Power transformers thermal modeling using an Enhanced Set-Membership Multivariable Gaussian Evolving Fuzzy System

Knowledge of temperature distribution in power transformers is essential for the management of electrical distribution systems. Monitoring the hot-spot temperature of a power transformer can extend its lifetime. In this work, we present two new models based on Set-Membership filtering: the Set-Membership evolving Multivariable Gaussian and the Enhanced Set-Membership evolving Multivariable Gaussian. Both approaches are acting by adjusting the learning rate in the evolving fuzzy modeling system. To evaluate its performance were applied synthetic data sets, as benchmarks, and data for thermal modeling of real power transformers, under two load conditions: with and without an overload condition. The obtained results are compared with the performance of the original evolving Multivariable Gaussian and with other classical models suggested in the literature. Both proposed models obtained lower errors and presenting a competitive number of rules, suggesting that the models are flexible and efficient approaches in these scenarios.O conhecimento da distribuição de temperatura em transformadores de potência é essencial para o gerenciamento de sistemas de distribuição elétrica. O monitoramento da temperatura do ponto quente de um transformador de energia pode estender sua vida útil. Neste trabalho, apresentamos dois novos modelos baseados na filtragem Set-Membership: o Set-Membership evolutivo Gaussiano Multivariado e o Enhanced Set-Membership evolutivo Gaussiano Multivariado. Ambas as abordagens agem ajustando a taxa de aprendizagem no sistema de modelagem fuzzy evolutivo. Para avaliar seu desempenho foram aplicados conjuntos de dados sintéticos, como benchmarks, e dados para modelagem térmica de transformadores de potência reais, sob duas condições de carga: com e sem sobrecarga. Os resultados obtidos são comparados com o desempenho do modelo evolutivo Gaussiano Multivariado original e com outros modelos clássicos sugeridos na literatura. Ambos os modelos propostos obtiveram erros menores e apresentam número competitivo de regras, sugerindo que os modelos são abordagens flexíveis e eficientes nestes cenários.PROQUALI (UFJF

Adaptivno neizraziti pristup sustavima prediktivne zaštite od preopterećenja transformatora snage

The improving of the utilization factors of mineral-oil-filled power transformers is of critical importance in the competitive market of electricity. Utilities need to change dynamically the loadability rating of transformers without penalizing their serviceability. As a key issue of loadability all aspects of the thermal performance, and in particular those related to the determination of tolerable windings hot-spot temperature (HST), overload practice and its impact on remanent life expectation should be investigated. So, this paper deals with a methodology for the identification of a Takagi-Sugeno-Kang (TSK) fuzzy model able to reproduce the thermal behaviour of large mineral-oil-filled power transformers for implementing a protective overload system. The TSK fuzzy model, working on the load current waveform and on the top oil temperature (TOT), gives an accurate global prediction of the HST pattern. In order to validate the usefulness of the approach suggested herein, some data cases, derived from various laboratory applications, are presented to measure the accuracy and robustness of the proposed fuzzy model.Poboljšanje faktora iskoristivosti transformatora snage punjenih mineralnim uljem od kritične je važnosti na kompetetivnom tržištu električne energije. Zahtijeva se da dinamičke promjene opterećenja transformatora ne utječu na njegovu raspoloživost i pouzdanost. Kako je opteretivost ključna problematika, moraju se istražiti svi aspekti toplinskih svojstava, posebice oni koji se odnose na određivanje dopuštene vršne temperature namota (HST), te učestalost pojave preopterećenja na očekivani životni vijek transformatora. Ovaj se članak bavi metodologijom identifikacije Takagi-Sugeno-Kang (TSK) neizrazitog modela koji može reproducirati temperaturno ponašanje velikih transformatora snage punjenih mineralnim uljem za implementaciju zaštitnog sustava protiv preopterećenja. TSK neizraziti model s praćenjem valnog oblika struje opterećenja i vršne temperature ulja (TOT) daje točnu globalnu predikciju vršne temperature namota. Točnost i robusnost predloženog neizrazitog modela provjereni su na skupovima laboratorijskih podataka kako bi se verificirala korisnost predloženog postupka

Application of Machine Learning Methods for Asset Management on Power Distribution Networks

This study aims to study the different kinds of Machine Learning (ML) models and their working principles for asset management in power networks. Also, it investigates the challenges behind asset management and its maintenance activities. In this review article, Machine Learning (ML) models are analyzed to improve the lifespan of the electrical components based on the maintenance management and assessment planning policies. The articles are categorized according to their purpose: 1) classification, 2) machine learning, and 3) artificial intelligence mechanisms. Moreover, the importance of using ML models for proper decision making based on the asset management plan is illustrated in a detailed manner. In addition to this, a comparative analysis between the ML models is performed, identifying the advantages and disadvantages of these techniques. Then, the challenges and managing operations of the asset management strategies are discussed based on the technical and economic factors. The proper functioning, maintenance and controlling operations of the electric components are key challenging and demanding tasks in the power distribution systems. Typically, asset management plays an essential role in determining the quality and profitability of the elements in the power network. Based on this investigation, the most suitable and optimal machine learning technique can be identified and used for future work. Doi: 10.28991/ESJ-2022-06-04-017 Full Text: PD

Modeling Cascading Failures in Power Systems in the Presence of Uncertain Wind Generation

One of the biggest threats to the power systems as critical infrastructures is large-scale blackouts resulting from cascading failures (CF) in the grid. The ongoing shift in energy portfolio due to ever-increasing penetration of renewable energy sources (RES) may drive the electric grid closer to its operational limits and introduce a large amount of uncertainty coming from their stochastic nature. One worrisome change is the increase in CFs. The CF simulation models in the literature do not allow consideration of RES penetration in studying the grid vulnerability. In this dissertation, we have developed tools and models to evaluate the impact of RE penetration on grid vulnerability to CF. We modeled uncertainty injected from different sources by analyzing actual high-resolution data from North American utilities. Next, we proposed two CF simulation models based on simplified DC power flow and full AC power flow to investigate system behavior under different operating conditions. Simulations show a dramatic improvement in the line flow uncertainty estimation based on the proposed model compared to the simplified DC OPF model. Furthermore, realistic assumptions on the integration of RE resources have been made to enhance our simulation technique. The proposed model is benchmarked against the historical blackout data and widely used models in the literature showing similar statistical patterns of blackout size

Neem oil as biopesticides

Agricultural biotechnology is a wide logical method used to improve plants, animals, and microorganisms. The biotechnology cycle in the agricultural segment incorporates improving the harvests, living things, and microorganism's quality and resistibility by hereditary adjustment. Other than that, biotechnology in agriculture additionally known from the utilization of more secure natural sources to create an item that will be ready to ensure and build the creation of yields and domesticated animals, for example, manure and biopesticides. The World Health Organization (WHO) likewise had reported that the synthetic based pesticides would arrive at their constraints of utilization as it loses their adequacy after some time. This can be shown by the disclosure of pesticides obstruction bugs. The neem plant was accounted for as the top rundown spices that can possibly go about as a biopesticide; this is because of the presence of various dynamic mixes known as limonoids. The significant compound is the azadirachtin which assumes an essential job as bug sprays, and it executes the focused-on bugs by troubling their development and generative system. The neem oil biopesticides additionally are less harmful towards living beings and less contamination toward nature. In this way, the neem removed biopesticides are presently popularized and have been sold and utilized in different nations

Extending the multiphysics modelling of electric machines in a digital twin concept

The digital twin is a trending technology that has been applied to different fields. In this work, the use of the digital twin of electric machines in a life cycle perspective is investigated. It presents a literature review of the main concepts and applications of the digital twin in the field. In addition, it discusses the methodological approach to obtain the digital twin of a static electric machine by using its multiphysics model in a reduced order model, to improve the maintenance scheme and estimate the lifetime of its insulation system based on the machine’s temperature profile.info:eu-repo/semantics/publishedVersio

A Review of Prognostics and Health Management Applications in Nuclear Power Plants

The US operating fleet of light water reactors (LWRs) is currently undergoing life extensions from the original 40-year license to 60 years of operation. In the US, 74 reactors have been approved for the first round license extension, and 19 additional applications are currently under review. Safe and economic operation of these plants beyond 60 years is now being considered in anticipation of a second round of license extensions to 80 years of operation.Greater situational awareness of key systems, structures, and components (SSCs) can provide the technical basis for extending the life of SSCs beyond the original design life and supports improvements in both safety and economics by supporting optimized maintenance planning and power uprates. These issues are not specific to the aging LWRs; future reactors (including Generation III+ LWRs, advanced reactors, small modular reactors, and fast reactors) can benefit from the same situational awareness. In fact, many SMR and advanced reactor designs have increased operating cycles (typically four years up to forty years), which reduce the opportunities for inspection and maintenance at frequent, scheduled outages. Understanding of the current condition of key equipment and the expected evolution of degradation during the next operating cycle allows for targeted inspection and maintenance activities. This article reviews the state of the art and the state of practice of prognostics and health management (PHM) for nuclear power systems. Key research needs and technical gaps are highlighted that must be addressed in order to fully realize the benefits of PHM in nuclear facilities

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

Simulation and optimization model for the construction of electrical substations

One of the most complex construction projects is electrical substations. An electrical substation is an auxiliary station of an electricity generation, transmission and distribution system where voltage is transformed from high to low or the reverse using transformers. Construction of electrical substation includes civil works and electromechanical works. The scope of civil works includes construction of several buildings/components divided into parallel and overlapped working phases that require variety of resources and are generally quite costly and consume a considerable amount of time. Therefore, construction of substations faces complicated time-cost-resource optimization problems. On another hand, the construction industry is turning out to be progressively competitive throughout the years, whereby the need to persistently discover approaches to enhance construction performance. To address the previously stated afflictions, this dissertation makes the underlying strides and introduces a simulation and optimization model for the execution processes of civil works for an electrical substation based on database excel file for input data entry. The input data include bill of quantities, maximum available resources, production rates, unit cost of resources and indirect cost. The model is built on Anylogic software using discrete event simulation method. The model is divided into three zones working in parallel to each other. Each zone includes a group of buildings related to the same construction area. Each zone-model describes the execution process schedule for each building in the zone, the time consumed, percentage of utilization of equipment and manpower crews, amount of materials consumed and total direct and indirect cost. The model is then optimized to mainly minimize the project duration using parameter variation experiment and genetic algorithm java code implemented using Anylogic platform. The model used allocated resource parameters as decision variables and available resources as constraints. The model is verified on real case studies in Egypt and sensitivity analysis studies are incorporated. The model is also validated using a real case study and proves its efficiency by attaining a reduction in model time units between simulation and optimization experiments of 10.25% and reduction in total cost of 4.7%. Also, by comparing the optimization results by the actual data of the case study, the model attains a reduction in time and cost by 13.6% and 6.3% respectively. An analysis to determine the effect of each resource on reduction in cost is also presented