A weighted voltage model predictive control method for a virtual synchronous generator with enhanced parameter robustness

To address the problem of insufficient system inertia and improve the power quality of grid-connected inverters, and to enhance the stability of the power system, a method to control a virtual synchronous generator (VSG) output voltage based on model predictive control (MPC) is proposed. Parameters of the inductors, capacitors and other components of the VSG can vary as the temperature and current changes. Consequently the VSG output voltage and power control accuracy using the conventional MPC method may be reduced. In this paper, to improve the parameter robustness of the MPC method, a new weighted predictive capacitor voltage control method is proposed. Through detailed theoretical analysis, the principle of the proposed method to reduce the influence of parameter errors on voltage tracking accuracy is analyzed. Finally, the effectiveness and feasibility of the proposed method are verified by experimental tests using the Typhoon control hardware-in-the-loop experimental platform.

Optimization techniques for economic load dispatch problem in power plant

This paper presents survey of optimization techniques used to solve the problem of economic load dispatch in power stations. Since there is no single method available for solving all economic dispatch problems efficiently, thus a number of different optimization methods have been developed to solve this problem. These techniques were divided into three types depending on the efficiency of the solution: stochastic process techniques, statistical methods, and mathematical programming techniques which divided to local optimization, and global optimization. It is found that is better to use hybrid techniques to overcome load dispatch problems so as to achieve significant improvements in computation time, convergence properties, solution quality, or parameter robustness.

Model Predictive Control Based on Parametric Disturbance Compensation

Model predictive control (MPC) has been widely implemented in the motor because of its simple control design and good results. However, MPC relies on the permanent magnet synchronous motor (PMSM) system model. With the operation of the motor, parameter drift will occur due to temperature rise and flux saturation, resulting in model mismatch, which will seriously affect the control accuracy of the motor. This paper proposes a model predictive control based on parameter disturbance compensation that monitors system disturbances caused by motor parameter drift and performs real-time parameter disturbance compensation. And the frequency-domain method was used to analyze the convergence and filterability of the model. The Bode diagram of measurement error and input disturbance was studied when the parameters were underdamped, critically damped, and overdamped. Guidelines for parameter selection are given. Simulation results show that the proposed method has good dynamic performance, anti-interference ability, and parameter robustness, which effectively avoids the current static difference and oscillation problems caused by parameter changes.

DEVELOPMENT AND VALIDATION OF ANALYTICAL METHOD TO QUANTIFY THE DISSOLUTION OF CINARIZIN IN CAPSULES COMPOUNDED

Cinnarizine (CIN) is used in the treatment of cerebral circulatory, peripheral circulatory and balance disorders. An analytical method was developed and validated to determine the dissolution of cinnarizine (CIN) in capsules compounded by ultraviolet detection spectrophotometry. The resolutions of the Agência Nacional de Vigilância Sanitária nº. 899 of May 29, 2003 and nº. 166 of July 24, 2017 were used as the guide for validation of analytical methods. CIN showed high solubility in 0.1 mol.L-1 hydrochloric acid at 37 ° C (9.43 mg.mL-1), selectivity / specificity in the presence of other components (0.35 %), maximum absorption spectrum in 251 nm; linearity (r = 0.9999); precision (RSD repet.: 0.09%, RSD inter.: 1.10%); accuracy (LQC = 99.9%, MQC = 99.5%, HQC = 100.7%); limits of detection and quantification of 0.042 and 0.42 μg.mL-1, respectively. In the parameter robustness it has been proven that the proposed method does not suffer significant variations. The validated analytical method is easy to perform and has reliable selectivity / specificity, linearity, precision, accuracy, limits of detection, limits of quantification and robustness. Therefore, the ultraviolet detection spectrophotometry method is applicable to determine CIN in capsules compounded in simple, accurate and low cost dissolution assays.