Improved Frequency Control Research Articles

Research on Mathematical Model of Energy Storage Assisted Wind Turbine Frequency Regulation Control Strategy

Abstract This paper proposes an improved frequency regulation strategy for the Doubly-Fed Induction Generator (DFIG) to mitigate the impact of wind power integration on system frequency. An energy storage system is used on the wind side to participate in the frequency regulation. The influence of wind power integration on the power system frequency is analyzed and an improved frequency control strategy for the DFIG is proposed. A control strategy for energy storage devices to support wind turbine frequency control is proposed. An energy storage device model is established that considers power correction based on the state of charge to avoid excessive charging and discharging. According to the operating state of the DFIG, a control strategy for the frequency regulation of the energy storage device is proposed. According to different wind speeds, a control strategy is proposed for the participation of the joint wind storage system in the frequency regulation. This control strategy can provide frequency support to the system when the wind turbine cannot participate in frequency regulation according to the different operating conditions of the wind turbine. After the wind turbine uses the improved frequency control strategy, it accelerates the recovery of the DFIG rotor speed while avoiding a secondary drop in the system frequency. In addition, when the energy storage device has a poor state of charge and the system frequency is good, it charges to restore the state of charge.

Improved frequency control performance of restructured multi-area power system through optimized controller design

This paper presents an optimal cascaded three degree of freedom proportional integral (3DOF PI) controller and compares its performance with conventional proportional integral (PI) controller for load frequency control of two area deregulated power system. The 3DOF PI controller enhances the degree of freedom and gives better dynamic response. Genetic algorithm (GA) is used to get the optimal gains of the proposed controllers. In the considered two area thermal-gas-fuel cell system, the thermal system consists of a reheat turbine with appropriate generation rate constraint non linearity. Battery storage and unified power flow controller (UPFC) are also assumed to be present. The performance of the proposed controllers is evaluated under different operating conditions that take place in deregulated power market. To tackle any contract violation this article emphasizes on the ancillary services provided by electric vehicles (EVs) and distributed generations. A robustness analysis is also presented by varying parameters from their nominal values.

Cloud–Edge Cooperative Load Frequency Control for Isolated Microgrid Using Emergent Computation-Based Large-Scale Meta-Machine Learning

In the isolated microgrid, each unit is managed by different operators, and their interests conflict greatly. To balance the interests of different stakeholders in the electric grid sector, this paper proposes an Edge-Cloud cooperative data-driven load frequency control (ECCDD-LFC) method for isolated microgrids, which can deliver improved frequency control performance and reduce regulation cost. This method replaces the LFC controller in the conventional microgrid control center with a Cloud-based agent and sets each unit as an independent-decision Edge-based agent. It enables the units to make decisions independently and realize Cloud-Edge cooperative control. In addition, an emergent computation large-scale multi-agent deep meta-deterministic policy gradient (ECLSMA-DMDPG) is proposed. In this algorithm, a centralized training and decentralized execution policy are used to achieve the collaboration of multiple agents, a meta-learning technique is used to improve the robustness of the algorithm, and emergent computation is used to produce high-value samples for a higher-performance policy. The effectiveness of the proposed method is demonstrated in a simulation of the Zhuzhou isolated microgrid of the China Southern Grid (CSG) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">.</i>

Improved Frequency Control Strategy for Offshore Wind Farm Integration via VSC-HVDC

Voltage source converter based high voltage DC system (VSC-HVDC) has become a very promising solution to integrate offshore wind farm. However, the equivalent inertia of the modern power system with large renewable energy integration becomes small, which will arouse some frequency stability problems. To tackle this problem, this paper proposes an improved frequency regulation strategy for VSC-HVDC integrated offshore wind farm. Firstly, in the frequency decrease stage, the rotor kinetic energy of wind turbines (WTs) is used to suppress the decrease of the frequency, and the control parameters are determined to make full use of the mechanical power and rotor kinetic energy of WTs, the frequency nadir is improved. Secondly, in the rotor speed recovery stage, the DC capacitors of VSC-HVDC are used to release power to compensate the deficiency value of wind farm output power and avoid the secondary frequency drop (SFD) problem. Lastly, the simulation is conducted in PSCAD/EMTDC to validate the effectiveness of the proposed coordinated frequency control strategy.

Enhanced stability and failure avoidance of hydropower plant in contingent island operation by model predictive frequency control

The challenges of contingent island operation of hydropower plants are addressed by proposing an enhanced frequency control with advanced control algorithms. The study is based on a real power plant and considers the relevant power system in its entirety along with the load and transmission lines. Integrated transfer functions between the guide vane opening of a hydro turbine and the frequency of the associated generator were determined by in-situ identification. A model predictive controller, a fractional order PID controller, and a PID controller utilizing integral absolute error and integral time absolute error criteria were designed and developed. The performance of the proposed algorithms with the identified plant model was tested on a NI-cRIO 9049 FPGA platform. Improved frequency control in terms of setpoint change was achieved with the MPC and FOPID controllers. The MPC controller also features betters disturbance rejection compared to conventional PID controllers, which are tuned according to integral error criteria. The considered algorithms have been simulated in different operating scenarios, such as variations of active power load and transmission length. The proposed approach enhances stability and consequently avoids operational failures of hydropower plants in contingent islanding mode.

Distributional Deep Reinforcement Learning-Based Emergency Frequency Control

Emergency frequency control is one of the most critical approaches to maintain power system stability after major disturbances. With the increasing number of grid-connected renewable energy sources, existing model-based methods of frequency control are facing up with challenges of computational speed and scalability for large-scale systems. In this paper, the emergency frequency control problem is formulated as a Markov Decision Process and solved through a novel distributional deep reinforcement learning (DRL) method, namely the distributional soft actor critic (DSAC) method. Compared with other reinforcement learning methods that only estimate the mean value, the proposed DSAC model estimates the distribution of value function over returns. This advancement can lead to more insights and knowledge for the agent, with the benefit of a much faster and more stable learning process, and the improved frequency control performance. The simulation results on IEEE 39-bus and IEEE 118-bus systems demonstrate the effectiveness and robustness of proposed models, as well as the advantage compared to other state-of-the-art DRL algorithms.

Insights on designing effective and efficient frequency control arrangements from the Australian National Electricity Market

For restructured electricity industries undergoing energy transition, designing effective and efficient frequency control arrangements is a complex and ongoing task that requires appropriate configuration of controllers, generator technical connection requirements, market arrangements and wider policy settings. In this paper, we provide an overview and assessment of these arrangements in Australia’s National Electricity Market - a useful case study given its long-standing frequency control ancillary services markets, yet recent challenges in maintaining secure frequency control. We assess the performance of these evolving arrangements in delivering improved frequency control outcomes, with particular regard to growing renewable penetrations and evident tensions between mandatory requirements and market-based incentives. Based on this assessment, we draw out four key insights on designing frequency control arrangements as power system capabilities and needs change: (1) Understanding control action interactions, (2) Implementing efficient price formation and cost-allocation mechanisms, (3) Monitoring and assessing service provision to better align participant remuneration with service quality, and (4) Considering both regulatory and market mechanisms and their consequences and interactions. In particular, we discuss the trade-offs between effective and efficient outcomes, and provide arguments for more robust and forward-looking frequency control arrangements during energy transition.

Research on frequency modulation of DFIG wind turbines auxiliary power grid based on improved frequency control

With a large number of DFIG wind turbines connected to the power grid, in order to improve the frequency fluctuation caused by its decoupling, this paper first analyses the current situation of DFIG wind turbines participating in the primary frequency modulation of power grid, and establishes the corresponding model based on the above analysis. According to the commonly used inertial control methods, a frequency modulation method for auxiliary power grid of DFIG wind turbines based on improved frequency control strategy is proposed. Through the simulation of actual power grid model, the grid frequency fluctuation has been effectively alleviated after adding frequency control link to DFIG wind turbines, and it is concluded that the higher the wind power penetration, the more significant the frequency improvement effect.

Genetically tuned fuzzy controlled flywheel powered micro-grid for improved frequency control

In this article, hybrid wind-diesel system is powered with a genetically tuned fuzzy controlled flywheel for improving its frequency control. Flywheel is interfaced with the system through an electrical machine (generator/motor) and an electronic converter for synchronization. Fuzzy logic controller for the flywheel is designed in such a way that it continuously controls the system frequency and simultaneously satisfies the operational constraints of flywheel. Fuzzy logic controller is optimized by genetically tuning its membership functions. Regulated variable based on frequency deviation of system and speed characteristics of flywheel is introduced to reach out to the optimized membership functions. Necessary modeling has been done and effectiveness of the assembly has been confirmed by the simulation results.

A Droop Frequency Control for Maintaining Different Frequency Qualities in a Stand-Alone Multimicrogrid System

Multiple microgrid (MG) systems can exist in a wide geographical area. They can interconnect and operate on different frequency qualities to enhance the penetration of renewable energy resources. To operate multiple MGs on different frequency qualities, a framework of the stand-alone multimicrogrid (MMG) system is proposed in this study. In the proposed MMG system, each MG connects to the common dc line through an ac/dc interlinking converter. A droop frequency control is proposed for the interlinking converter to improve frequency control performance and achieve autonomous power sharing. The sensitivity analysis with respect to the proposed control is performed to evaluate the stability of the converter system. The proposed droop frequency controller is evaluated in the MMG system with three MGs. The feasibility of the proposed controller is verified by the hardware-in-the-loop simulation using OPAL-RT technologies. The droop frequency controller is executed in digital signal processor TMS-320F-28335 while the proposed MMG system is modeled in a real-time simulator (OP5600). A comparison study on the proposed droop frequency control and conventional P/f control is presented. By using the proposed frequency control, the energy reserves in the adjacent microgrids can be shared effectively to achieve better performance of frequency regulation in the stand-alone MMG system.

Improved frequency control of a micro-grid with a genetically tuned fuzzy controlled super-capacitor system

In this paper, genetically tuned fuzzy controlled super-capacitor energy storage system (SCESS) is employed to improve the frequency control of a hybrid wind-diesel system. Super-capacitor is interfaced with the system through voltage source converter and bidirectional DC-DC buck-boost converter. The fuzzy logic controller for SCESS is designed in such a way that the effect of load disturbance is continuously mitigated while considering the operational constraints of SCESS. The membership functions of fuzzy controller are tuned by employing genetic algorithm (GA) for optimal performance. Optimised membership functions are reached out by introducing a regulated variable based on supercapacitor voltage and frequency deviation of the system. To validate the proposed scheme, detailed model is developed and tested in MATLAB/Simulink environment.

Improved frequency control of a micro-grid with a genetically tuned fuzzy controlled super-capacitor system

Improved frequency control of a micro-grid with a genetically tuned fuzzy controlled super-capacitor system

Adaptive predictive control of a small capacity SMES unit for improved frequency control of a wind‐diesel power system

Energy storage is becoming increasingly important for isolated power systems having overall low inertia. Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. However, a small rating SMES device has operational constraints, therefore a suitable control strategy is required for its profitable and constrained operation. An adaptive controller which encapsulates on-line identification with model predictive control is proposed in this paper. A recursive least-squares algorithm is used to identify a reduced-order model of wind-diesel power system on-line. Based on the identified model and a simple discrete time model of SMES unit, an adaptive generalized predictive control scheme (AGPC) considering constraints on SMES current level and converter rating is formulated. The scheme yields a control signal which on one hand keeps the system frequency deviations to minimum and on the other hand forces the SMES device to operate within and near its operational constraints, for profitable operation. Simulation studies are performed to illustrate the potency of the proposed strategy in achieving all the control objectives.

Fuzzy based frequency control in an isolated network employing parallel operated fuel cell/ultra-capacitor systems

This paper proposes a fuzzy logic controller for power management of hybrid wind turbine (WT), photovoltaic (PV), fuel cell (FC), and ultra-capacitor (UC) for stand-alone applications. WT and PV are the primary power sources of the system, and an FC is expected to provide long-term energy balance, whereas the UC is employed as buffer storage for the short-term compensation. The improvement in fuzzy logic strategies enhances dynamic response of the FC/UC power system under various load conditions by suitable rule base design for fuzzy controller. The combined use of FC and UC has the potential for better energy efficiency and lifetime increment of FC technology. These rules are designed such that charging and discharging the UC voltage is controlled automatically. The fuzzy controller creates a balance between production and consumption with determination of the exact reference values for WT, PV, and FC. This causes a good frequency controlled in the hybrid generation power system. The fuzzy logic strategies performance under different condition has been verified by using real weather data practical load demand profile. To demonstrate the effectiveness of the proposed fuzzy logic strategies, comparison with improved frequency control method was performed using matlab/simulink by integrating the detailed mathematical and electrical models of the hybrid generation power system.

Improved frequency control of DBR lasers under hopped conditions by prediction and compensation of heating

DBR lasers can exhibit significant frequency-errors when operated in which a random frequency-hopping schedule. We introduce a simple thermal model which anticipates the frequency errors a change in schedule induces. Experiments were performed which confirm the validity of the model. A compensation scheme is developed which reduces the worst case frequency error range from 32.1 to 7.9 GHz.

Absolute frequency control of a 1560 nm (192 THz) DFB laser locked to a rubidium absorption line using a second-harmonic-generated signal

We demonstrate second-harmonic generation from a DFB laser at 1560 nm in a type I critically phase-matched KNbO/sub 3/ crystal. We obtain 2.2 nW at 780 mm with 11.3 mW at 1560 nm incident on the crystal. The conversion efficiency is 17.2 pW/(mW)/sup 2/. The 780 nm beam is used to interrogate a resonance of the /sup 87/Rb-D/sub 2/ line at 780 nm and lock the laser frequency. To characterize the absolute frequency stability, two 1560 nm DFB lasers are respectively stabilized on a Doppler resonance of the /sup 87/Rb-D/sub 2/ line (780.246 nm) and of the /sup 85/Rb-D/sub 2/ line (780.244 nm). The square root of the Allan variance measured from the beat note is around 1.5/spl times/10/sup -9/ for averaging times between 3 and 100 s. To improve the precision of the frequency locking, we realize a setup to observe a saturated absorption profile. We use a 780 nm stabilized laser as a pump and the SHG signal as a probe. A saturated absorption profile is observed over the Doppler envelope. Work is under progress to use this saturated resonance for an improved frequency control.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>