Active Power Regulation Research Articles

Autonomous DC Line Power Flow Regulation Using Adaptive Droop Control in HVDC Grid

The regulation of active power flowing through one or multiple DC lines plays an important role to guarantee secure and economic operations of high voltage direct current (HVDC) grids. This paper proposes a new method to regulate DC line power flow based on the adaptive DC voltage droop control strategy in which the voltage references of the voltage droop controllers vary autonomously at post-contingencies. The main advantage of the proposed method is that it can avoid installation of extra equipment and thus the associated losses and costs in the power-converter-based power flow control methods. The proposed control approach does not require to solve online global AC-DC power flow equations, leading to autonomous control. Furthermore, the adaptive droop control does not influence the stability of the HVDC grid since only the droop voltage references vary, but not the droop coefficients. Static analysis and dynamic simulations of a five-terminal HVDC grid are implemented using MATLAB/Simulink Simscape Blockset and OPAL-RT RT-LAB libraries to validate the effectiveness of the proposed autonomous control method.

Active power dynamic interval control based on operation data mining for wind farms to improve regulation performance in AGC

With the real-time changes of wind speed and operating conditions, it is a challenge to fully tap the active power regulation ability and improve the control performance of automatic generation control (AGC) in a wind farm (WF). The essence of tapping the active power regulation ability is to realise the coordination and complementarity of each wind turbine's (WT's) dynamic adjustment performance (DAP). To address this, a novel data mining method is developed to derive the internal relations between WTs’ output power and pitch angle, impeller speed and pitch angle during the power adjustment process, and a unified mechanism model is established to describe DAP of WTs. Based on the discovered relationship between WTs’ DAP and its operating states, an active power distribution algorithm and a dynamic interval control method are proposed. Then, an active power dynamic interval control strategy that has been implemented using Java script in MyEclipse for WFs is further developed. The control strategy has been tested and applied in a 50 MW WF in northwest China. The preliminary results showed that the control strategy has improved the rapidity and accuracy of AGC in the WF.

Reducing the active power curtailment of distributed generation based on soft open points in unbalanced distribution networks

Voltage profiles may exceed the upper limit in a distribution network with a high penetration of distributed generation (DG). Voltage can be effectively regulated by curtailing the active power of DG and adjusting the reactive power. Soft open points (SOPs) have flexible active power transfer and reactive power regulation capabilities that can help reduce the active power curtailment of DG. Asymmetric network parameters, single-phase loads, and DGs cause voltage unbalance in distribution networks. This study proposes an optimal power control model of SOPs and DG converters in unbalanced distribution networks (UDNs). First, the individual phase power control characteristics of SOPs and DG converters in UDNs are modelled. Second, an optimisation model is constructed with the minimum active power curtailment of DG and the total power loss and voltage unbalance of UDNs as the objective function and with consideration of the networks and SOP operation constraints. The original optimisation model with non-convex and non-linear characteristics is transformed using power flow linearisation and linear relaxation into a linear programming model that can be efficiently solved. Finally, the feasibility and efficiency of the proposed model are verified using an IEEE 33-node system.

Data‐driven modeling for fatigue loads of large‐scale wind turbines under active power regulation

AbstractAdvanced control methods for coordinatively optimizing active power dispatch and fatigue load distribution of wind turbines (WTs) in mountain wind farms, require the fatigue load modeling that has not been fully studied. This study proposes a data‐driven modeling method for fatigue loads of large‐scale WT under active power regulation. Firstly, load simulations based on Monte Carlo approach are conducted to overcome the uncertainty of fatigue load caused by turbulent wind. Subsequently, the target components of WT are selected according to the fatigue load dataset distribution at various power setpoints and the sensitivity to active power. Specifically, the Jarque–Bera statistic is used to evaluate the distribution characteristics of datasets; the single‐value processing determines the valid value through the maximum probability of the Gaussian kernel density distribution of the dataset; the Morris screening is employed to select the valid value with high sensitivity to active power regulation. Afterwards, arbitrary polynomial chaos expansion and support vector regression are performed to establish the data model of fatigue loads, respectively. Finally, the proposed method is applied into a 1.5‐MW commercial WT model designed by the manufacturer through the Bladed software. The obtained data‐driven model establishes a basis of simultaneously optimizing active power dispatch and fatigue load distribution, making it possible to reduce energy cost in mountain wind farms.

Forecasting based energy management of flywheel energy storage system connected to a wind power plant

The active power output of a wind power system needs regulation due to the stochastic nature of wind speed. A flywheel energy storage system (FESS) is a viable option for active power regulation in a wind power plant. An efficient energy management system (EMS) for FESS is required for healthy operation of the overall connected system. A wind speed forecasting based EMS has been proposed in this paper. It utilizes the repeated wavelet transform based ARIMA model for very short-term wind speed forecasting, which has been proven to be better than the methods that exist in the literature. An artificial neural network based model is used to translate the forecasted wind speed to instantaneous wind power output. Considering the initial energy of FESS, an optimization technique has been used to calculate the speed command to be given to FESS for a given energy exchanged with the grid. The proposed control approach extends FESS usability as an energy exchange system for a period of large change in wind speed where the normal control approach saturates the FESS speed. The feasibility of the proposed EMS algorithm has been tested in MATLAB/Simulink.

A Power Hardware-in-the-Loop Based Method for FAPR Compliance Testing of the Wind Turbine Converters Control

A task for new power generation technologies, interfaced to the electrical grid by power electronic converters, is to stiffen the rate of change of frequency (RoCoF) at the initial few milliseconds (ms) after any variation of active power balance. This task is defined in this article as fast active power regulation (FAPR), a generic definition of the FAPR is also proposed in this study. Converters equipped with FAPR controls should be tested in laboratory conditions before employment in the actual power system. This paper presents a power hardware-in-the-loop (PHIL) based method for FAPR compliance testing of the wind turbine converter controls. The presented PHIL setup is a generic test setup for the testing of all kinds of control strategies of the grid-connected power electronic converters. Firstly, a generic PHIL testing methodology is presented. Later on, a combined droop- anFd derivative-based FAPR control has been implemented and tested on the proposed PHIL setup for FAPR compliance criteria of the wind turbine converters. The compliance criteria for the FAPR of the wind turbine converter controls have been framed based on the literature survey. Improvement in the RoCoF and and maximum underfrequency deviation (NADIR) has been observed if the wind turbine converter controls abide by the FAPR compliance criteria.

An IoT and Edge Computing Based Framework for Charge Scheduling and EV Selection in V2G Systems

The daily fluctuations in the power requirements and the regulation of voltage and frequency cause substantial energy dissipation. These lead to a reduction in the operational efficiency of the power grid. V2G (Vehicle 2 Grid) enabled electric vehicles (EVs) can act as a reactive power resource and can provide active power regulation, load matching, and current harmonic filtering. We propose a smart framework based on Internet of Things (IoT) and Edge computing to manage the V2G operations efficiently. The proposed framework can handle distributed energy sources, and can help in grid stabilization, increasing its reliability, and improving the power efficiency. V2G energy transfers can affect the EV's battery lifetime, however if carefully managed, they can be economical both for the grid operators, as well as the EV owners. The proposed framework creates an optimum charging schedule for each EV to maximize the profit of the EV owners, keeping the preferences set by the vehicle owner and the grid requirement in consideration.

Stator Current-Sensorless-Modulated Model Predictive Direct Power Control of a DFIM With Magnetizing Characteristic Identification

This article presents a direct power control method based on modulated model predictive control for a doubly fed induction machine. The modulated predictive control algorithm constructs an optimal voltage vector from two inverter states that give a minimum absolute error in the active and reactive power. This article focuses on the effects of magnetic saturation and its impact on the accuracy of computed reactive power when the stator current sensors are not installed. To reduce the impact of magnetic saturation on reactive power computation, the machine's magnetizing characteristic is identified through a self-commissioning scheme introduced in this article. The identified magnetizing curve is utilized to construct a full-state stator flux observer, which is used to accurately estimate stator currents that appear in the reactive power equation. Experimental results are presented to demonstrate the accuracy of the reactive power computation in the absence of stator current sensors while conserving the rapid transient response offered by a modulated predictive control strategy for active and reactive power regulation.

Research on frequency modulation control of photovoltaic power generation system based on VSG

Abstract In order to improve the friendliness of the grid connection of new energy power generation, the new energy photovoltaic (PV) unit is equivalent to a synchronous generator in the power system and a virtual synchronous generator (VSG)-controlled PV energy storage complementary grid-connected power generation system model is established and studied to analyze the VSG. When power is supplied to the load together with the power grid, the energy storage unit inside the VSG will release and store the electrical energy according to the fluctuation of the PV output, which plays the role of the adjustment of the prime mover; in the case of load power fluctuations, and power grid assume the corresponding active power regulation according to their capacity. The amount of active power adjustment to jointly and maintain the power balance inside the system under the condition of fluctuating load power. The overall system architecture and control strategy of PV grid-connected inverter based on VSG algorithm are proposed. The PV-VSG proposed here not only takes into account the maximum power point tracking control but also has independent participation in the power supply. A series of characteristics of synchronous generators, such as network frequency modulation voltage regulation and inertia damping, can effectively improve the new energy PV power generation system and promote the new energy consumption. The results of system simulation and field demonstration operation fully show the effectiveness and correctness of the proposed control strategy based on VSG algorithm.

Interleaved Totem-Pole ZVS Converter Operating in CCM for Single-Stage Bidirectional AC–DC Conversion With High-Frequency Isolation

In this article, a new bidirectional single-stage interleaved totem-pole electrolytic capacitorless ac-dc converter with high-frequency isolation and low components count is proposed. The proposed converter is constructed using nonregulating two-phase interleaved totem-pole converter switched with a fixed 50% duty on the grid side and a full-bridge on the dc-side for active power and dc output regulation. This switching method results in a ripple-free grid current regardless of the magnitude of the input inductances. Consequently, a proper design of input inductance secures soft switching for all switches under wide voltage and load ranges without an auxiliary circuit or resonant tank. Hence, the proposed topology overcomes the reverse recovery issue, thereby enabling the use of Si devices in CCM. Moreover, the current spike around the ac main zero-crossing is avoided in the CCM operation due to small rectified voltage around zero-crossing. Furthermore, the instantaneous powers at the grid side and dc-side are identical since the proposed topology is electrolytic capacitorless with inherent second harmonic ripple current at the dc-side. PFC is inherently performed in the proposed converter without a current shaping control loop, and the phase-shift angle is the only control variable. Hence, the control system is simple and reliable. A 3.3 kW prototype of the proposed converter is built and tested in order to verify the performance and the theoretical claims.

Classification and dynamic assessment of droop-based grid-forming control schemes: Application in HVDC systems

This paper introduces a novel classification for droop-based control strategies towards emerging interest of utilizing grid-forming control schemes in high voltage direct current (HVDC) systems. Classical droop control for grid-forming operation does not conventionally depend on a phase-locked loop (PLL). It is demonstrated that by including a PLL in droop control, it is possible to define two other droop-based control variants with different capabilities and functionalities. To highlight the differences in performance of each control scheme, the active power response of the power converter is evaluated in case of variation in grid short circuit ratio (SCR) as well as the PLL response time by considering an ideal DC bus. Accuracy in active power regulation, frequency support capability and virtual inertia emulation are the functionalities that have been addressed for the proposed three different control schemes. In a next step, the introduced droop-based grid-forming schemes are assessed by considering the dynamics of both AC and DC side of the power converter at one terminal of an HVDC link. Finally, based on the simulation results, a summary of features for all introduced grid-forming control schemes is presented11This work is supported by the project “HVDC Inertia Provision” (HVDC Pro), financed by the ENERGIX program of the Research Council of Norway (RCN) with project number 268053/E2, and the industry partners; Statnett, Statoil, RTE and ELIA..

A Dispatchable Droop Control Method for Distributed Generators in Islanded AC Microgrids

This article proposes a dispatchable droop control method for multiple distributed generators (DGs), which can be applied in islanded ac microgrids. The proposed method utilizes first-order inertia elements to achieve pseudo hierarchical control so that the DG can share the load automatically on a smaller time scale and obey the dispatch order on a larger time scale. On one hand, the proposed method contains active power regulation and frequency restoration control simultaneously. On the other hand, it has either the reactive power regulation control or the voltage control for different situations. The proposed method is still applicable even when the given power control references are infeasible. The effectiveness of the proposed method is verified by the corresponding simulation based on MATLAB/Simulink.

Predictive controller for interconnected microgrids

This research presents a robust model predictive controller of two microgrids (MGs) interconnected via tie-line (TL) power. Power system operations continue to face new challenges due to the large integration of renewable energy generation with an active load demand uncertainty and the management and control of bidirectional power flow between MGs and others uncertainties and system nonlinearities due to the power system operating condition. To handle these uncertainties and system nonlinearities a robust model using predictive control scheme is presented in this paper to achieve the control of the active power between two MGs when considering three disturbances scenario models. In the design process, uncertainties and nonlinearities of the system were taken into account and contributed to the robustness of the closed-loop system. Robust control scheme development considering power system nonlinearities and uncertainties were used to improve the online close-loop robustness. The model helped to achieve a desired active power regulation by coordinating the MGs and active power over-shoot and under-shoot time were reduced outstandingly. A Comparison was made between open-loop and close-loop simulation results, which indicate that the model can handle robustness while settling power deviation of the interconnected system. MATLAB environment was used to solve the optimisation problem.

Adaptability evaluation and active power regulation of FID in active distribution network

In this study, a two-layer model is established for evaluating the adaptability and regulating the active power to improve the economy and stability of a distribution network. A flexible interconnection device (FID) is used to provide flexible, fast, and accurate power conversion control in the active distribution network. It solves the power reverse problem due to photovoltaics (PV). The adaptability model is established in the planning layer to evaluate the revenue of the distribution network after access to FIDs in different numbers and positions with respect to the economy. The adaptive step-size search algorithm and FID active power transfer interval (which can be advantageous to the distribution network) are considered as the operation regions. Subsequently, the operation regions are transferred to the active power regulation model in the optimization layer via the sequential scan method to adjust the PV permeability and load ratio of the distribution network for stability. The elitist non-dominated sorting genetic algorithm is used to select the optimal position, number, and active power transfer values of the FID corresponding to the optimal PV permeability and load rate in the operation regions. Finally, the results of a realistic case study are provided and indicate that the proposed approach improves the economy and stability of the distribution network. The simulation results verify the effectiveness and feasibility of the proposed method.

Fully-Distributed Deloading Operation of DFIG-Based Wind Farm for Load Sharing

A system-level consensus-based deloading operation is proposed for DFIG-based wind farm (WF) participating in system active power regulation. Rotor overspeeding control (ROC) and pitch angle control (PAC) are coordinated for load sharing among each wind turbine (WT). For ROC, a novel fully-distributed consensus protocol is developed for fair load sharing control without the need to know the total active power capacity. Considering the influences of wind turbines’ individual differences and rotor speed limit, the amount of WTs involved in consensus protocol are dynamically adjusted according to their varying operating points. Further, a distributed optimization strategy is designed for active power setting-points allocation to curtail the utilization of WF's pitch angle during PAC. As the result, the proposed strategy can fully and quickly extract the available rotor overspeeding margin for a high kinetic energy storage and a better dynamic performance in ROC stage, and further minimize the dependency on pitch angle when facing deeper deloading operation. Case studies demonstrate the effectiveness of the proposed scheme.

Resilient Synchronization of Voltage/Frequency in AC Microgrids Under Deception Attacks

This article proposes a resilient distributed secondary voltage and frequency control scheme for autonomous ac microgrids considering disturbances and attacks on both sensors and actuators. To achieve the main objectives of the control system, first, a distributed state observer is employed to predict the normal behavior of state variables in the presence of potential deception attacks. Then, a distributed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H_\infty }$</tex-math></inline-formula> controller is utilized to mitigate the impacts of disturbances and uncertainties. Finally, to overcome the detrimental effects of attack signals, a resilient distributed adaptive algorithm is integrated with the designed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H_\infty }$</tex-math></inline-formula> controller. The proposed control algorithm has no restriction on the number of agents under attack and guarantees the boundedness of synchronization errors for all units. Also, in addition to distributed generation units, the contribution of distributed energy storage (DES) units in the regulation of voltage, frequency, and active power sharing is considered. Due to the limited energy of DESs, it is needed to balance the state of charge of these units. We evaluate the performance of the proposed algorithm using offline digital time-domain simulation studies carried out on a test microgrid system in MATLAB/Simulink environment, and the results are compared with previously reported methods. Simulation results and comparison with previous works reveal the effectiveness and accuracy of the proposed algorithm in regulating microgrid voltage and frequency.

A Model Predictive Control Strategy for Distribution Grids: Voltage and Frequency Regulation for Islanded Mode Operation

In the last few years, one of the most important challenges of power technologies has been the integration of traditional energy production systems and distributed energy resources. Large-scale photovoltaic systems and wind farms may decrease the quality of the electrical grid service, mainly due to voltage and frequency peaks and fluctuations. Besides, new functionalities, such as the operation in islanded mode of some portions of the medium-voltage grid, are more and more required. In this respect, a model predictive control for voltage and frequency regulation in interconnected local distribution systems is presented. In the proposed model, each local system represents a collection of intelligent buildings and microgrids with a large capacity in active and reactive power regulation. The related model formalization includes a linear approximation of the power flow equations, based on stochastic variables related to the electrical load and to the production from renewable sources. A model predictive control problem is formalized, and a closed-loop linear control law has been obtained. In the results section, the proposed approach has been tested on the Institute of Electrical and Electronics Engineers(IEEE) 5 bus system, considering multiple loads and renewable sources variations on each local system.

Voltage Control for Distribution Networks via Coordinated Regulation of Active and Reactive Power of DGs

Fast-acting reactive power support from distributed generations (DGs) is a promising approach for tackling rapid voltage fluctuations in distribution networks. However, the voltage regulation range via reactive power of DGs alone is narrow especially in distribution networks with high resistance-reactance ratio. In this paper, a randomized algorithm is proposed to improve the voltage profile in distribution networks via coordinated regulation of the active and reactive power of DGs. To this end, first the variables of the proposed quadratically constrained quadratic programming problem on voltage control are partitioned into disjoint subsets, each of which corresponds to a unique low-dimensional subproblem. Second, these subsets are updated serially in a randomized manner via solving their corresponding subproblems, which overcomes the requirement for system-wide coordination among participating agents and guarantees an optimal solution. Compared with the existing algorithms, the proposed algorithm is resilient to network reconfigurations and achieves a wider voltage regulation range. The effectiveness and convergence performance of the proposed algorithm is validated by the case studies.

An Improved Dynamic Voltage Restorer Model for Ensuring Fault Ride-Through Capability of DFIG-based Wind Turbine Systems

Renewable energy sources (RES) are being integrated to electrical grid to complement the conventional sources in meeting up with global electrical energy demand. Among the RES, Wind Energy Conversion Systems (WECS) have gained global electricity market competitiveness especially the Doubly Fed Induction Generator (DFIG)-based Wind Turbines (WTs) because of flexible regulation of active and reactive power, higher power quality, variable speed operation, four quadrant converter operation and better dynamic performance. Grid connected DFIG-based WTs are prone to disturbances due to faults in the network which made the utilization of the power generated a major concern. The grid code requirement for integrating the DFIGs to grid specified that they must remain connected and support the grid stability during grid disturbances of up to 1500milliseconds. The ability of the DFIG WT system to uphold to the grid codes requirement is termed the Fault Ride – Through (FRT). This paper presented a 1.5MW grid connected DFIG-based WT model with a Dynamic Voltage Restorer (DVR) for FRT capability enhancement. The design and simulation were performed in MATLAB/Simulink software. The test system was subjected to disturbances leading to Low Voltage Ride – Through (LVRT), Zero Voltage Ride – Through (ZVRT) and High Voltage Ride – Through (HVRT) considering three – phase balanced fault and single line to ground fault. The performance of improved model of DVR shows enhancement over conventional DVR in terms of voltage compensation and fault current mitigation.

Current control based on limit cycle stability for photovoltaic arrays

This study describes a current controller, based on a Lyapunov control law and a limit cycle oscillator (LCO) to provide stability into the grid-connected photovoltaic (PV) system during grid faults. The current controller also ensures an efficient current injection and active power regulation. The proposed controller offers a high degree of immunity and robustness against perturbation on the grid, due to the three-phase LCO – frequency locked loop (FLL) synchronisation technique. The LCO-FLL is used to compute the positive and negative sequence components of the grid, which are used by a Lyapunov control law in order to control the injected currents into the grid. Moreover, the inverter input voltage is considered in the controller design. The control configuration is proved by two different strategies, balanced injected currents and constant active power in the presence of an unbalanced grid voltage. Simulation and experimental test results are presented to demonstrate the proficiency and performance of the proposed technique in grid-connected PV systems.