An adaptive series control for an interior permanent magnet synchronous motor with actuator compensation

An adaptive series speed control system for an interior permanent magnet synchronous motor(IPMSM)drive is presented in this paper.This control system consists of a current and a speed control loop,and it is intended to improve the drive’s speed tracking performance as well as to compensate for voltage distortions caused by non-ideal characteristics of the drive’s actuator,which is a voltage source inverter(VSI).To achieve these goals,a simple model that captures these characteristics of the VSI is developed and embedded in the motor’s electrical model.Then,based on the resulting model,an adaptive proportional-integral(PI)control for the current loops is designed,allowing for state regulation and actuator compensation.Additionally,to improve the drive’s speed tracking performance,a proportional-model-reference adaptive controller(MRAC)is designed for the speed loop.Techniques from machine learning are used for designing the MRAC to effectively address nonlinearities and uncertainties in the speed dynamic.Finally,simulation results are presented to illustrate the outstanding performance of the proposed multi-loop controller.

A New Robust Adaptive Neural Network Backstepping Control for Single Machine Infinite Power System With TCSC

For a single machine infinite power system with thyristor controlled series compensation(TCSC) device, which is affected by system model uncertainties, nonlinear time-delays and external unknown disturbances, we present a robust adaptive backstepping control scheme based on the radial basis function neural network(RBFNN). The RBFNN is introduced to approximate the complex nonlinear function involving uncertainties and external unknown disturbances, and meanwhile a new robust term is constructed to further estimate the system residual error,which removes the requirement of knowing the upper bound of the disturbances and uncertainty terms. The stability analysis of the power system is presented based on the Lyapunov function,which can guarantee the uniform ultimate boundedness(UUB) of all parameters and states of the whole closed-loop system. A comparison is made between the RBFNN-based robust adaptive control and the general backstepping control in the simulation part to verify the effectiveness of the proposed control scheme.

Approach for Grid Connected PV Management:Advance Solar Prediction and Enhancement of Voltage Stability Margin Using FACTS Device

The uncertainty in solar energy is different from conventional,dispatchable generation fuels and difficult to incorporate into the standard system operating procedures.In the first part of this work,the machine learning algorithm is used to train models based on solar irradiance data and different meteorological weather information to predict the solar irradiance for different cities to validate the forecasting model.Again,the intermittent and inertialess nature of photovoltaic(PV)systems can produce significant power oscillations that can cause significant problems with dynamic stability of the power system and also limit the penetration capacity of PV into the grid.In the second part,it is shown that the residue-based power oscillation damping(POD)controller obviously improves the inter-area oscillation damping.The validity and effectiveness of the proposed controller are demonstrated on the three-machine two-area test system that combines the conventional synchronous generator and flexible alternating current transmission systems(FACTS)device using simulations.This report overall puts an in-depth analysis with regard to the challenges of solar resources with integrating,planning,operating,and particularly the stability of the rest of the power grid,including existing generation resources,customer requirements,and the transmission system itself that will lead to an improved decision making in resource allocations and grid stability.

Coordination of PSS and TCSC controller using modified particle swarm optimization algorithm to improve power system dynamic performance

This paper develops a modified optimization procedure for coordination of a power system stabilizer (PSS) and a thyristor controlled series compensator (TCSC) controller to enhance the power system small signal stability.The new approach employs eigenvalue-based and time-domain simulation based objective functions simultaneously to improve the optimization convergence rate.A modified particle swarm optimization (MPSO) algorithm is used as the optimization algorithm.The results of simulations and eigenvalue analysis for a single machine infinite bus (SMIB) system equipped with the proposed PSS and TCSC controllers confirm that the new approach is effective in enhancing the system stability.

An interval type-2 fuzzy logic controller for TCSC to improve the damping of power system oscillations

In this paper an interval type-2 fuzzy logic controller （IT2FLC） was proposed for thyristor controlled series capacitor （TCSC） to improve power system damping. For controller design, memberships of system variables were represented using interval type-2 fuzzy sets. The three-dimensional membership function of type-2 fuzzy sets provided additional degree of freedom that made it possible to directly model and handle uncertainties. Simulations conducted on a single machine infinite bus （SMIB） power system showed that the proposed controller was more effective than particle swarm optimization （PSO） tuned and type-1 fuzzy logic （T1FL） based damping controllers. Robust performance of the proposed controller was also validated at different operating conditions, various disturbances and parameter variation of the transmission line parameters.

Orthogonality of Redesigned tRNA Molecules with Three Stop Codons

The ability to expand genetic code in living cells has emerged as a powerful method with diverse applications.Here,we design re-placement of the anticodons of E.coli tRNAs that recognize codons for 20 natural amino acids,with three anti-stop codons,resulting in a total of 60 engineered tRNA constructs.We test these constructs one by one in E.coli,and found that six tRNAsCUA(tyrV,serX,hisR,trpT,glnV and leuX),two tRNAsUCA(trpT and leuX)and one tRNAUUA(tyrV)allowed efficient expression of Red Fluorescence Protein(RFP)with the presence of a corresponding stop codon in frame.Furthermore,we exploit the mutual orthogonality of tRNASer CUA,tRNATrpUCA and tRNATyrUUA with corresponding stop codons and demonstrated that the tRNASer CUA and the tRNATrp UCA can provide dynamic range and low crosstalk.Finally,we show the TAG and TGA can not only be used as an"AND gate"circuit to control the translation of target gene,but also be used to control the translation of a prodeoxyviolacein(PDV)pathway and a reporter in parallel.Overall,this work provides flexible tools for translational control and holds great potential to promote synthetic biology studies.

Demand response based congestion management in a mix of pool and bilateral electricity market model

The independent system operator （ISO） is a key element in the deregulated structure with one of the responsibilities of transmission congestion management （CM）. The ISO opts market based solutions to manage congestion receiving bids from generation companies （GENCOs） as well as distribution companies （DISCOMs） to reschedule their generation and relocate demand. The nodal prices increases during the congestion hours and the demand response to nodal prices will be an effective tool for the control of congestion. In this paper, demand response-based CM has been proposed for a mix of pool and bilateral electricity market model. The linear bid curves have been considered for demand bids to respond to the congestion in the network. The bilateral demand has been obtained with minimum deviations in their preferred schedule. The impact of flexible alternating current transmission system （FACTS） devices viz static var compensator （SVC） and thyristor controlled series compensator （TCSC） has also been considered for demand management during congestion. Multi-line congestion cases have been considered to study the impact on demand response without and with FACTS devices. The proposed approach has been tested on the IEEE 24 bus test system.