Optimal linear quadratic Gaussian control based frequency regulation with communication delays in power system

<p>In this paper, load frequency regulator based on linear quadratic Gaussian (LQG) is designed for the MAPS with communication delays. The communication delay is considered to denote the small time delay in a local control area of a wide-area power system. The system is modeled in the state space with inclusion of the delay state matrix parameters. Since some state variables are difficult to measure in a real modern multi-area power system, Kalman filter is used to estimate the unmeasured variables. In addition, the controller with the optimal feedback gain reduces the frequency spikes to zero and keeps the system stable. Lyapunov function based on the LMI technique is used to re-assure the asymptotically stability and the convergence of the estimator error. The designed LQG is simulated in a two area connected power network with considerable time delay. The result from the simulations indicates that the controller performed with expectation in terms of damping the frequency fluctuations and area control errors. It also solved the limitation of other controllers which need to measure all the system state variables.</p>

Load frequency control in the presence of simultaneous cyber-attack and participation of demand response program

Simultaneous investigation of demand response programs and false data injection cyber-attack are critical issues for the smart power system frequency regulation. To this purpose, in this paper, the output of the studied system is simultaneously divided into two subsystems: one part including false data injection cyder-attack and another part without cyder-attack. Then, false data injection cyber-attack and load disturbance are estimated by a non-linear sliding mode observer, simultaneously and separately. After that, demand response is incorporated in the uncertain power system to compensate the whole or a part of the load disturbance based on the available electrical power in the aggregators considering communication time delay. Finally, active disturbance rejection control is modified and introduced to remove the false data injection cyber-attack and control the uncompensated load disturbance. The salp swarm algorithm is used to design the parameters. The results of several simulation scenarios indicate the efficient performance of the proposed method.

Configuration of an Energy Storage System Considering the Frequency Response and the Dynamic Frequency Dispersion

The high proportion of renewable energy sources (RESs) in the system reduces the frequency support capacity and aggravates the generation of unbalanced power, while the dynamic frequency dispersion makes it difficult for a centralized energy storage system (ESS) to take into account the frequency requirements of different regions. In this context, the research takes the region with high penetration of RESs and frequent power fluctuations as the grid node of the ESS. By configuring the parameters of the ESS under the control strategy of virtual synchronous generators, the inertia and the primary frequency reserve of the system are supplemented, and the regulation characteristics of the ESS are depicted. Taking the steady-state recovery time and the amplitude coefficient as the evaluation indexes, the effects of the virtual inertia constant, the virtual damping coefficient, and the virtual frequency regulation coefficient on the behavior of the ESS are deeply analyzed. Finally, the quantitative configuration of the ESS is realized by considering the frequency response and the dynamic frequency dispersion.

A Novel Model Predictive Control for Stability Improvement of Small Scaled Zero-inertia Multiple DGs Micro-grid

A zero-inertia micro-grid is a power system consisting of multiple renewable energy power sources and energy storage systems without the presence of conventional synchronous generators. In such a system, a large variation of the load or source sides during the islanded mode of operation extremely degrades the micro-grid's voltage and frequency stability. This study presents a virtual inertia-based predictive control strategy for a small-scale zero-inertia multiple distributed generators (DGs) micro-grid. In islanded mode, Voltage Model Predictive Control (VMPC) was implemented to control and maintain the voltage and frequency of the micro-grid. However, instabilities in frequency and voltage may rise at the Point of Common Coupling (PCC) due to large variations at both source and load sides. Therefore, the proposed virtual inertia loop calculates the amount of active power to be delivered or absorbed by each DG, and its effect is reflected in the estimated d current component of the VMPC, thus providing better frequency regulation. In grid-connected mode, Direct Power Model Predictive Control (DPMPC) was implemented to manage the power flow between each DG and the utility grid. The control approach also enables the DG plug and play characteristics. The performance of the control strategy was investigated and verified using the PSCAD/EMTDC software platform.

Frequency regulation of a RES integrated power system with AC/DC parallel link employing a fuzzy tuned fractional order controller

This paper demonstrates the operational efficacy of a newly proposed fuzzy tuned fractional order controller to offer an improved frequency regulation of a multi area renewable energy source (RES) integrated nonlinear power system. The effect of governor dead band nonlinearity and generation rate constraint of hydro and thermal power plants are considered in the system. Moreover, a proposed appropriate High voltage direct current (HVDC) tie line model is incorporated in this work, to verify the frequency deviation. Different test cases are applied to verify the robustness of the controllers on frequency response. The superiority of the proposed controller upon Proportional integral and derivative (PID), fuzzy logic controller and fuzzy PID controller in minimizing frequency deviation has been verified through MATLAB SIMULINK environment.