Solar wind
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The paper presents the latest results of the studies of small-scale fluctuations in a turbulent flow of solar wind (SW) using measurements with extremely high temporal resolution (up to 0.03 s) of the bright monitor of SW (BMSW) plasma spectrometer operating on astrophysical SPECTR-R spacecraft at distances up to 350,000 km from the Earth. The spectra of SW ion flux fluctuations in the range of scales between 0.03 and 100 s are systematically analysed. The difference of slopes in low- and high-frequency parts of spectra and the frequency of the break point between these two characteristic slopes was analysed for different conditions in the SW. The statistical properties of the SW ion flux fluctuations were thoroughly analysed on scales less than 10 s. A high level of intermittency is demonstrated. The extended self-similarity of SW ion flux turbulent flow is constantly observed. The approximation of non-Gaussian probability distribution function of ion flux fluctuations by the Tsallis statistics shows the non-extensive character of SW fluctuations. Statistical characteristics of ion flux fluctuations are compared with the predictions of a log-Poisson model. The log-Poisson parametrization of the structure function scaling has shown that well-defined filament-like plasma structures are, as a rule, observed in the turbulent SW flows.
- Klíčová slova
- intermittency, kinetic scales, plasma turbulence, solar wind,
- Publikační typ
- časopisecké články MeSH
An information-theoretic approach for detecting causality and information transfer is used to identify interactions of solar activity and interplanetary medium conditions with the Earth's magnetosphere-ionosphere systems. A causal information transfer from the solar wind parameters to geomagnetic indices is detected. The vertical component of the interplanetary magnetic field (Bz) influences the auroral electrojet (AE) index with an information transfer delay of 10 min and the geomagnetic disturbances at mid-latitudes measured by the symmetric field in the H component (SYM-H) index with a delay of about 30 min. Using a properly conditioned causality measure, no causal link between AE and SYM-H, or between magnetospheric substorms and magnetic storms can be detected. The observed causal relations can be described as linear time-delayed information transfer.
- Klíčová slova
- causality, information transfer, solar wind-magnetosphere–ionosphere system, space weather, time reversal, time series,
- Publikační typ
- časopisecké články MeSH
This Letter shows the first results from the solar wind monitor onboard the Spektr-R spacecraft which measures plasma moments with a time resolution of 31 ms. This high-time resolution allows us to make direct observations of solar wind turbulence below ion kinetic length scales. We present examples of the frequency spectra of the density, velocity, and thermal velocity. Our study reveals that although these parameters exhibit the same behavior at the magnetohydrodynamic scale, their spectra are remarkably different at the kinetic scale.
- Publikační typ
- časopisecké články MeSH
This paper uses enhanced turbulent flow in water-based optimization (TFWO), specifically ETFWO, to achieve optimal power flow (OPF) in electrical networks that use both solar photovoltaic (PV) units and wind turbines (WTs). ETFWO is an enhanced TFWO that alters the TFWO structure through the promotion of communication and collaboration. Individuals in the population now interact with each other more often, which makes it possible to search more accurately in the search area while ignoring local optimal solutions. Probabilistic models and real-time data on wind speed and solar irradiance are used to predict the power output of WT and PV producers. The OPF and solution methods are evaluated using the IEEE 30-bus network. By comparing ETFWO to analogical other optimization techniques applied to the same groups of constraints, control variables, and system data, we can gauge the algorithm's robustness and efficiency in solving OPF. It is shown in this paper that the proposed ETFWO algorithm can provide suitable solutions to OPF problems in electrical networks with integrated PV units and WTs in terms of energy generation costs, improved voltage profiles, emissions, and losses, compared to the traditional TFWO and other proposed algorithms in recent studies.
- Publikační typ
- časopisecké články MeSH
In day-to-day investigations the closest correlation with sudden cardiovascular mortality is displayed by the density of solar wind. An increased mortality is recorded after its brisk rise (in particular after potent proton phenomena) and paradoxically also in case of very low density value. Minor proton phenomena and eruptions with X-ray emission did not influence the mortality in the authors' group. This type of increased solar activity thus should not influence the prognosis of morbidity and mortality from cardiovascular diseases. When mean monthly density values of solar wind are correlated with mortality, the relationship is paradoxically indirect. The rate and temperature of the solar wind does not play any part due to its phase retardation after increased density. The correlation of mean annual values of all parameters of solar wind (i.e. density, velocity and temperature) and mortality is also indirect. There is no explanation so far for the increased mortality during low density levels during the interval between two rises in the course of day-to-day monitoring. For the short-term mortality prognosis thus potent proton phenomena can be used; the effect of very low values of solar wind density will have to be confirmed. The biogenic action of solar wind is obviously more complex than was formerly assumed.
- MeSH
- kardiovaskulární nemoci mortalita MeSH
- lidé MeSH
- náhlá smrt epidemiologie MeSH
- sluneční soustava * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- anglický abstrakt MeSH
- časopisecké články MeSH
- Geografické názvy
- Československo epidemiologie MeSH
This study introduces an enhanced self-adaptive wild goose algorithm (SAWGA) for solving economical-environmental-technical optimal power flow (OPF) problems in traditional and modern energy systems. Leveraging adaptive search strategies and robust diversity capabilities, SAWGA distinguishes itself from classical WGA by incorporating four potent optimizers. The algorithm's application to optimize an OPF model on the different IEEE 30-bus and 118-bus electrical networks, featuring conventional thermal power units alongside solar photovoltaic (PV) and wind power (WT) units, addresses the rising uncertainties in operating conditions, particularly with the integration of renewable energy sources (RESs). The inherent complexity of OPF problems in electrical networks, exacerbated by the inclusion of RESs like PV and WT units, poses significant challenges. Traditional optimization algorithms struggle due to the problem's high complexity, susceptibility to local optima, and numerous continuous and discrete decision parameters. The study's simulation results underscore the efficacy of SAWGA in achieving optimal solutions for OPF, notably reducing overall fuel consumption costs in a faster and more efficient convergence. Noteworthy attributes of SAWGA include its remarkable capabilities in optimizing various objective functions, effective management of OPF challenges, and consistent outperformance compared to traditional WGA and other modern algorithms. The method exhibits a robust ability to achieve global or nearly global optimal settings for decision parameters, emphasizing its superiority in total cost reduction and rapid convergence.
Promoting renewable energy sources, particularly in the solar industry, has the potential to address the energy shortfall in Central Africa. Nevertheless, a difficulty occurs due to the erratic characteristics of solar irradiance data, which is influenced by climatic fluctuations and challenging to regulate. The current investigation focuses on predicting solar irradiance on an inclined surface, taking into consideration the impact of climatic variables such as temperature, wind speed, humidity, and air pressure. The used methodology for this objective is Artificial Neural Network (ANN), and the inquiry is carried out in the metropolitan region of Douala. The data collection device used in this research is the meteorological station located at the IUT of Douala. This station was built as a component of the Douala sustainable city effort, in partnership with the CUD and the IRD. Data was collected at 30-min intervals for a duration of around 2 years, namely from January 17, 2019, to October 30, 2020. The aforementioned data has been saved in a database that underwent pre-processing in Excel and later employed MATLAB for the creation of the artificial neural network model. 80% of the available data was utilized for training the network, 15% was allotted for validation, and the remaining 5% was used for testing. Different combinations of input data were evaluated to ascertain their individual degrees of accuracy. The logistic Sigmoid function, with 50 hidden layer neurons, yielded a correlation coefficient of 98.883% between the observed and estimated sun irradiation. This function is suggested for evaluating the intensities of solar radiation at the place being researched and at other sites that have similar climatic conditions.
- Klíčová slova
- Feed-forward network, Multilayer perceptron, Neural network, Solar radiation,
- Publikační typ
- časopisecké články MeSH
The location and spatial extent of the region populated by the foreshock waves depend on the IMF orientation. We performed a systematic statistical study of wave activity in the frequency range of 0.03 - 0.15 Hz observed during an initial phase of the THEMIS mission. Wave activity is quantified by standard deviations of the IMF magnitude and its components over 10-min intervals. We apply the foreshock coordinate system defined as the angle between the bow shock normal and upstream magnetic field vectors and the distance from the spacecraft to bow shock along the magnetic field line. We have found that the Ultra-low Frequency (ULF) foreshock boundary (a) is well defined in these coordinates, (b) it tends to shift outward with an increasing solar wind bulk speed, and (c) with an increasing Mach number. However, the change of the fluctuation level in the foreshock is not uniform because the increasing solar wind bulk speed enhances the fluctuation level mainly in a close proximity of the bow shock whereas the increasing Mach number leads to an intensification of fluctuation levels at the foreshock boundary.
- Klíčová slova
- ULF wave foreshock boundary, ULF waves, bow shock, foreshock, solar wind,
- Publikační typ
- časopisecké články MeSH
The use of plug-in hybrid electric vehicles (PHEVs) provides a way to address energy and environmental issues. Integrating a large number of PHEVs with advanced control and storage capabilities can enhance the flexibility of the distribution grid. This study proposes an innovative energy management strategy (EMS) using an Iterative map-based self-adaptive crystal structure algorithm (SaCryStAl) specifically designed for microgrids with renewable energy sources (RESs) and PHEVs. The goal is to optimize multi-objective scheduling for a microgrid with wind turbines, micro-turbines, fuel cells, solar photovoltaic systems, and batteries to balance power and store excess energy. The aim is to minimize microgrid operating costs while considering environmental impacts. The optimization problem is framed as a multi-objective problem with nonlinear constraints, using fuzzy logic to aid decision-making. In the first scenario, the microgrid is optimized with all RESs installed within predetermined boundaries, in addition to grid connection. In the second scenario, the microgrid operates with a wind turbine at rated power. The third case study involves integrating plug-in hybrid electric vehicles (PHEVs) into the microgrid in three charging modes: coordinated, smart, and uncoordinated, utilizing standard and rated RES power. The SaCryStAl algorithm showed superior performance in operation cost, emissions, and execution time compared to traditional CryStAl and other recent optimization methods. The proposed SaCryStAl algorithm achieved optimal solutions in the first scenario for cost and emissions at 177.29 €ct and 469.92 kg, respectively, within a reasonable time frame. In the second scenario, it yielded optimal cost and emissions values of 112.02 €ct and 196.15 kg, respectively. Lastly, in the third scenario, the SaCryStAl algorithm achieves optimal cost values of 319.9301 €ct, 160.9827 €ct and 128.2815 €ct for uncoordinated charging, coordinated charging and smart charging modes respectively. Optimization results reveal that the proposed SaCryStAl outperformed other evolutionary optimization algorithms, such as differential evolution, CryStAl, Grey Wolf Optimizer, particle swarm optimization, and genetic algorithm, as confirmed through test cases.
The interaction between interplanetary shocks or planetary bow shock and upstream magnetohydrodynamics (MHD) waves (hereafter referred to as wave-shock interactions) is of fundamental importance to plasma physics. Linear waves and shocks, which are supported by MHD framework, are ubiquitous in almost all plasma environments. A thorough understanding of the interaction between linear waves and shocks is useful not only for heliophysics and astrophysics but also for other applications such as inertial confinement fusion. We revisit the theoretical problem of shock-wave interaction based on the linearized boundary conditions of MHD. The shock is regarded as an ideal discontinuity and individual wave modes are considered to impact the shock from upstream. The wavevectors and amplitudes of the downstream transmitted waves are calculated. We further develop a method to apply the theory directly to in-situ heliospheric shock observations. The validity of the method is demonstrated through the example of a fast-forward interplanetary shock observed at 1 AU.
- Klíčová slova
- heliosphere, magnetohydrodynamics, shocks, solar wind,
- Publikační typ
- časopisecké články MeSH
