The paper presents a new method for simultaneous tracking of varying grid impedance and its uncertainty bounds. Impedance tracking consists of two stages. In the first stage, the actual noise estimate is obtained from least squares (LS) residua. In the second stage, the noise covariance matrix is approximated with the use of residual information. Then weighted least squares (WLS) method is applied in order to estimate impedance and background voltage. Finally uncertainty bounds for impedance estimation are computed. The robustness of the method has been verified using simulated signals. The proposed method has been compared to sliding LS. The results have shown, that the method performs much better than the LS for all considered cases, even in the presence of significant background voltage variations.
A solar photovoltaic (PV) system has been emerging out as one of the greatest potential renewable energy sources and is contributing significantly in the energy sector. The PV system depends upon the solar irradiation and any changes in the incoming solar irradiation will affect badly on the output of the PV system. The solar irradiation is location specific and also the atmospheric conditions in the surroundings of the PV system contribute significantly to its performance. This paper presents the cumulative assessment of the four MPPT techniques during the partial shading conditions (PSCs) for different configurations of the PV array. The partial shading configurations like series-parallel, bridge link, total cross tied and honeycomb structure for an 8#2;4 PV array has been simulated to compare the maximum power point tracking (MPPT) techniques. The MPPT techniques like perturb and observe, incremental conductance, extremum seeking control and a fuzzy logic controller were implemented for different shading patterns. The results related to the maximum power tracked, tracking efficiency of each of the MPPT techniques were presented in order to assess the best MPPT technique and the best configuration of the PV array for yielding the maximum power during the PSCs.
Recently, the search for new effective energy production solutions has been focused on the production of electricity using renewable and environmentally friendly carriers. This resulted in an increased interest in PV cells and cogeneration systems. The article looks at the main factors affecting their operational parameters against the background of the development history of subsequent generations of PV cells. Average daily solar radiation and wind velocity in Lodz were characterized. The research was done on a static and tracking system with a total peak power of 15 kWp and a 30 kW microturbine. PV panels are installed on the building of the Institute of Electrical Power Engineering of the Lodz University of Technology and they work as part of DERLab. A microturbine is inside the building. Energy measurements were carried out in 2016 giving grounds for the analysis of energy efficiency and financial analysis of the energy supply in buildings. Energy yields in the static and tracking system as well as percentage coverage of electricity from PV cells and microturbines were assessed. The distribution of monthly savings, annual savings of energy costs and the payback time of the investment costs of the systems subject to the test were determined. The research we have done allows us to say that the energy produced by follow-up modules is about 3 times greater than that generated in stationary modules. On the other hand, the annual savings of energy costs using gas micro-turbines are about 10 times higher than those of lagging panels. The analysis shows that it is possible to determine the profitability of the microturbine and photovoltaic panels use despite large financial outlays. The payback period of investment outlays is about 12 years when using the installation throughout the year.
Blockchain is a technology, which could revolutionize many industries in the future. A system like that is based on a chain of blocks that is used for storing and transferring various data, forming a decentralized ledger. Although various fundamental projects based on the blockchain system in the energy industry are in their early stage of development, as well as other solutions, applications of blockchain technology in the broadly understood power engineering sector are considered to have a very large potential. This paper presents a brief description of the blockchain technology, its general operating principle and the possibilities it brings. The next section of the article contains a characterization of two exemplary and possible blockchain technology applications, which in the perspective of time may have a significant impact on the power engineering sector. The first solution is related to carrying out energy transactions, which could be conducted in an easy way directly between energy producers and consumers. Thanks to blockchain technology, this could lead to a partial decentralization in that area. The second proposed example concerns energy resources origin tracking, which would allow fixed origin attributes and parameters affecting the environment to be assigned to the generated energy. By implementing that solution, it would be possible to construct a fuel footprint of individual generating units. The article also mentions examples of other potential applications of blockchain technology in the power engineering sector.
In multi-axis motion control systems, the tracking errors of single axis load and the contour errors caused by the mismatch of dynamic characteristics between the moving axes will affect the accuracy of the motion control system. To solve this issue, a biaxial motion control strategy based on double-iterative learning and cross-coupling control is proposed. The proposed control method improves the accuracy of the motion control system by improving individual axis tracking performance and contour tracking performance. On this basis, a rapid control prototype (RCP) is designed, and the experiment is verified by the hardware and software platforms, LabVIEW and Compact RIO. The whole design shows enhancement in the precision of the motion control of the multiaxis system. The performance in individual axis tracking and contour tracking is greatly improved.
This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS-PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.