proposed two‐stage stochastic model assigns decision‐making regarding calculating PV hosting capacity at different nodes, in addition to the allocation and capacity of SVCs. In the second stage, the first stage decisions are assessed to ensure the power flow constraints under various uncertainties such as daily load and stochastic PV generation. The presented model is investigated through numerical analyses on modified IEEE 15‐bus and IEEE 33‐bus distribution systems considering different active‐reactive strategy cases. While most previous works only rely on one type of active or reactive power control strategy, this study investigates the challenges of the respective application of active and reactive power control in various modes of fundamental practices. The obtained results prove the superiority of the proposed hybrid active‐reactive control strategy for enhancing PV hosting capacity compared to respective active or reactive power controls.

Seamless Fault-Tolerant Control for Cascaded H-bridge Converters Based Battery Energy Storage System

This article presents a phase-shifted pulsewidth-modulation-based fault-tolerant approach for the cascaded H-bridge-based battery energy storage system to ride through the single switch fault. When the fault occurs, the faulty cell is bypassed first. Afterwards, the missing voltage levels of the faulty cell are compensated by the remaining healthy cells to maintain the line-to-line voltages balanced. The compensation of the missing voltage levels presented is achieved by simple logic operation without modifying three-phase voltage references and phase-shifted angles of carriers, which enables seamless operation and enhances the system stability. In addition, the detailed active power control strategy used for state-of-charge balancing of the battery units is proposed and discussed. The validity and effectiveness of the proposed method are verified by simulation and experimental results.

Active power control strategy of DFIGs in flexible interconnected distribution network

In the development of new-type power system, the flexible interconnected distribution network becomes a better inclination. With the continuous increase of wind power generation in the flexible interconnected distribution network, the frequency stability issue caused by the high randomness of wind power generation has become increasingly prominent. This paper suggests an advanced active power strategy of double-fed induction generators (DFIGs) based on modifying power tracking curves in the interconnected distribution network for smoothing out the fluctuations of the system frequency. To this end, the various power tracking operation is used to participate in power smoothing instead of maximum power tracking operation so as to fully utilize the large rotor inertia of the double-fed induction generators for smoothing out the fluctuations of the power output of double-fed induction generators and system frequency. The control gain for the various power tracking operation is determined by the instantaneous system frequency deviation and rotor speed of the DFIG. Based on the modified IEEE 14 power system, simulation results successfully proved that the suggested advanced active power strategy is benefit for reducing the fluctuations of the output power of the DFIG and suppressing the maximum system frequency deviations with the scenario of continuously varying wind speed conditions.

Decoupling active power control scheme of doubly-fed induction generator for providing virtual inertial response

Virtual inertial control (VIC) is implemented in the controller of doubly-fed induction generators (DFIGs) to compensate for the reduction in capability of the frequency regulation. However, the conventional VIC might give negative impacts on improve the frequency nadir due to the coupling power dynamics between the variation of the power references of the maximum power tracking operation (MPTO) and VIC. In addition, when regaining the rotor speed, a double frequency drop (DFD) trends to produce due to the sudden output drop. This paper suggests a decoupling active power control scheme of a wind power plant to improve the frequency nadir and minimize the DFD. To improve the frequency nadir, the proposed VIC suggests various operating power tracking operations to improve the frequency nadir. The variable-coefficient-PI-control based rotor speed recovery strategy (RSRS) is suggested to minimize the DFD and automatically switches to the MPTO. Test results demonstrate that the suggested decoupling active power control scheme with proposed RSRS and VIC strategy can minimize the DFD and reduce mechanical stresses on the wind turbine while enhancing the frequency nadir.

Optimal Control of a Single-Stage Modular PV-Grid-Driven System Using a Gradient Optimization Algorithm

There are many studies that focus on extracting harmonics from both DC and AC sides of grid-interfaced photovoltaic (PV) systems. Based on these studies, the paper introduces an efficient method depending on hybrid DC voltage, and an active and reactive power (DC-V PQ) control scheme in a single-stage three-phase grid-interfaced PV system. The proposed scheme is designed to regulate DC voltage to minimize power loss and energy share between the network reconfiguration and the utility grid. Moreover, the technique is more effective at dealing with uncertainty and has higher reliability under various operating scenarios. These operations are the insertion of linear load 1, nonlinear load, and linear load 2. Moreover, a novel objective function (OF) is developed to improve the dynamic response of the system. OF is coupled with a particle swarm optimization (PSO) algorithm and a gradient optimization (GBO) algorithm. The analysis and the comparative study prove the superiority of GBO with counterfeits algorithm.

Active Power Control Integrated With Reactive Power Compensation of Battery Energy Stored Quasi-Z Source Inverter PV Power System Operating in VSG Mode

The battery energy stored quasi-Z source inverter (BES-qZSI)-based photovoltaic (PV) power system combines the advantages of the qZSI and energy storage system. However, as the BES-qZSI is a fast-response power converter without any inertia, when applied as a grid-connected system, it leads to decreased power system inertia. The low inertia problem will degrade the system’s performance and affect the system’s stability. Moreover, the BES-qZSI PV power system usually employs a phase-locked loop and PR regulator to control the grid current to track the desired reference in phase with the grid voltage. These do not reflect the characteristics of frequency modulation and voltage regulation. To enhance the system’s frequency and voltage self-adjustment ability, a control strategy based on the virtual synchronous generator (VSG) technique for the BES-qZSI PV power system is proposed in this article. By introducing the concept of synchronous generator, the BES-qZSI PV power system has the characteristics of the heavy moment of inertia, droop frequency active, droop characteristic of voltage–reactive power, and so on. Then, an active power control strategy integrated with reactive power compensation is proposed to implement PV generation and reactive power compensation at the same time. The simulation and experimental results verify the proposed control strategy.

Steps towards Decarbonization of an Offshore Microgrid: Including Renewable, Enhancing Storage and Eliminating Need of Dump Load

A novel control strategy to manage the integration of a wind turbine (WT) and an energy storage unit to an existing stand-alone microgrid servicing an oil and gas (O&G) rig is the topic of this paper. The control strategy includes a primary and a secondary controller that, using the battery in tandem with the WT, does not require any dump load (A). The secondary controller includes an energy management system (EMS) which uses the estimated wind production and other specific local information to size the battery to avoid the curtailment of the WT (B) and simultaneously provide the framework for the economic analysis (C). Points A, B and C are the main novelties introduced with this work. Additionally, a primary controller operates the original microgrid source, a gas turbine (GT), at its maximum efficiency through an active power control strategy to lower fuel consumption, by prioritizing the exploitation of the renewable energy source through the combination EMS and battery sizing. The microgrid is simulated and the combined controller of the battery and GT bench-tested.

Wind farm control for wake-loss compensation, thrust balancing and load-limiting of turbines

As renewable energy sources such as wind farms become dominant, new challenges emerge for operating and controlling them. Traditionally, wind farm control aims to dispatch power set-points to individual turbines to maximize energy extraction and, thus, their usage as assets. Yet, grid balance and frequency support are fundamental in presence of high renewable penetration and volatility of energy prices and demand. This requires a paradigm change, moving from power maximization to revenue maximization. In this paper, three active power control strategies pushing this shift of paradigm are investigated, namely: wake-loss compensation, thrust balancing, and load-limiting control.The findings of large eddy simulations of a reference wind farm show that wake-loss compensation indeed improves the power generation on waked wind farms, but at the price of increased structural loads on certain turbines. The addition of a thrust balancing can equalize the stresses of individual turbines and their wear in the long term, while still attaining the required power output at the farm level. Furthermore, load-limiting controllers could potentially aid by allowing maintenance to be scheduled in a single time window, thus reducing operation and maintenance costs.

An adaptive active power rolling dispatch strategy for high proportion of renewable energy based on distributed deep reinforcement learning

In this article, an adaptive active power rolling dispatch strategy based on distributed deep reinforcement learning is proposed to deal with the uncertainty of high-proportioned renewable energy. For each agent, by using recurrent neural network layers and graph attention layers in its network structure, we aim to improve the generalization ability of the multiple agents in active power flow control. Furthermore, a regional graph attention network algorithm, which can effectively help agents aggregate the regional information of their neighborhood, is proposed to improve the information capture ability of agents. We adopt the structure of ‘centralized training, distributed execution’ to help agents improve the effectiveness of proposed methods in dynamic environments. The case studies demonstrate that the proposed algorithm can help multi-agents learn effective active power control strategies. Each agent has a strong generalization ability in terms of time granularity and network topology. We expect that such an approach can improve the practicability and adaptability of distributed AI method on power system control issues.