The article presents the consequences of the introduction of EU regulation 2016/631 for power park modules (PPMs), of which wind farms are a typical example. Analysing the yearlong course of changes in the generated power, the possibility of a typical wind farm meeting the requirements for the production and absorption of reactive power was checked. It was shown that in the selected cases it was necessary to introduce additional sources of reactive power on the side of the farm’s MV.
Single-branch filters are still popular and are commonly used for power quality improvement purposes. Analysis of a single-branch filter is a relatively simple task. Although individual filters tuned to specific harmonics can be easily designed, after connecting them into a group it turns out that the capacitance and inductance mutually influence each other, distorting the resulting frequency characteristics. This article presents a matrix method for design a group of single-branch filters, so that the resultant frequency characteristic satisfies the design requirements including the requirements for location of the frequency characteristic maxima. Designer indicates the frequencies of the parallel resonances.
The presented paper concerns the issues of communication networks applied to monitoring and control of reactive power compensator for small hydroelectric plants installed in areas distant from urban agglomerations. Ethernet, CAN, Modbus and GPRS transmission protocols has been used. Industrial programmable controller as a data collector has been used also.
Asynchronized (doubly-fed) machines with two (three) excitating winding and reversing excitation system allow to control vector of magnetomotive force. This solution allows separating regulation of the electromagnetic torque (active power) and voltage (reactive power). This paper describes the experience in the development and operation of asynchronized turbogenerators and condensers.
With the increasing penetration rate of grid-connected renewable energy generation, the problem of grid voltage excursion becomes an important issue that needs to be solved urgently. As a new type of voltage regulation control method, electric spring (ES) can alleviate the fluctuations of renewable energy output effectively. In this paper, the background and basic principle of the electric spring are introduced firstly. Then, considering the influence of an electric spring on noncritical load voltage, noncritical loads are classified reasonably, and based on the electric spring phasor diagram, the control method to meet the noncritical load voltage constraint is proposed. This control method can meet the requirements of voltage excursions of different kinds of noncritical load, increase the connection capacity of the noncritical load and improve the voltage stabilization capacity of the electric spring. Finally, through the simulation case, the feasibility and validity of electric spring theory and the proposed control method are verified.
The work presents a DC power supply with power factor correction (PFC). This device is also equipped with a parallel active filter function, which enables the possibility of compensation (minimization) of reactive and distortion power, generated by a group of loads, connected to the same power grid node. A passive filter with variable inductance applied at the input of the power supply allows for a significant improvement in quality of the system control (given specific criteria), as compared to the solution with a filter with fixed parameters. This is possible by increasing the dynamics of current changes at the power supply input (extending its “frequency response”). The paper presents the principle of operation as well as structures and models of the power supply control system and its power stage. Selected test results of the simulation model of the electric system with the power supply, in various operating conditions, are also presented.
The paper aims at the higher reactive power management complexity caused by the access of distributed power, and the problem such as large data exchange capacity, low accuracy of reactive power distribution, a slow convergence rate, and so on, may appear when the controlled objects are large. This paper proposes a reactive power and voltage control management strategy based on virtual reactance cloud control. The coupling between active power and reactive power in the system is effectively eliminated through the virtual reactance. At the same time, huge amounts of data are treated to parallel processing by using the cloud computing model parallel distributed processing, realize the uncertainty transformation between qualitative concept and quantitative value. The power distribution matrix is formed according to graph theory, and the accurate allocation of reactive power is realized by applying the cloud control model. Finally, the validity and rationality of this method are verified by testing a practical node system through simulation.
Analysis of power consumption presents a very important issue for power distribution system operators. Some power system processes such as planning, demand forecasting, development, etc.., require a complete understanding of behaviour of power consumption for observed area, which requires appropriate techniques for analysis of available data. In this paper, two different time-frequency techniques are applied for analysis of hourly values of active and reactive power consumption from one real power distribution transformer substation in urban part of Sarajevo city. Using the continuous wavelet transform (CWT) with wavelet power spectrum and global wavelet spectrum some properties of analysed time series are determined. Then, empirical mode decomposition (EMD) and Hilbert-Huang Transform (HHT) are applied for the analyses of the same time series and the results showed that both applied approaches can provide very useful information about the behaviour of power consumption for observed time interval and different period (frequency) bands. Also it can be noticed that the results obtained by global wavelet spectrum and marginal Hilbert spectrum are very similar, thus confirming that both approaches could be used for identification of main properties of active and reactive power consumption time series.
In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC). This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.
This paper presents a novel speed estimator using Reactive Power based Model Reference Neural Learning Adaptive System (RP-MRNLAS) for sensorless indirect vector controlled induction motor drives. The Model Reference Adaptive System (MRAS) based speed estimator using simplified reactive power equations is one of the speed estimation method used for sensor-less indirect vector controlled induction motor drives. The conventional MRAS speed estimator uses PI controller for adaptation mechanism. The nonlinear mapping capability of Neural Network (NN) and the powerful learning algorithms have increased the applications of NN in power electronics and drives. This paper proposes the use of neural learning algorithm for adaptation in a reactive power technique based MRAS for speed estimation. The proposed scheme combines the advantages of simplified reactive power technique and the capability of neural learning algorithm to form a scheme named “Reactive Power based Model Reference Neural Learning Adaptive System” (RP-MRNLAS) for speed estimator in Sensorless Indirect Vector Controlled Induction Motor Drives. The proposed RP-MRNLAS is compared in terms of accuracy, integrator drift problems and stator resistance versions with the commonly used Rotor Flux based MRNLAS (RF-MRNLAS) for the same system and validated through Matlab/Simulink. The superiority of the RP-MRNLAS technique is demonstrated.
This paper presents a novel approach for reactive power planning of a connected power network. Reactive power planning is nothing but the optimal usage of all reactive power sources i.e., transformer tap setting arrangements, reactive generations of generators and shunt VAR compensators installed at weak nodes. Shunt VAR compensator placement positions are determined by a FVSI (Fast Voltage Stability Index) method. Optimal setting of all reactive power reserves are determined by a GA (genetic algorithm) based optimization method. The effectiveness of the detection of the weak nodes by the FVSI method is validated by comparing the result with two other wellknown methods of weak node detection like Modal analysis and the L-index method. Finally, FVSI based allocation of VAR sources emerges as the most suitable method for reactive power planning.
This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.
Transmission line loss minimization in a power system is an important research issue and it can be achieved by means of reactive power compensation. The unscheduled increment of load in a power system has driven the system to experience stressed conditions. This phenomenon has also led to voltage profile depreciation below the acceptable secure limit. The significance and use of Flexible AC Transmission System (FACTS) devices and capacitor placement is in order to alleviate the voltage profile decay problem. The optimal value of compensating devices equires proper optimization technique, able to search the optimal solution with less computational burden. This paper presents a technique to provide simultaneous or individual controls of basic system parameter like transmission voltage, impedance and phase angle, thereby controlling the transmitted power using Unified Power Flow Controller (UPFC) based on Bacterial Foraging (BF) algorithm. Voltage stability level of the system is defined on the Fast Voltage Stability Index (FVSI) of the lines. The IEEE 14-bus system is used as the test system to demonstrate the applicability and efficiency of the proposed system. The test result showed that the ocation of UPFC improves the voltage profile and also minimize the real power loss.
The smart grid concept is predicated upon the pervasive With the construction and development of distribution automation, distributed power supply needs to be comprehensively considered in reactive power optimization as a supplement to reactive power. The traditional reactive power optimization of a distribution network cannot meet the requirements of an active distribution network (ADN), so the Improved Grey Wolf Optimizer (IGWO) is proposed to solve the reactive power optimization problem of the ADN, which can improve the convergence speed of the conventional GWO by changing the level of exploration and development. In addition, a weighted distance strategy is employed in the proposed IGWO to overcome the shortcomings of the conventional GWO. Aiming at the problem that reactive power optimization of an ADN is non-linear and non-convex optimization, a convex model of reactive power optimization of the ADN is proposed, and tested on IEEE33 nodes and IEEE69 nodes, which verifies the effectiveness of the proposed model. Finally, the experimental results verify that the proposed IGWO runs faster and converges more accurately than the GWO.
The paper presents a concept of a control system for a high-frequency three-phase PWM grid-tied converter (3x400 V / 50 Hz) that performs functions of a 10-kW DC power supply with voltage range of 600÷800 V and of a reactive power compensator. Simulation tests (in PLECS) allowed proper selection of semiconductor switches between fast IGBTs and silicon carbide MOSFETs. As the main criterion minimum amount of power losses in semiconductor devices was adopted. Switching frequency of at least 40 kHz was used with the aim of minimizing size of passive filters (chokes, capacitors) both on the AC side and on the DC side. Simulation results have been confirmed in experimental studies of the PWM converter, the power factor of which (inductive and capacitive) could be regulated in range from 0.7 to 1.0 with THDi of line currents below 5% and energy efficiency of approximately 98.5%. The control system was implemented in Texas Instruments TMS320F28377S microcontroller.