Award: Excellence in science 2013 Engineering 2.12: Electric devices (ARRS 2014). The paper proposes an IM torque control derived from the model in the stator current vector reference frame. The required torque is produced by simultaneously manipulating the magnitude and the rotation speed of the stator current vector thus forcing the rotor flux linkage vector to change implicitly in such a way that overall stability is preserved. Additional control features include maximal torque per ampere ratio in steady state and almost perfect command tracking even if the machine is magnetically saturated.The control adopts a cascaded structure and is based on a partial dynamic inversion of the reduced model that assures existence and uniqueness of the inverse mapping between the required torque, the rotor flux linkage vector and the stator current vector. Singularity at zero rotor flux linkage represents no restriction for the control performance in the admissible machine operating range. The implementation of the proposed control requires the estimation of the torque producing rotor flux component and cascaded stator current controllers. Experimental results confirm the key expectations and show the potential and benefits of the proposed control schemes.
COBISS.SI-ID: 16731414
This work deals with the differential evolution (DE) based method for simultaneous identification of the electric, magnetic and mechanical subsystem parameters of a line-start interior permanent magnet synchronous motor (LSIPMSM). The parameters are determined in the optimization procedure using the dynamic model of the LSIPMSM, the time behavior of voltages, currents and speed measured on the tested LSIPMSM, and the DE which is applied as the optimization tool. During the optimization procedure the DE changes the parameters of the LSIPMSM dynamic model in such a way that the differences between the measured and calculated time behavior of individual state variables is minimized. The paper focuses on the objective function definition, constraints settings for individual parameters, normalisation of parameters, and above all the test and measurement procedures performed on the LSIPMSM, which all together make possible to determine the LSIPMSM dynamic model parameters valid for a broad range of operation, and thus, ensuring proper evaluation of the LSIPMSM%s line-starting capability. Some of the LSIPMSM parameters that can be determined by finite element analysis and experimental methods are compared to the values obtained by the DE, thus validating the DE based approach.
COBISS.SI-ID: 17638166
This paper presents a comparative study of different static hysteresis models coupled to the parametric magneto-dynamic model of soft magnetic steel sheets. Both mathematical and behavioural as well as physically based approaches are discussed with respect to the ability to predict the dynamic hysteresis loop shape and iron loss under arbitrary excitation waveforms. Both current- as well as voltage-driven excitation cases are evaluated. The presented analysis discusses and points out advantages and limitations of the majority of the well-known static hysteresis models. In this way, it supports the selection of adequate hysteresis models for the speci?c application, i.e., smooth excitations, distorted ?ux waveforms, transients, or steady-state regimes. Comparisons against measurements for a M400-50A electrical steel over a wide range of magnetic ?ux density and frequencies for both sinusoidal and arbitrary excitations are analysed. In the analysis hysteresis loop shapes, power losses as well as NRMS errors of individual loop sections are compared.
COBISS.SI-ID: 20246038
This paper deals with an analysis of a middle frequency resistance spot-welding (RSW) system with a dc welding current controlled by a pulse width modulated inverter, which supplies a welding transformer with a full wave recti?er mounted at the secondary. Welding transformers in the automotive industry are usually mounted on the arm of a moving robot, so the weight is important. To achieve the same welding power with a large welding current, the transformer’s weight can be reduced with a higher PWM switching frequency. This higher frequency allows a reduction in the transformer’s iron-core cross section with shorter primary and secondary windings. Unfortunately, the leakage inductances prevent the RSW system from achieving the same nominal welding current at higher frequencies. The frequency-dependent maximum welding current is a characteristic behaviour of the RSW system, which can be determined by sophisticated and time-consuming simulations or with the expensive measurements. The third option presented in this paper is determination of an analytical solution, which allows calculation of the maximum welding current as function of frequency or any parameter of the RSW system circuit model. The analytically calculated frequency-dependent function of the maximum welding current was completely con?rmed by measurements on an industrial RSW system and by numerical simulations.
COBISS.SI-ID: 20664598
One of the major challenges today is assessing the suitability of PV (photovoltaic) systems' installations on buildings' roofs regarding the received solar irradiance. The availability of aerial laser-scanning, namely LiDAR (Light Detection And Ranging), means that assessment can be performed automatically over large-scale urban areas in high accuracy by considering surfaces' topographies, long-term direct and diffuse irradiance measurements, and influences of shadowing. The solar potential metric was introduced for this purpose, however it fails to provide any insights into the production of electrical energy by a specific PV system. Hence, the PV potential metric can be used that integrates received instantaneous irradiance which is then multiplied by the PV system's efficiency characteristics. Many existing PV potential metrics over LiDAR data consider the PV modules' efficiencies to be constant, when in reality they are nonlinear. This paper presents a novel PV potential estimation over LiDAR data, where the PV modules' and solar inverter's nonlinear efficiency characteristics are approximated by modelled functions. The estimated electrical energy production from buildings' roofs within an urban area was extensively analysed by comparing the constant and nonlinear efficiency characteristics of different PV module types and solar inverters. The obtained results were confirmed through measurements performed on an existing PV system.
COBISS.SI-ID: 17543702
With the growing urbanization and environmental concerns over buildings' energy consumption and carbon footprint, the demand for energy-efficient building design is greater than ever. This paper addresses these concerns by presenting a novel method for estimating and optimising the thermal load (i.e. total energy load for heating and cooling) of a building within a real environment, provided by high-resolution LiDAR data, while considering long-term climatological parameters, estimated direct and anisotropic diffuse irradiance, shadowing from surroundings, and terrain topography. In the optimisation part of the method, the building's design is optimised regarding the estimated thermal load. The estimation was validated with the well-established EnergyPlus software. In experiments, a rectangular building's design was optimised on a flat and urban dataset. The effect of a building's design parameters on thermal load was inspected as well. On average, the proposed method improved a building's net heat gain by over 103 kWh/m2 and reduced its thermal load by 234.18 kWh/m2 when compared with the initial building design.
COBISS.SI-ID: 20948246
The optimal dispatching of cascade Hydro Power Plants is known as a complex optimization problem. In order to solve this problem the authors have applied an adapted differential evolution algorithm by using a fixed and dynamic population size. According to the dynamic population size, the proposed algorithm uses novel random and minimum to maximum sort strategy in order to create new populations with decreased or increased sizes. This implementation enables global search with fast convergence. It also uses a multi-core processor, where all the necessary optimization data are sent to the individual core of a central processing unit. The main aim of the optimization process is to satisfy 24 h demand by minimizing the water quantity used per electrical energy produced. This optimization process also satisfies the desired reservoir levels at the end of the day. The models used in this paper were the real parameters' models of eight cascade Hydro Power Plants located in Slovenia (Europe). Also the standard model from the literature is used in order to compare the performance of the adapted optimization algorithm.
COBISS.SI-ID: 17881366
Proliferation of distributed generation units, integrated within the distribution network requires increased attention to their proper placements. In urban areas, buildings' rooftops are expected to have greater involvement in the deployment of PV (photovoltaic) systems. This paper proposes a novel procedure for determining roof surfaces suitable for their installation. The PV potential of roof surfaces is assessed based on Light Detection And Ranging (LiDAR) data and pyrometer measurements. Then, the time-dependent PV generation profiles, electricity distribution network configuration, and time dependent loading profiles are used together over time-steps for selecting those roof surfaces with the highest PV potential, which would lead to the highest reduction of network losses per year. The presented procedure was implemented within a real urban area distribution network. The results obtained confirmed that PV potential assessment could be an insufficient criterion when selecting those roof surfaces suitable for the installation of PV systems. In order to obtain relevant results, network configuration and time-dependent loading and generation profiles must be considered as well.
COBISS.SI-ID: 19317526
This paper proposes a parallelized online optimization of low voltage distribution network (LVDN) operation. It is performed on a Graphics Processing Unit (GPU) by combining the optimization procedure with the load flow method. In the case study, performed for the test LVDN with distributed generators (DGs) and controllable loads, differential evolution optimisation based on a Backward-Forward Sweep load flow method was parallelised on GPU. The goal of online optimization is to keep the LVDN voltage profile within the prescribed limits, to minimize LVDN losses, and to enable demand response functionality. This is achieved by the optimization determined reference values for the controllable load’s operation, and the reactive power generation, and active power curtailment of DGs. The results show that the parallelised GPU implemented optimisation can be significantly faster than similar implementation on a Central Processing Unit (CPU), and is, therefore, suitable for the online optimisation of the presented LVDN.
COBISS.SI-ID: 20280342
Clouds moving at a high speed in front of the Sun can cause step changes in the output power of photovoltaic (PV) power plants, which can lead to voltage fluctuations and stability problems in the connected electricity networks. These effects can be reduced effectively by proper short-term cloud passing forecasting and suitable PV power plant output power control. This paper proposes a low-cost Internet of Things (IoT)-based solution for intra-minute cloud passing forecasting. The hardware consists of a Raspberry PI Model B 3 with a WiFi connection and an OmniVision OV5647 sensor with a mounted wide-angle lens, a circular polarizing (CPL) filter and a natural density (ND) filter. The completely new algorithm for cloud passing forecasting uses the green and blue colors in the photo to determine the position of the Sun, to recognize the clouds, and to predict their movement. The image processing is performed in several stages, considering selectively only a small part of the photo relevant to the movement of the clouds in the vicinity of the Sun in the next minute. The proposed algorithm is compact, fast and suitable for implementation on low cost processors with low computation power. The speed of the cloud parts closest to the Sun is used to predict when the clouds will cover the Sun. WiFi communication is used to transmit this data to the PV power plant control system in order to decrease the output power slowly and smoothly.
COBISS.SI-ID: 20570134