Search Results (6)

This review paper describes and compares the practical methods that make it possible to calculate an average value of apparent, active, and reactive (i.e., blind and distorted) power in each calculation step. In addition to two methods, $p–q$ and $ip–iq$, it deals with the application of the $id–iq$ method for determining power components’ mean values in a discrete step. The results are important and needed for the right dimensioning and sizing of power electronic and electrical systems (PEESs), which those power components produce. This is because the integral calculation for the mean values of the product of voltage u(t) and current i(t) always gives a value lower than the actual value of the apparent power. Using moving average and moving root mean square (rms) techniques (or digital filtering), one obtains the right values, although with a time delay. Using sliding filtering, these techniques calculate the average or rms values, respectively, of the power components in each step k. By calculating the moving average value of the power components in both transient and steady states (on/off as well), we achieve the correct design of the system. The transients for the three- and single-phase power electronic systems are modeled, simulated, and theoretically supported in this study. Any PEES can be determined and sized using the calculated data. The real-time HW simulator Plecs RT Box 1 and Matlab/Simulink 2024a simulations validate the comprehensive time waveform produced by the suggested method. Full article

The rising electricity costs, cost of space heating, and domestic hot water end up driving consumers toward reducing expenses by generating their electricity through devices like photovoltaic systems and efficient combined heat and power plants. When coupled with thermal systems via an energy management system (EMS) in a Multi-Energy System (MES), this self-produced electricity can effectively lower electricity and heating bills. However, MESs with EMSs can serve various purposes beyond cost reduction via self-consumption, such as reacting to variable electricity prices, meeting special grid connection conditions, or minimizing CO₂ emissions. These diverse strategies create unique prosumer profiles, deviating significantly from standard load profiles. The potential threat to the power grid arises as grid operators lack visibility into which consumers employ which control strategies. This paper investigates the impact of controlled MESs on the power grid compared to average households and answers whether new control strategies affect the planning strategies of low voltage grids. It proposes a comprehensive four-step toolchain for the detailed simulation of thermal–electrical load profiles, MES control strategies, and grid dynamics. It includes a new method for the grid impact analysis of extreme and average bulk values. As a result, this study identifies three primary factors influencing distribution power grids by MESs. Firstly, the presence and scale of photovoltaic (PV) systems significantly affect extreme values in the grid. Secondly, MESs incorporating combined heat and power (CHP) and heat pump (HP) units impact the overall grid performance, mainly reflected in bulk values. Thirdly, the placement of an MES with heating systems, especially when concentrated in one feeder, plays a crucial role in grid dynamics. Despite the three distinct factors identified as impactful on the power grid, this study reveals that the various control strategies, despite leading to vastly different grid profiles, do not exhibit divergent impacts on buses, lines, or transformers. Remarkably, the impact of MESs remains consistently similar across the range of control strategies studied. Therefore, different control strategies do not pose an additional challenge to the grid integration of MESs. Full article

This paper deals with the quasi-instantaneous determination (in a single-step response time) of apparent, active, and reactive (i.e., blind and distortion) power mean values including the total power factor, total harmonic distortion, and phase shift of fundamentals of a power electronic and electrical system (PEES) using the ip-iq method, which is the main contribution of the paper. The power components’ mean values are investigated during the transient and steady states. The power components’ mean values can be determined directly from phase current and voltage quantities, using an integral calculus over one period within the next calculation step and using moving average and moving rms techniques (or digital filtering). Consequently, the power factor can be evaluated with known values of a phase shift of fundamentals (using a Fourier analysis). The results of this study show how a distortion power component during transients is generated even under a harmonic supply and linear resistive–inductive load. The paper contains a theoretical base, modeling, and simulation for the three and single phases of the transients in power electronic systems. The worked-out results can be used to determine and size any PES. The presented approach brings a detailed time waveform verified by simulations in Matlab/Simulink 2022a and the Real-time HW Simulator Plecs RT Box 1. Full article

This paper deals with the quasi-instantaneous determination of an apparent-, active-, and reactive (i.e., blind and distortion) power mean values, including total power factor, total harmonic distortion, and phase shift of fundamentals of power electronic system (PES) using the p-q method. The power components’ mean values are investigated both during transients and steady states. Using an integral calculus over one period and the moving average method (or digital filtering), the power components’ mean values can be determined within the next calculation step directly from phase current and voltage quantities. Consequently, with known values of a phase shift of fundamentals (using Fourier analysis), the power factor can be evaluated. The results of this study show how a distortion power component during transients is generated even under harmonic supplying and linear resistive-inductive load. The paper contains a theoretical base, modeling, and simulation for the 5-, 3-, and 2-phases of PES transients. A system compensated by switched capacitors as well as an active power filter shows a possibility to compensate for distortion and reactive power components in the next calculation step. Worked-out results can be used for the right determination and sizing of any PES. The presented approach brings the detailed time-waveform and improved quality of electrical quantities (time-waveforms), and through quasi-instantaneous (single step) response time of compensation, minimizes nascent overvoltage of the system. Full article

Currently used methods of simulation of doubly fed induction machines (DFIM), especially in real-time simulators (where a relatively large calculation step is used and high adequacy is required), do not provide the required adequacy, especially in rotor electrical circuits. In order to increase the adequacy of reproducing of electrical processes occurring in the circuits of the wound DFIM rotor, this paper presents a proposal and a verification of a new method of real-time simulation. The new method of mathematical modeling of electrical circuits uses voltage averaging at the calculation step. This method was supplemented by prediction of the machine’s rotor angle, which significantly increases the degree of adequacy of reproducing physical quantities present in DFIM, especially in the machine’s rotor. This method allows real-time simulation of electrical systems with a relatively large calculation step (of the order of 200 µs), while maintaining an appropriate degree of adequacy. Full article

In order to improve the performance of the closed-loop Buck converter control system, a compound control scheme based on nonlinear disturbance observer (DO) and nonsingular terminal sliding mode (TSM) was developed to control the Buck converter. The control design includes two steps. First of all, without considering the dynamic and steady-state performances, a baseline terminal sliding mode controller was designed based on the average model of the Buck converter, such that the desired value of output voltage could be tracked. Secondly, a nonlinear DO was designed, which yields an estimated value as the feedforward term to compensate the lumped disturbance. The compound controller was composed of the terminal sliding mode controller as the state feedback and the estimated value as the feedforward term. Simulation analysis and experimental verifications showed that compared with the traditional proportional integral derivative (PID) and terminal sliding mode state feedback control, the proposed compound control method can provide faster convergence performance and higher voltage output quality for the closed-loop system of the Buck converter. Full article