Saima Ali

Damping low frequency oscillations using online Adaptive NeuroFuzzy Type-2 based STATCOM

The reactive power compensation using shunt FACTS controllers also regulates the voltage of bus at which the shunt controller is installed. Static Synchronous Compensator (STATCOM), one of the shunt FACTS controllers, is a well-known controller used for this purpose, however, this article investigates its behavior for damping power system oscillations by application of a novel direct adaptive NeuroFuzzy Type2 (ANFT2) based nonlinear control scheme, for damping low frequency inter-area oscillations, using STATCOM. The proposed control scheme exploits the excellent estimation property of Type2 membership functions for modeling uncertainties in the system. The parameters of the proposed control scheme are updated online without using any offline training data which in turn minimizes the memory requirements, computational complexity and latency maintaining the performance of the system. The performance of the proposed control system is tested for various faults and operating conditions on multi-machine test system using nonlinear time domain simulations. Finally, the comparative analysis of ANT2 with Adaptive NeuroFuzzy Type-1 (ANFT1) control and without control is presented to validate the efficiency of proposed control system. The simulation results reveal that the proposed control scheme significantly improves the damping performance in transient and steady-state regions.

Control of DC link voltage for grid interfaced DFIG using Adaptive Sliding Mode & Fuzzy based on Levenberg-Marquardt algorithm during symmetrical fault

Enhancement of fault ride through capability of Doubly Fed Induction Generator (DFIG) is demanding issue in developed countries. In this paper crowbar circuit is implemented for limitation of fault current while the Adaptive Sliding Mode Controller (ASMC) & Adaptive Fuzzy controller (AFC) based on Levenberg-Marquardt algorithm is proposed to enhance fault ride through capability. The Adaptive controller is used to control DC link voltage during normal and faulty condition. The result of controlled DC link voltage with ASMC & AFC is critically and analytically compared with the conventional tuned PI controller. The test bench model is IEEE 5 bus system composed of 9MW DFIG interfaced with 120kv grid.

Fast Performance Computing Model for Smart Distributed Power Systems

Plug-in Electric Vehicles (PEVs) are becoming the more prominent solution compared to fossil fuels cars technology due to its significant role in Greenhouse Gas (GHG) reduction, flexible storage, and ancillary service provision as a Distributed Generation (DG) resource in Vehicle to Grid (V2G) regulation mode. However, large-scale penetration of PEVs and growing demand of energy intensive Data Centers (DCs) brings undesirable higher load peaks in electricity demand hence, impose supply-demand imbalance and threaten the reliability of wholesale and retail power market. In order to overcome the aforementioned challenges, the proposed research considers smart Distributed Power System (DPS) comprising conventional sources, renewable energy, V2G regulation, and flexible storage energy resources. Moreover, price and incentive based Demand Response (DR) programs are implemented to sustain the balance between net demand and available generating resources in the DPS. In addition, we adapted a novel strategy to implement the computational intensive jobs of the proposed DPS model including incoming load profiles, V2G regulation, battery State of Charge (SOC) indication, and fast computation in decision based automated DR algorithm using Fast Performance Computing resources of DCs. In response, DPS provide economical and stable power to DCs under strict power quality constraints. Finally, the improved results are verified using case study of ISO California integrated with hybrid generation.

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

TCSC based online adaptive control for improving damping in multimachine power system

Power systems are inherently prone to disturbances that result in poorly damped low frequency electromechanical oscillations. This paper presents an adaptive PID (APID) controller for improving oscillation damping capability of a Thyristor controlled series capacitor (TCSC). An adaptive supplementary control can set the control parameters of PID in an online mode responding to respective changes in systems operating conditions. Control parameters are updated in real time by utilizing gradient descent method. Performance of proposed controller is investigated on two machine four bus system under diverse fault conditions. Nonlinear time domain simulation is made in MATLAB/Simulink and validation of proposed controller is made by its comparison with conventional PI controller. Results show clear eminence of proposed controller in improving transient stability of given system.