Technical University of Sofia

The development of energy management tools for next-generation PhotoVoltaic (PV) installations, including storage units, provides flexibility to distribution system operators. In this paper, the aggregation and implementation of these determinist energy management methods for business customers in a microgrid power system are presented. This paper proposes a determinist energy management system for a microgrid, including advanced PV generators with embedded storage units and a gas microturbine. The system is organized according to different functions and is implemented in two parts: a central energy management of the microgrid and a local power management at the customer side. The power planning is designed according to the prediction for PV power production and the load forecasting. The central and local management systems exchange data and order through a communication network. According to received grid power references, additional functions are also designed to manage locally the power flows between the various sources. Application to the case of a hybrid supercapacitor battery-based PV active generator is presented.

Abstract:- The attempts for solving linear inseparable problems have led to different variations on the number of layers of neurons and activation functions used. The backpropagation algorithm is the most known and used supervised learning algorithm. Also called the generalized delta algorithm because it expands the training way of the adaline network, it is based on minimizing the difference between the desired output and the actual output, through the downward gradient method (the gradient tells us how a function varies in different directions). Training a multilayer perceptron is often quite slow, requiring thousands or tens of thousands of epochs for complex problems. The best known methods to accelerate learning are: the momentum method and applying a variable learning rate. The paper presents the possibility to control the induction driving using neural systems. Key-Words:- Backpropagation algorithm, Gradient method, Multilayer perceptron, Induction driving. 1

In this paper risk identification is investigated as a basic stage in risk management. The risk identification phase as the first stage in the risk management process is presented and its leading role for effective risk management is proved. The basic terms that are necessary for building of the frame approach for risk identification are defined: sources of risk‐hazard, factor‐peril‐resources exposed to risk. A classification of risk sources – physical, social, political, operational, economic, legal and cognitive environment – is proposed. It allows covering all types of risk facing the organisation. A grouping of the resources exposed to risk such as physical, human, and financial resources is introduced. It is based on a practical consideration of the risk situations in the organisations.

, the patterns through which heterogenous TP53 (encoding human p53) mutant genomes emerge and influence tumorigenesis remain poorly understood. Here, in a mouse model of pancreatic ductal adenocarcinoma that reports sporadic p53 loss of heterozygosity before cancer onset, we find that malignant properties enabled by p53 inactivation are acquired through a predictable pattern of genome evolution. Single-cell sequencing and in situ genotyping of cells from the point of p53 inactivation through progression to frank cancer reveal that this deterministic behaviour involves four sequential phases-Trp53 (encoding mouse p53) loss of heterozygosity, accumulation of deletions, genome doubling, and the emergence of gains and amplifications-each associated with specific histological stages across the premalignant and malignant spectrum. Despite rampant heterogeneity, the deletion events that follow p53 inactivation target functionally relevant pathways that can shape genomic evolution and remain fixed as homogenous events in diverse malignant populations. Thus, loss of p53-the 'guardian of the genome'-is not merely a gateway to genetic chaos but, rather, can enable deterministic patterns of genome evolution that may point to new strategies for the treatment of TP53-mutant tumours.

BACKGROUND: Modern biomedical amplifiers have a very high common mode rejection ratio. Nevertheless, recordings are often contaminated by residual power-line interference. Traditional analogue and digital filters are known to suppress ECG components near to the power-line frequency. Different types of digital notch filters are widely used despite their inherent contradiction: tolerable signal distortion needs a narrow frequency band, which leads to ineffective filtering in cases of larger frequency deviation of the interference. Adaptive filtering introduces unacceptable transient response time, especially after steep and large QRS complexes. Other available techniques such as Fourier transform do not work in real time. The subtraction procedure is found to cope better with this problem. METHOD: The subtraction procedure was developed some two decades ago, and almost totally eliminates power-line interference from the ECG signal. This procedure does not affect the signal frequency components around the interfering frequency. Digital filtering is applied on linear segments of the signal to remove the interference components. These interference components are stored and further subtracted from the signal wherever non-linear segments are encountered. RESULTS: Modifications of the subtraction procedure have been used in thousands of ECG instruments and computer-aided systems. Other work has extended this procedure to almost all possible cases of sampling rate and interference frequency variation. Improved structure of the on-line procedure has worked successfully regardless of the multiplicity between the sampling rate and the interference frequency. Such flexibility is due to the use of specific filter modules. CONCLUSION: The subtraction procedure has largely proved advantageous over other methods for power-line interference cancellation in ECG signals.

The purpose of the current Letter is to give some relations between gravitational lensing in the strong-deflection limit and the frequencies of the quasinormal modes of spherically symmetric, asymptotically flat black holes. On the one side, the relations obtained can give a physical interpretation of the strong-deflection limit parameters. On the other side, they also give an alternative method for the measurement of the frequencies of the quasinormal modes of spherically symmetric, asymptotically flat black holes. They could be applied to the localization of the sources of gravitational waves and could tell us what frequencies of the gravitational waves we could expect from a black hole acting simultaneously as a gravitational lens and a source of gravitational waves.

In order to take full advantage of distributed generators, an evolution of the classical power system organization and management is also necessary. An aggregator of a residential urban electrical network can be considered by the distribution system operator as a stakeholder, which is able to control a cluster of local generators and loads with technical constraints for the connection with the remaining distribution grid and commercial contracts with outer electrical producers. This paper is focused on the design of the microgrid central energy management system which relies on a day-ahead operational planning and an online adjustment procedure during the operation. A dynamic programming-based algorithm is derived to solve the unit commitment problem with a multiobjective function in order to reduce the economic cost and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> equivalent emissions. The proposed energy management system is implemented into a supervisory control and data acquisition (SCADA) and tested by using a hardware-in-the-loop simulation of the urban network. Economic and environmental gains are evaluated.

In this paper, we present a mathematical model and adaptive controller for an autonomous vehicle overtaking maneuver. We consider the problem of an autonomous three-phase overtaking without the use of any roadway marking scheme or intervehicle communication. The developed feedback controller requires information for the current relative intervehicle position and orientation, which are assumed to be available from onboard sensors. We apply standard robotic nomenclature for translational and rotational displacements and velocities and propose a general kinematic model of the vehicles and the relative intervehicle kinematics during the overtaking maneuver. The overtaking maneuver is investigated as a tracking problem with respect to desired polynomial virtual trajectories for every phase, which are generated in real time. An update control law for the automated overtaking vehicle is designed that allows tracking the desired trajectories in the presence of unknown velocity of the overtaken vehicle. Simulation results illustrate the performance of the proposed controller.

Ambient-assisted living (AAL) is promising to become a supplement of the current care models, providing enhanced living experience to people within context-aware homes and smart environments. Activity recognition based on sensory data in AAL systems is an important task because 1) it can be used for estimation of levels of physical activity, 2) it can lead to detecting changes of daily patterns that may indicate an emerging medical condition, or 3) it can be used for detection of accidents and emergencies. To be accepted, AAL systems must be affordable while providing reliable performance. These two factors hugely depend on optimizing the number of utilized sensors and extracting robust features from them. This paper proposes a generic feature engineering method for selecting robust features from a variety of sensors, which can be used for generating reliable classification models. From the originally recorded time series and some newly generated time series [i.e., magnitudes, first derivatives, delta series, and fast Fourier transformation (FFT)-based series], a variety of time and frequency domain features are extracted. Then, using two-phase feature selection, the number of generated features is greatly reduced. Finally, different classification models are trained and evaluated on an independent test set. The proposed method was evaluated on five publicly available data sets, and on all of them, it yielded better accuracy than when using hand-tailored features. The benefits of the proposed systematic feature engineering method are quickly discovering good feature sets for any given task than manually finding ones suitable for a particular task, selecting a small feature set that outperforms manually determined features in both execution time and accuracy, and identification of relevant sensor types and body locations automatically. Ultimately, the proposed method could reduce the cost of AAL systems by facilitating execution of algorithms on devices with limited resources and by using as few sensors as possible.

Mathematical backgrounds tolerance analysis of linear electric circuits - global optimization approach linear circuit tolerance analysis - linear interval system approach stability of linear circuits with interval parameters transient analysis of linear circuits with interval data analysis of nonlinear electric circuits.

The purpose of this study is to appraise the integration or convergence issues influencing the mutual functioning of blockchain, AI, and IoT. The study argued that the recent developments in the field of IoT and blockchain prediction have involved the integration of innumerable classification schemes to establish a hybrid model. The introduction of the hybrid technique relies on the prediction performance that strives to override the limitations of any available architectural scheme. This study offers a comprehensive exploratory appraisal of the issues influencing the successful integration of IoT and blockchain in regards to functionality and effectiveness of security, trust, and flawless communication issues. The exploratory research methodology was used in analyzing the issues affecting the integration of blockchain, artificial intelligence (AI), and the internet of things (IoT). The findings indicated that the integration challenges influencing the effective operations of blockchain, AI, and IoT as a single system involve security, scalability, accountability, and trust of communications. The study recommends that successful and effective integration will enhance the development of new business models as well as the digital transformation of market corporations. Accordingly, new approaches to convergence should ensure that executives address the new technology demands to obtain significant gains in efficiency.

An analysis of the momentum conservation equations of a redundant free-flying spacecraft/manipulator system acting in a zero-gravity environment is presented. In order to follow a predefined end-effector path, the inverse kinematics at velocity level is considered. The redundancy is solved alternatively in terms of pseudoinverses and null-space components of the manipulator inertia matrix, the manipulator Jacobian matrix, and the generalized Jacobian matrix. A general manipulation task is defined as end-effector continuous path tracking with simultaneous attitude control of the spacecraft. Three subtasks of the general task are considered. The case of manipulator motions that yield no spacecraft attitude disturbance is analyzed in more detail and a special 'fixed-attitude-restricted' (FAR) Jacobian is defined. Through singular-value decomposition of this Jacobian, corresponding FAR dexterity measures (FAR manipulability and FAR condition number) are derived.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper describes the theoretical and experimental results achieved in optimizing the application of the series loaded series resonant converter for contactless energy transfer. The main goal of this work is to define the power stage operation mode that guarantees the highest possible efficiency. The results suggest a method to select the physical parameters (operation frequency, characteristic impedance, transformer ratio, etc.) to achieve that efficiency improvement. The research clarifies also the effects of the physical separation between both halves of the ferromagnetic core on the characteristics of the transformer. It is shown that for practical values of the separation distance, the leakage inductance, being part of the resonant inductor, remains almost unchanged. Nevertheless, the current distribution between the primary and the secondary windings changes significantly due to the large variation of the magnetizing inductance. An approximation in the circuit analysis permits to obtain more rapidly the changing values of the converter parameters. The analysis results in a set of equations which solutions are presented graphically. The graphics show a shift of the best efficiency operation zone, compared to the converter with an ideally coupled transformer. Experimental results are presented confirming that expected tendency.

The paper presents the most comprehensive and large-scale global study to date on how higher education students perceived the use of ChatGPT in early 2024. With a sample of 23,218 students from 109 countries and territories, the study reveals that students primarily used ChatGPT for brainstorming, summarizing texts, and finding research articles, with a few using it for professional and creative writing. They found it useful for simplifying complex information and summarizing content, but less reliable for providing information and supporting classroom learning, though some considered its information clearer than that from peers and teachers. Moreover, students agreed on the need for AI regulations at all levels due to concerns about ChatGPT promoting cheating, plagiarism, and social isolation. However, they believed ChatGPT could potentially enhance their access to knowledge and improve their learning experience, study efficiency, and chances of achieving good grades. While ChatGPT was perceived as effective in potentially improving AI literacy, digital communication, and content creation skills, it was less useful for interpersonal communication, decision-making, numeracy, native language proficiency, and the development of critical thinking skills. Students also felt that ChatGPT would boost demand for AI-related skills and facilitate remote work without significantly impacting unemployment. Emotionally, students mostly felt positive using ChatGPT, with curiosity and calmness being the most common emotions. Further examinations reveal variations in students' perceptions across different socio-demographic and geographic factors, with key factors influencing students' use of ChatGPT also being identified. Higher education institutions' managers and teachers may benefit from these findings while formulating the curricula and instructions/regulations for ChatGPT use, as well as when designing the teaching methods and assessment tools. Moreover, policymakers may also consider the findings when formulating strategies for secondary and higher education system development, especially in light of changing labor market needs and related digital skills development.

Abstract Digital marketing is an integral part of the process of digital business transformation. It incorporates new marketing techniques that are based on information and communication technologies. For this reason, its application in practice is a prerequisite for the successful development of the business in the contemporary market conditions. The object of this paper is the digital marketing and the subject is the digital marketing advantages and disadvantages. The first purpose of this paper is to systemize the various terms for digital marketing used in the specialized literature and the Internet and to show the differences between them. The second is to present the characteristics of the main advantages and disadvantages of digital marketing. Knowing them in depth, companies will be able to develop effective digital marketing strategies that have high potential to achieve company goals and at the same time are suitable to their profile. Thereby, they will be able to determine to what extent and which tools of the whole digital marketing palette are best suited to their marketing activities.

Abstract A review on recent development in self‐consistent description of high‐frequency discharges is presented. The discussions are based on fluid models of travelling‐wave‐sustained plasmas and results for the axial structure of discharges in different gases. (© 2004 WILEY‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim)

The influence is studied of Co-Ti substituted Ba hexaferrite on the efficiency of the hexaferrite-magnetite-graphite triple absorbing system of fillers dispersed in a rubber matrix. Using the planned experiment technique, the optimal ratio is determined of its components, as well as their influence on the absorber's optimal thickness. The introduction of a hexaferrite in the system improves the composite absorbing properties manifested mostly in broadening the maximal absorption frequency band. It is assumed that the presence of the hexaferrite results in improving the long-range order of the absorbing fillers arrangement in the polymer matrix.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

SUMMARY In this paper, we study the problem of global exponential stability for impulsive cellular neural networks with time‐varying delays and supremums. Using Young's inequality and Lyapunov‐like functions, new stability criteria are proved. Because supremums and impulses are relevant in various contexts, including problems in the theory of automatic control, our results can be applied in the qualitative investigations of many practical problems of diverse interest. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Ultrasonic sensors allow us to equip robots with a means of perceiving surrounding objects, an alternative to technical vision. Humanoid robots, like robots of other types, are, first, equipped with sensory systems similar to the senses of a human. However, this approach is not enough. All possible types and kinds of sensors should be used, including those that are similar to those of other animals and creations (in particular, echolocation in dolphins and bats), as well as sensors that have no analogues in the wild. This paper discusses the main issues that arise when working with the HC-SR04 ultrasound rangefinder based on the STM32VLDISCOVERY evaluation board. The characteristics of similar modules for comparison are given. A subroutine for working with the sensor is given.

The cryogenic industry has experienced remarkable expansion in recent years. Cryogenic technologies are commonly used for industrial processes, such as air separation and natural gas liquefaction. Another recently proposed and tested cryogenic application is Liquid Air Energy Storage (LAES). This technology allows for large-scale long-duration storage of renewable energy in the power grid. One major advantage over alternative storage techniques is the possibility of efficient integration with important industrial processes, e.g., refrigerated warehousing of food and pharmaceuticals. Heat exchangers are among the most important components determining the energy efficiency of cryogenic systems. They also constitute the necessary interface between a LAES system and the industrial process utilizing the available cooling effect. The present review aims to familiarise energy professionals and stakeholders with the latest achievements, innovations, and trends in the field of cryogenic heat exchangers, with particular emphasis on their applications to LAES systems employing renewable energy resources. Important innovations in coil-wound and plate-fin heat exchanger design and simulation methods are reviewed among others, while special attention is given to regenerators as a prospective component of cryogenic energy storage systems. This review also reveals that the geographical spread of research and development activities has recently expanded from well-established centers of excellence to rather active emerging establishments around the globe.