Primary frequency control considering communication delay for grid-connected offshore wind power systems

Offshore wind farms are becoming increasingly distant from onshore centralized control centers,and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control.This causes a deterioration in the performance of the primary frequency control and,in some cases,may even result in frequency instability within the power system.Therefore,a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power.The Padéapproximation was used to model the time delays,and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays.The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored.In addition,a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics.Finally,a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform.The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.

Ladder Time Stepwise Inertia Coordinated Control Method of Multiple Wind Farms to Suppress System Frequency Secondary Drop

Currently,both regulated and deregulated power trading exist in China’s power system,which has caused imbalanced funds in the electricity market.In this paper,a simulation analysis of the electricity market with wind energy resources is conducted,and the calculation methods of unbalanced funds are investigated systematically.In detail,the calculation formulas of unbalanced funds are illustrated based on their definition,and a two-track electricity market clearing model is established.Firstly,the concept of the dual-track system is explained,and the specific calculation formulas of various types of unbalanced funds are provided.Next,considering the renewable energy consumption,the market clearing model based on DC power flow is constructed and solved;by combining fitting methods of mid-and long-term curves,the unbalanced funds are calculated based on clearing results and formulas.

Remote Control of Bovine Catalase Activity with Specific Frequencies of Human and Bovine Catalase with and without Bound NADP+

Remote control enzyme technology is widely used today through resonance. In this study, we showed that the use of frequencies of the catalase enzyme itself to increase enzymatic rate is successful not only in test tubes but also remotely. The present study also suggests that, under optimal temperature, the use of bovine catalase frequency (the specific frequency of that enzyme) has a superior rate promoting vibration than the human catalase frequency, and so increases very significantly the chemical rate of bovine catalase (about 120% at 40˚C). It also suggests that bovine catalase subjected to bovine and human frequencies with catalase bound NADP+ experienced more resonance weight towards NADP+ and so were more slowly reduced back to catalase bound NADPH, increasing compound II formation rate, and slowing down the catalase activity rate.

A Temporary Frequency Response Strategy Using a Voltage Source-Based PermanentMagnet Synchronous Generator and Energy Storage Systems

Energy storage systems(ESS)and permanent magnet synchronous generators(PMSG)are speculated to be able to exhibit frequency regulation capabilities by adding differential and proportional control loops with different control objectives.The available PMSG kinetic energy and charging/discharging capacities of the ESS were restricted.To improve the inertia response and frequency control capability,we propose a short-term frequency support strategy for the ESS and PMSG.To this end,the weights were embedded in the control loops to adjust the participation of the differential and proportional controls based on the system frequency excursion.The effectiveness of the proposed control strategy was verified using PSCAD/EMTDC.The simulations revealed that the proposed strategy could improve the maximum rate of change of the frequency nadir and maximum frequency excursion.Therefore,it provides a promising solution of ancillary services for frequency regulation of PMSG and ESS.

Model-Free Adaptive Frequency Calibration for Voltage-Controlled Oscillators

The operating frequency accuracy of the local oscillators is critical for the overall system performance in the communication systems.However,the high-precision oscillators could be too expensive for civil applications.In this paper,we propose a model-free adaptive frequency calibration framework for a voltage-controlled crystal oscillator(VCO)equipped with a time to digital converter(TDC),which can significantly improve the frequency accuracy of the VCO thus calibrated.The idea is to utilize a high-precision TDC to directly measure the VCO period which is then passed to a model-free method for working frequency calibration.One advantage of this method is that the working frequency calibration employs the system history of input/output(I/O)data,instead of establishing an accurate VCO voltagecontrolled oscillator model.Another advantage is the lightweight calibration method with low complexity such that it can be implemented on an MCU with limited computation capabilities.Experimental results show that the proposed calibration method can improve the frequency accuracy of a VCO from±20 ppm to±10 ppb,which indicates the promise of the modelfree adaptive frequency calibrator for VCOs.

A low-noise X-band microwave source with digital automatic frequency control for electron paramagnetic resonance spectroscopy

We report a new design of microwave source for X-band electron paramagnetic resonance spectrometer.The microwave source is equipped with a digital automatic frequency control circuit.The parameters of the digital automatic frequency control circuit can be flexibly configured for different experimental conditions,such as the input powers or the quality factors of the resonator.The configurability makes the microwave source universally compatible and greatly extends its application.To demonstrate the ability of adapting to various experimental conditions,the microwave source is tested by varying the input powers and the quality factors of the resonator.A satisfactory phase noise as low as-135 d Bc/Hz at 100-k Hz offset from the center frequency is achieved,due to the use of a phase-locked dielectric resonator oscillator and a direct digital synthesizer.Continuous-wave electron paramagnetic resonance experiments are conducted to examine the performance of the microwave source.The outstanding performance shows a prospect of wide applications of the microwave source in numerous fields of science.

Finite-time economic model predictive control for optimal load dispatch and frequency regulation in interconnected power systems

This paper presents a finite-time economic model predictive control(MPC)algorithm that can be used for frequency regulation and optimal load dispatch in multi-area power systems.Economic MPC can be used in a power system to ensure frequency stability,real-time economic optimization,control of the system and optimal load dispatch from it.A generalized terminal penalty term was used,and the finite-time convergence of the system was guaranteed.The effectiveness of the proposed model predictive control algorithm was verified by simulating a power system,which had two areas connected by an AC tie line.The simulation results demonstrated the effectiveness of the algorithm.

Tool Condition Monitoring Based on Nonlinear Output Frequency Response Functions and Multivariate Control Chart

Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.

Signal frequency based self－tuning fuzzy controller for semi－active suspension system

A new kind of fuzzy control scheme, based on the identification of the signal' s main frequency and the behavior of the ER damper, is proposed to control the semi-active suspension system. This method ad-justs the fuzzy controller to achieve the best isolation effect by analyzing the main frequency' s characters and inspecting the change of system parameters. The input of the fuzzy controller is the main frequency and the op-timal damping ratio is the output. Simulation results indicated that the proposed control method is very effec-tive in isolating the vibration.

A New Design of Robust H∞Load-Frequency Controller for Optimal Coordination of Energy Generation in Power System Stability Using LMI Approach

This paper presents the problem of robust H∞?load frequency controller design and robust H￥ based approach called advanced frequency control (AFC). The objective is to split the task of balancing frequency deviations introduced by renewable energy source (RES) and load variations according to the capabilities of storage and generators. The problem we address is to design an output feedback controller such that, all admissible parameter uncertainties, the closed-loop system satisfies not only the prespecified H∞? norm constraint on the transfer function from the disturbance input to the system output. The conventional generators mainly balance the low-frequency components and load variations while the energy storage devices compensate the high- frequency components. In order to enable the controller design for storage devices located at buses with no generators, a model for the frequency at such a bus is developed. Then, AEC controllers are synthesized through decentralized static output feedback to reduce the complexity. The conditions for the existence of desired controllers are derived in terms of a linear matrix inequality (LMI) algorithm is improved. From the simulation results, the system responses with the proposed controller are the best transient responses.

Design of Nichols PID Controller for Load Frequency Control

为解决互联水电系统负荷频率控制（load frequencycontrol,LFC）问题,及保持互联电网系统频率、联络线功率及区域控制误差（area control error,ACE）的稳定,根据闭环系统谐振峰值与系统响应最大峰值之间的关系,构建一个与系统参数及控制器参数都相关的优化问题,通过该问题的求解获得控制器参数与系统参数之间的数学关系,针对水轮发电系统非最小相位特性,通过串加比例–微分（proportional-derivative,PD）控制方式降低系统阶次,设计尼科尔斯（Nichols）曲线的比例–积分–微分（proportional-integral-derivative,PID）控制器。基于模型参数扰动和负荷干扰的仿真结果表明：尼科尔斯PID控制器能快速调整系统频率偏差、联络线功率偏差及ACE为0,具有良好的鲁棒性能和抗负荷干扰性能,系统过渡过程性能明显优于传统PID调节器结果。

Load Frequency Control of Small Hydropower Plants Using One-Input Fuzzy PI Controller with Linear and Non-Linear Plant Model

This study presents an intelligent approach for load frequency control (LFC) of small hydropower plants (SHPs). The approach which is based on fuzzy logic (FL), takes into account the non-linearity of SHPs—something which is not possible using traditional controllers. Most intelligent methods use two- input fuzzy controllers, but because such controllers are expensive, there is economic interest in the relatively cheaper single-input controllers. A non- linear control model based on one-input fuzzy logic PI (FLPI) controller was developed and applied to control the non-linear SHP. Using MATLAB/Si- mulink SimScape, the SHP was simulated with linear and non-linear plant models. The performance of the FLPI controller was investigated and compared with that of the conventional PI/PID controller. Results show that the settling time for the FLPI controller is about 8 times shorter;while the overshoot is about 15 times smaller compared to the conventional PI/PID controller. Therefore, the FLPI controller performs better than the conventional PI/PID controller not only in meeting the LFC control objective but also in ensuring increased dynamic stability of SHPs.

Kautz Function Based Continuous-Time Model Predictive Controller for Load Frequency Control in a Multi-Area Power System

A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control(LFC).A dynamic model of an interconnected power system was used for Model Predictive Controller(MPC)design.MPC predicts the future trajectory of the dynamic model by calculating the optimal closed loop feedback gain matrix.In this paper,the optimal closed loop feedback gain matrix was calculated using Kautz function.Being an Orthonormal Basis Function(OBF),Kautz function has an advantage of solving complex pole-based nonlinear system.Genetic Algorithm(GA)was applied to optimally tune the Kautz function-based MPC.A constraint based on phase plane analysis was implemented with the cost function in order to improve the robustness of the Kautz function-based MPC.The proposed method was simulated with three area interconnected power system and the efficiency of the proposed method was measured and exhibited by comparing with conventional Proportional and Integral(PI)controller and Linear Quadratic Regulation(LQR).

Novel Adaptive Neural Controller Design Based on HVDC Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance

This paper presents the effect of the high voltage direct current (HVDC) transmission system based on voltage source converter (VSC) on the sub synchronous resonance (SSR) and low frequency oscillations (LFO) in power system. Also, a novel adaptive neural controller based on neural identifier is proposed for the HVDC which is capable of damping out LFO and sub synchronous oscillations (SSO). For comparison purposes, results of system based damping neural controller are compared with a lead-lag controller based on quantum particle swarm optimization (QPSO). It is shown that implementing adaptive damping controller not only improves the stability of power system but also can overcome drawbacks of conventional compensators with fixed parameters. In order to determine the most effective input of HVDC system to apply supplementary controller signal, analysis based on singular value decomposition is performed. To evaluate the performance of the proposed controller, transient simulations of detailed nonlinear system are considered.

Bilateral Contract for Load Frequency and Renewable Energy Sources Using Advanced Controller

Reestablishment in power system brings in significant transformation in the power sector by extinguishing the possession of sound consolidated assistance.However,the collaboration of various manufacturing agencies,autonomous power manufacturers,and buyers have created complex installation processes.The regular active load and inefficiency of best measures among varied associates is a huge hazard.Any sudden load deviation will give rise to immediate amendment in frequency and tie-line power errors.It is essential to deal with every zone’s frequency and tie-line power within permitted confines followed by fluctuations within the load.Therefore,it can be proficient by implementing Load Frequency Control under the Bilateral case,stabilizing the power and frequency distinction within the interrelated power grid.Balancing the net deviation in multiple areas is possible by minimizing the unbalance of Bilateral Contracts with the help of proportional integral and advanced controllers like Harris Hawks Optimizer.We proposed the advanced controller Harris Hawk optimizer-based model and validated it on a test bench.The experiment results show that the delay time is 0.0029 s and the settling time of 20.86 s only.This model can also be leveraged to examine the decision boundaries of the Bilateral case.

Pulse-Width Pulse-Frequency Based Optimal Controller Design for Kinetic Kill Vehicle Attitude Tracking Control

The attitude control problem of the kinetic kill vehicle is studied in this work. A new mathematical model of the kinetic kill vehicle is proposed, the linear quadratic regulator technique is used to design the optimal attitude controller, and the pulse-width pulse-frequency modulator is used to shape the continuous control command to pulse or on-off signals to meet the requirements of the reaction thrusters. The methods to select the appropriate parameters of pulse-width pulse-frequency are presented in detail. Numerical simulations show that the performance of the LQR/PWPF approach can achieve good control performance such as pseudo-linear operation, high accuracy, and fast enough tracking speed.

Hybrid Fuzzy Controller Based Frequency Regulation in Restructured Power System

This paper discusses the implementation of Load Frequency Control (LFC) in restructured power system using Hybrid Fuzzy controller. The formulation of LFC in open energy market is much more challenging;hence it needs an intelligent controller to adapt the changes imposed by the dynamics of restructured bilateral contracts. Fuzzy Logic Control deals well with uncertainty and indistinctness while Particle Swarm Optimization (PSO) is a well-known optimization tool. Abovementioned techniques are combined and called as Hybrid Fuzzy to improve the dynamic performance of the system. Frequency control of restructured system has been achieved by automatic Membership Function (MF) tuned fuzzy logic controller. The parameters defining membership function has been tuned and updated from time to time using Particle Swarm Optimization (PSO). The robustness of the proposed hybrid fuzzy controller has been compared with conventional fuzzy logic controller using performance measures like overshoot and settling time following a step load perturbation. The motivation for using membership function tuning using PSO is to show the behavior of the controller for a wide range of system parameters and load changes. Error based analysis with parametric uncertainties and load changes is tested on a two-area restructured power system.

Optimal control of wireless energy transfer system via decreasing frequency

In order to solve the multiple power extreme value point problem caused by system frequency splitting during wireless energy transmission at short distances a transmission model of the system is established.With the comprehensive consideration of the resonance frequency load parameters and the coupling between coils the internal factors of frequency splitting and boundary conditions are discussed.The results show that under the condition of the fixed load the higher the natural resonance frequency the easier the frequency splitting. As the frequency splitting occurs the frequency of the maximum power transfer is no longer with the natural resonance frequency which can make the system unstable and the transfer power more difficult to control. Therefore a decreasing-frequency method is proposed to avoid the system frequency splitting. And decreasing the system resonance frequency can make the system successfully withdraw the frequency splitting area at a short-distance range.Under the fixed load condition the transmission power of the system can be increased by 400% and the transmission efficiency is reduced by only 14% which greatly improves the transmission performance of the system.

Intrusion Detection System with Remote Signalling for Vehicles Using an Arduino Controller and Radio-Frequency Technology

Malicious activities or policy violations have been a concern for the past years. For example, many people have been victims of robbery on vehicles. A conceptual diagram of an Intrusion Detection System (IDS) [1] [2] for vehicles with remote signaling using an Arduino controller and radio-frequency technology is proposed in this paper. To address malicious activities on vehicles, two aspects are considered here, namely: notifier and detector. Firstly, an object-oriented C module that puts on and off a controller (installed inside the vehicle) and an anti-theft electronic editing that powered using an alternator and supported by a back-up battery are implemented. Secondly, a magnetic intrusion sensor, controlled by a proximity detector using radio-frequency technology, has been installed on each vehicle door. To enable IDS, a user needs to activate the monitoring system when leaving their vehicle. This is done using a remote system. In case the user does not activate the monitoring system while leaving the vehicle, a 5-meter-proximity detector will automatically lock the system and set off the monitoring system whenever the user is outside the detection zone. The detection zone is a 5-meter radius area centered at the controller. Here, monitoring consists of geolocating any intruders within the detection zone. This means, if any of the vehicle doors is opened while the system is still locked, the controller will activate the vehicle alarm for a few seconds, thereafter send an SMS notification to the owner. The system automatically unlocks as soon as the proximity detector is within the detection zone. The contribution of this paper, as compared to other similar work, is to reinforce the electronic implementation of IDS.

Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs

Reliable load frequency control LFC is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-Area interconnected power system with wind turbines, this paper presents a distributed model predictive control DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints GRCs, load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed-loop performance, and computational burden with the physical constraints. © 2014 Chinese Association of Automation.