Power Control Scheme Research Articles

A New Thermal Management Strategy of IGBT in DFIG for Economic Benefit Maximization

Wind speed fluctuation generally shortens the lifetime of the insulated gate bipolar transistor (IGBT) module in the doubly fed induction generator (DFIG), which leads to frequent component replacement and cost increase of wind power generation. Conventional power control strategies consider solely the wind turbine output power maximization, and existing junction temperature thermal management strategies focus on IGBT lifetime extension, both of which are not effective under turbulent wind speed conditions and ignore the trade-off between the device reliability and output power for the overall DFIG economic benefit. To bridge the gap between the IGBT reliability and the output power under turbulent wind speed conditions, we propose a novel IGBT thermal management strategy for optimal economic benefit. Specifically, we first smooth the output power through a linear power control (LPC) method with conditions on the wind speed and turbine speed to reduce the IGBT low-frequency junction temperature fluctuation, which extends IGBT lifetime. We then propose a grid encirclement and suppression search (GESS) method that maximizes the economic benefit defined by LPC-smoothed output power and IGBT lifetime. Simulation shows that our proposed LPC-GESS strategy outperforms a competing strategy at economic benefit by a large margin, up to 15.3%. Our proposed strategy can potentially be used in wind power stations for fast and reliable economic benefit-oriented IGBT thermal management.

Power Control Strategies During Voltage Sags According to Spanish Grid Code

In order to connect any power converters into the grid there are some grid requirements to insure the safe operation of the grid. So, the control of the converters especially during abnormal condition-e.g. during voltage sags- is a very important key to guarantee the good behavior of the distributed generation system. In this paper four control strategies,will be stated in the literature, are discussed in order to ensure their ability to match the grid requirements when unsymmetrical voltage sags are produced in the network. The Spanish grid code did not give any information about the negative sequence, and it only represents the positive sequence components. Therefore, the main contribution of this paper is to verify the grid code with not only the positive sequence but also with the negative sequence. Moreover, the system is tested by simulation to show that the results cope well with the analytical equations.

CUSUM based Fault Detection of Stator Winding Short Circuits in Doubly-Fed Induction Generator based Wind Energy Conversion Systems

This paper investigates the detection of short-circuit faults in the stator winding of a Wind Energy Conversion System (WECS) based on a Doubly-Fed Induction Generator (DFIG). The Cumulative Sum (CUSUM) algorithm is used to detect the change in the stator negative-sequence current magnitude which is used as the fault residual. The grid voltage unbalance is considered along with the fault position and its severity to evaluate the effect on the residual. The generator is modeled using the winding-function approach. Simulation results are presented for a 15 kW system operated, under a power control strategy, at rated conditions. It is shown that the fault-detection method is able to detect the fault rapidly and is not influenced by the grid voltage unbalance within normal limits.

A Direct Power Controller for Doubly-Fed Induction Generator

This paper proposes a direct power control scheme for doubly-fed induction generator for variable speed wind power generation. Using a stator flux decoupling and deadbeat control loops the algorithm calculates the rotor voltage vector to be supplied to the rotor in order to eliminate the active and reactive power errors that can achieve high accuracy and fast dynamic power response based on the estimated stator flux, the active and reactive power and their errors. Simulations results are carried out for validation of the digital controller operation.

A novel power control scheme for distributed DFIG based on cooperation of hybrid energy storage system and grid-side converter

Due to the uncertainty of wind energy, the wind power is difficult to be dispatched and may cause the voltage fluctuations for distributed network. Therefore, a novel power control scheme is proposed to manage the output power of the distributed doubly-fed induction generator (DFIG) by cooperating the hybrid energy storage system (HESS). In the proposed scheme, the grid-side converter of DFIG is controlled to manage overall output power of the DFIG/HESS hybrid system in accordance to the power dispatching command. The HESS is utilized to deal with the power difference between DFIG generation power and the power dispatching command. The HESS is embedded in the DC-link bus of DFIG and is composed of superconducting magnetic energy storage and batteries. Additionally, in order to avoid HESS from overcharging and over-discharging, the pitch angle control and power dispatching command are adjusted by considering the state of charge (SOC) of HESS. Finally, the simulation model of distributed DFIG and HESS is built on the real-time digital simulation (RTDS) platform, and the simulation results validate the effectiveness and reliability of the proposed power control scheme.

Centralized control of a Wave Energy Farm

As long as an increased number of Wave Energy Converters are reaching their prototypal and pre-commercial stage it is fundamental to analyse in detail the issues arising from the grid integration of such devices. Point absorbers are among the most promising Wave Energy Converters. In this paper a point absorbers wave farm, connected to a weak grid, is simulated in order to evaluate how active and reactive power control strategies can help to fulfil the grid codes and to improve the behaviour of the farm as well as the efficiency of the internal grid. The real test case offered by bimep is used to model the internal grid of the farm. Different farm level control strategies, centralized and decentralized, are considered and compared. Both steady-state and dynamic analyses are carried out in order to assess the performance of the farm under its nominal operation and also to underline the detrimental effect of the energy source intermittency. Fault analyses are performed to evaluate the effect of voltage dips on the system operation.

A Mathematical Model for Dynamic Electric Vehicles: Analysis and Optimization

In this article, we introduce a flexible and reliable technique to simulate and optimize the characteristics of a Dynamic Electrical Vehicle (DEV). The DEV model is a discrete event-based modeling technique used in electrical vehicle research to improve the effectiveness and performance of various electrical vehicles (EVs) components. Here, the DEVS model is applied to EV research in several ways, including battery management optimization, evaluation of power train design and control strategy, and driver behavior analysis. The essential power train elements, including the battery, motor, generator, internal combustion engine, and power electronics are included in the mathematical model for the dynamic electric vehicle. The model is derived using the conservation of energy principle. The model includes mathematical equations for the electrical power output, battery charge level, motor torque, motor power output, generator power output, internal combustion engine torque, mechanical power delivered to the generator, and the efficiencies of the power electronics, motor, generator, and engine. The model is examined by using a numerical method called the Runge–Kutta Method of order 4 for dynamic electric vehicle’s performance under various driving states for maximum effectiveness and performance. It is revealed that the DEV model provides a systematic method to simulate and optimize the behavior of complex EV systems.

Optimizing V2X Communication: Spectrum Resource Allocation and Power Control Strategies for Next-Generation Wireless Technologies

The upcoming wireless technology developments in the next generations are expected to substantially transform the vehicle-to-everything (V2X) communication network. The challenge of limited spectrum resources in V2X communication, caused by the need for high data rates, necessitates a thorough analysis of spectrum resource allocation and power control. This complex problem falls under the domain of mixed-integer nonlinear programming; a strategic approach is implemented to overcome these issues, which divides the main challenge into two sub-problems. The issue of resource allocation is addressed by implementing a multiaccess spectrum allocation method, which is deliberately designed to optimize the utilization of the spectrum resources that are currently accessible. Concurrently, the power control issue is resolved by employing a continuous convex approximation technique, which effectively converts non-convex power-allocation issues into convex equivalents. This approach helps to alleviate interference between users. Finally, the simulation results prove that the proposed approaches can improve vehicle performance. The algorithms proposed in this article significantly improve the system throughput and access rate of vehicular user equipment (VUEs) while ensuring the data rate of cellular user equipment (CUEs).

Design of control strategy for reactor power control system of LBE cooled Actinide Burner Reactor (ABR) using system analysis code NUSOL-LMR

The power control strategy for the Lead–Bismuth Eutectic (LBE) cooled Actinide Burner Reactor (ABR) has been designed to assess the closed-loop performance of newly developed control blocks that were not modeled in the NUSOL-LMR code before this research effort. After establishing a sustainable model of ABR in NUSOL-LMR, validation of the model in light of the already-published research is performed. The said closed-loop control strategy (consisting of the power and temperature control blocks) is evaluated under different transient scenarios (reactivity insertion, primary coolant pump fault, and change in demand power levels). The power and temperature control blocks concurrently control reactor power during any transient occurrence. The coupling effect of the primary coolant temperature deviation on the reactor power has been minimized by the proportional and integral (PI) controller in the temperature control block. The simulation results demonstrate that the closed-loop performance of the ABR under the controller action during transient events is quite satisfactory. The closed-loop power regulation performance of the conventional sliding mode controller (SMC) with a PI sliding surface (PISM) in the power control block of NUSOL-LMR is better than that of a simple proportional, integral and derivative (PID) controller. The asymptotic stability of the closed-loop system with the PISM controller has been ensured using the Lyapunov stability theory.

Bidirectional PWM Converter to Interface AC Part to DC Microgrid with Neutral Potential Balancing

This research presents a description of a bidirectional pulse width modulated converter that functions as a rectifier by using the direct power control strategy and space vector modulation technology. In contrast to the voltage-oriented control strategy, this method minimises the number of internal current loops and requires more tuning. While functioning as an inverter, it applies the space vector modulation technique as well. The approach, on the other hand, is not the same as rectifiers since it calculates the duty ratio of the neighbouring voltage vectors in each small triangle that is generated in each sector that has a period of 60 degrees. In both situations, the neutral point potential has been brought back into equilibrium.

An efficient power control strategy for active mitigation of blade in‐plane fatigue loading in PMSG‐based wind turbines

AbstractThis paper assesses the dynamic performance of permanent magnet synchronous generator‐based wind turbine (WT) regarding the blade in‐plane fatigue loads once the WT is controlled in power control mode. Blade in‐plane oscillations, associated with the poorly blade in‐plane modes, can be excited by turbulent winds or grid disturbances that may lead to damage of the blades and reduce the drive‐train reliability. To overcome this drawback, at first, a model with three degrees of freedom is extracted for the drive‐train system, and then, an active mitigation approach is proposed to mitigate the blade in‐plane oscillations. The proposed method can effectively suppress the blade in‐plane vibrations by adding a supplementary term into the power control loop that is proportional to the speed difference between the blade and generator. The speed difference between the blade and generator is obtained by estimation of the blade‐hub and hub‐generator shaft torsional torques. Next, the performance of the proposed active mitigation approach is examined by the modal and frequency response analyses and time‐domain simulations. Finally, it is shown that the proposed approach has superior performance over the conventional approaches based on the simplified drive‐train model and crossing the measured generator speed through a band‐pass filter.

Asynchronous distributed optimal power control for fatigue load minimization in wind farms

An asynchronous distributed optimal power control (OPC) scheme is proposed to minimize fatigue load in the wind farms (WFs) in this paper. To better satisfy the grid code, each wind turbine (WT) in the scheme is equipped with an energy storage system (ESS) at the DC link of the WT converter. Based on the WT topology, a WT-ESS control model is established, thus developing an OPC scheme to control the generator torque, pitch angle, and ESS output simultaneously for reducing fatigue load. By formulating the model predicted control (MPC)-based optimal problems, the virtual mechanical power control is proposed to regulate the ESSs output for clarifying the power interactions among WTs and ESSs. In order to achieve more effective control of the above three parameters among multiple WTs-ESSs, an asynchronous distributed alternating direction method of multipliers (AD-ADMM) is developed to simultaneously minimize the variations of thrust force, shaft torque, and flapping moment load of the WTs in a wider range. Considering the impact of communication delays, the proposed AD-ADMM algorithm has the higher time efficiency and system robustness. The convergence of the proposed AD-ADMM algorithm is analyzed, and several cases are used to validate the performance of the OPC scheme.© 2017 Elsevier Inc. All rights reserved.

A new power management strategy for PV-FC-based autonomous DC microgrid

Solar energy is widely available in nature and electricity can be easily extracted using solar PV cells. A fuel cell being reliable and environment friendly becomes a good choice for the backup so as to compensate for continuously varying solar irradiation. This paper presents simple control schemes for power management of the DC microgrid consisting of PV modules and fuel cell as energy sources and a hydrogen electrolyzer system for storing the excess power generated. The supercapacitor bank is used as a short term energy storage device for providing the energy buffer whenever sudden fluctuations occur in the input power and the load demand. A new power control strategy is developed for a hydrogen storage system. The performance of the system is assessed with and without the supercapacitor bank and the results are compared. A comparative study of the voltage regulation of the microgrid is presented with the controller of the supercapacitor bank, realized using a traditional PI controller and an intelligent fuzzy logic controller.

HVDC auxiliary emergency power control strategy for power disturbance in two different positions of AC/DC interconnection system

HVDC auxiliary emergency power control strategy for power disturbance in two different positions of AC/DC interconnection system

Augmented dynamics of nonlinear systems: A review

We discuss a simple yet powerful control technique called “Linear Augmentation” (LA) for nonlinear dynamical systems. The linear augmentation can be perceived as a type of interaction that may occur naturally in dynamical systems as an environmental effect, or can be explicitly added to a system in order to control its collective dynamical behavior. LA has been known to effectively regulate resulting dynamics of various dynamical systems and can be used as a powerful control strategy in various applications. Examples include targeting attractor(s), regulating multistable dynamics, suppression of extreme events, and controlling chimera states in the nonlinear dynamical systems.

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.

Metaheuristics-Based Uplink Power Control Scheme for User-Centric Cell-Free Massive MIMO Systems

Metaheuristics-Based Uplink Power Control Scheme for User-Centric Cell-Free Massive MIMO Systems

Transient Angle and Voltage Stability of Grid-Forming Converters with Typical Reactive Power Control Schemes

Transient Angle and Voltage Stability of Grid-Forming Converters with Typical Reactive Power Control Schemes

Real-time MPC with Control Barrier Functions for Autonomous Driving using Safety Enhanced Collocation

The autonomous driving industry is continuously dealing with safety-critical scenarios, and nonlinear model predictive control (NMPC) is a powerful control strategy for handling such situations. However, standard safety constraints are not scalable and require a long NMPC horizon. Moreover, the adoption of NMPC in the automotive industry is limited by the heavy computation of numerical optimization routines. To address those issues, this paper presents a real-time capable NMPC for automated driving in urban environments, using control barrier functions (CBFs). Furthermore, the designed NMPC is based on a novel collocation transcription approach, named RESAFE/COL, that allows to reduce the number of optimization variables while still guaranteeing the continuous time (nonlinear) inequality constraints satisfaction, through regional convex hull approximation. RESAFE/COL is proven to be 5 times faster than multiple shooting and more tractable for embedded hardware without a decrease in the performance, nor accuracy and safety of the numerical solution. We validate our NMPC-CBF with RESAFE/COL on digital twins of the vehicle and the urban environment and show the safe controller's ability to improve crash avoidance by 91%. Supplementary visual material can be found at https://youtu.be/_EnbfYwljp4.

Power Control Strategy Optimization to Improve Energy Efficiency of the Hybrid Electric Propulsion Ship

Power Control Strategy Optimization to Improve Energy Efficiency of the Hybrid Electric Propulsion Ship