Total transfer capability (TTC) is an effective indicator to evaluate the transmission limit of the interconnected systems. However, due to the large-scale wind power integration, operation conditions of a power system may change rapidly, yielding time-varying characteristics of the TTC. As a result, the traditional time-consuming transient stability constrained TTC model is unable to assess the online transmission margin. In this paper, we propose an online measurement-based TTC estimator using the nonparametric analytics. It consists of three major components: the probabilistic data generation, the composite feature selection, and the group Lasso regression-based training scheme. Specifically, we present a probabilistic data generation approach to take into account the uncertainties of the day-ahead generation scheduling and to reduce the number of redundant or infeasible data. Then, the composite feature selection is used to reduce the dimension of the generated data and identify the features which are highly correlated with TTC. The features are determined by the maximal information coefficients and nonparametric independence screening approach. Finally, these selected features are trained by the group Lasso regression to learn the correlation between the TTC and the online measurements. Once real-time measurements are available, the TTC can be assessed immediately through the learned correlation relationship. Extensive numerical results carried out on the modified New England 39-bus test system demonstrate the feasibility of the proposed TTC estimator for online applications.

Online TTC Estimation Using Nonparametric Analytics Considering Wind Power Integration

Doubly fed induction generator (DFIG) is one of the most popular generators used nowadays in wind turbine systems (WTSs). This machine has some interesting advantages especially in variables speed applications. In the DFIG-based WTS, the rotor side of the machine is normally fed by a two-level power inverter controlled by the usual pulse width modulation (PWM) technique. This last has a principal disadvantages which is the high level of harmonic distortion. In this paper, we propose a novel technique based on space vector modulation (SVM) and fuzzy logic in order to performs the power provided by the DFIG to the grid. Simulation results show the efficiency of the proposed technique especially on the quality of the provided power comparatively to the usual PWM

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Indirect Vector Control of a DFIG Supplied by a Two-level FSVM Inverter for Wind Turbine System

Distortions of current and voltage waveforms from a sinusoidal shape are, not only a source of technical problems, but also have serious economic effects. Their occurrence is related to the common use of loads with nonlinear current-voltage characteristics. These are both high-power loads (most often power electronic switching devices supplying high-power drives), but also widely used low-power loads (power supplies, chargers, energy-saving light sources). The best way to eliminate these distortions is to use active power filters. The cost of these devices is relatively high. Therefore, scientists all over the world are conducting research aimed at developing techniques for the proper placement of these devices, in order to minimize their investment costs. The best solution to this problem is to use optimization techniques. This paper compares the methods and criteria used by the authors of publications dealing with this topic. The summary also indicates a possible direction for further work.

https://www.mdpi.com/1996-1073/15/3/1175/pdf?version=1644313285

A Review on Optimization of Active Power Filter Placement and Sizing Methods

This article deals in the modelling of intelligent controller for the Hybrid photovoltaic (PV)/Wind based smart grid system. With the development of solid state electronics also power systems intelligent techniques like neural networks, fuzzy logic, expert systems take part an essential contribution in design of controller for the smart grid. The above techniques give potential tools for design and development of fault detection controller in the advanced smart grid (SG). The intelligent techniques attained in rapid evolution during previous decades and their utilization now increased rapidly in current industrial environment. Renewable energy integration, participation of customers, performance optimization is important key features of digital grid power systems. In this article presents in new method of digital grid for hybrid photovoltaic/Wind based smart grid system were developed. It consists of solar PV array systems, wind power systems, asynchronous generator, converters, MPPT systems, fuzzy logic controllers (FLC). The model was performed through MATLAB/SIMULINK environment. The dynamic performance in presented model was tested in various operating conditions. Sunlight Irradiation, heat and rate of wind statistics was collected in a power grid combined solar PV model placed in main system. In this proposed simulation model also in supervision scheme give an appropriate tool for optimization of smart grid performance.

Design of Intelligent Controller for Hybrid PV/Wind Energy Based Smart Grid for Energy Management Applications

The realization of power electronic applications on hardware is a challenging task. The digital control circuit strategies are used to overcome the analog control strategies by providing great flexibility with simple equipment and higher switching frequencies. In this manuscript, an area optimized, modified digital space vector (DSV) pulse width modulation is designed and realized on low-cost FPGA. The modified digital space vector pulse width modulation (DSVPWM) uses a phase-locked loop (PLL) to generate clocks using the digital clock manager (DCM). These DCM clocks are used in the DSVPWM module to synchronize the other sub-modules. The voltage generation unit generates the three-phase (3-Ф) voltages and is used in the alpha-beta generation and sector determination unit. The reference active vectors are made by the reference generation unit and used in switching time calculation. The PWM pulses are generated using switching time generation, and lastly, the dead time occurrence unit generates the final SVPWM gate pulses. The modified DSVPWM is synthesized and implemented on Spartan-3E FPGA. The modified DSVPWM utilizes 17% slices, works at 102.45 MHz, and consumes 0.070 W total power. The simulation results and the resource utilization of modified DSVPWM are represented in detail. The modified DSVPWM is compared with existing PWM approaches on different Spartan-series FPGAs with better chip area improvement

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Modified digital space vector pulse width modulation realization on low-cost FPGA platform with optimization for 3-phase voltage source inverter

Simulated Annealing Based Selective Harmonic Elimination for Multi-level Inverter

This paper explores on experimental investigation of Shunt Hybrid Active Power Filter (SHAPF) for mitigation of harmonics and reactive power. In the present work, a Fuzzy Logic Controller (FLC) is implemented for generating desired harmonic reference currents and for regulating the DC side voltage of SHAPF. To efficiently utilize DC side voltage, Space Vector Pulse Width Modulation (SVPWM) is used for generating desired pulses required for Voltage Source Converter (VSC) in shunt Active Power Filter (APF). Experimental analysis has been carried out to assess the proposed control scheme. The control algorithm of the SHAPF is realized in digital domain using Spartan 6 Field-Programmable Gate Array (FPGA) controller. The fundamental necessities for the application structure require careful selection and configuration of elements of SHAPF. The hardware design of components of SHAPF is exhibited in this paper. The outcomes of this paper confirm the viability of SHAPF through 150V/1.5kVA experimental setup.

Experimental investigation of an indirect current controlled Fuzzy-SVPWM based Shunt Hybrid Active Power Filter

The increasing demand for electrical power necessitates the expansion of power system, which is constrained by land availability and other resources. This results in the utilization of power system upto its stability limits. The TTC for an instance gives us the load that can be further supplied by the system before it loses stability. This paper aims at computing the stability limits of the power system network employed for the computation of Total Transfer Capability (TTC) using Support Vector Machine (SVM). Computation of voltage stability (using voltage stability index method and P-Q plane method) has been considered on IEEE 30 bus system. Small signal stability limit (Eigen value approach) has been considered on an WSCC 3 machine 9 bus system for which TTC has been calculated by employing SVM. All simulations are carried out in MATLAB 8.0-R 2012 b environment.

Determination of TTC and application of SVM for demarcation of stability limits

Traditional Locational Marginal Price (LMP) consists of Energy, Congestion and Loss price. Accurate calculation of LMP is highly critical in ensuring smooth operation of the electricity market. LMP varies with respect to parameters such as operational, line design and generator design. The study on sensitivities of LMPs with respect to constraints along with the price helps in efficient running of the system. In this paper, the impact of different constraints on LMP is evaluated. The LMP at each bus is determined by using AC Optimized Power Flow. The impact of generator, transformer, load and transmission parameters on the LMP values is studied on IEEE WSCC 9 bus system. This paper helps to investigate the factors affecting the LMP and their impact on it. Power World Simulator is used for simulation and the results show the desired operating points of the system which helps to improve the system's economic operation.

Sensitivity assessment on Locational Marginal Price under deregulated electricity market

In the current electricity market, the demand for power increases exponentially day by day. The ISO can boost the power sales by using “willingness to pay” approach on the consumers. This paper proposes a novel approach of scheduling power by incorporating willingness to pay of consumers into the load dispatch problem. The consumers with higher willingness to pay usually use appropriate capacity transmission lines to receive power owing to their evident power needs. The appropriate capacity of the transmission lines allows congestion free power distribution and thus enabling a holistic improvement of the transmission system. The paper also includes the emission constraints to reduce the emissions from the generating plants and an incentive based curtailment scheme to support the willingness to pay based load dispatch. The proposed optimized model uses bees foraging algorithm (BFA) to perform economic load dispatch problem. A three generator model is used to illustrate the proposed approach.

S. Prabhakar Karthikeyan

Papers

Simulated Annealing Based Selective Harmonic Elimination for Multi-level Inverter

Experimental investigation of an indirect current controlled Fuzzy-SVPWM based Shunt Hybrid Active Power Filter

Determination of TTC and application of SVM for demarcation of stability limits

Sensitivity assessment on Locational Marginal Price under deregulated electricity market

Heuristic approach on economic load dispatch problem using willingness to pay along with incentive based load curtailment schemes