astronomy

Smart Cities EMC Network for Training

Smart Cities EMC Network for Training is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Smart Cities EMC Network for Training rather than just read about it. In short: The Smart Cities EMC Network for Training (SCENT) is a project funded by the European Union's Horizon 2020 research program under the Marie Skłodowska-Curie grant agreement No 812391. It is a Ph.D training network program in the field of Electromagnetic Compatibility (EMC) especially in the smart cities application.

Key takeaways

Smart Cities EMC Network for Training belongs to astronomy; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Smart Cities EMC Network for Training to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Smart Cities EMC Network for Training from memory before moving on to harder problems.

Reference excerpt

The Smart Cities EMC Network for Training (SCENT) is a project funded by the European Union's Horizon 2020 research program under the Marie Skłodowska-Curie grant agreement No 812391. It is a Ph.D training network program in the field of Electromagnetic Compatibility (EMC) especially in the smart cities application. Three universities (the University of Twente, the University of Nottingham, the University of Zielona Góra) and twelve industries collaborate in SCENT project. Supported by the IEEE EMC Society Technical Committee 7: ("Low-Frequency EMC") besides Ph.D training program, SCENT project also performs scientific training programs and social outreach programs.

History The initiative began in 2018 with the aim of finding solutions to power quality (PQ) problems arising from conducted electromagnetic interference (EMI) from integrated electrical power system equipment that are becoming smart (Smart Cities). The European Union started SCENT project at 1 September 2018 as part of the H2020-EU. 1.3.1 under ITN scheme. The H2020-EU.1.3.1 is an EU collaborative program to foster new skills by means of initial training of researchers. The CORDIS EU commission stated, as the part of Horizon 2020 program, the SCENT project is designated to support the optimization of power distribution networks inside buildings and industrial plants and transport networks with respect to compatibility (no interference) and efficiency. The SCENT project implement in 4 years and end on 31 August 2022.

Objectives The SCENT project was established to carry out doctorate training, scientific training, and social activities in collaboration with universities, research institutions, and non-academic organisations. In order to achieve this general objective, the SCENT project divides their work into several detailed projects called Work Packages.

Management Objective: Efficient project execution, including finance, reporting and maintaining the relationship between the SCENT stakeholders.

Training Objective: Create a European Doctoral/Graduate School for EMC, especially on conducted emissions, susceptibility and harmonics.

Dissemination and exploration Objective: Disseminate the SCENT's findings to the European academic, educational, industrial, and public groups. Integrate the SCENT doctoral program into established graduate programs.

Outreach Objective: Disseminate the SCENT's findings to the public.

Behavioral modelling and simulation of connected devices Objective: Developed new models and simulated several load conditions connected to grids.

Statistical and probabilistic modelling and simulation Objective: Develop validated models and simulations of power distribution grids for EMC and power quality assessment.

Measurement and monitoring, experimental evaluation of equipment and network Objective: To characterize and evaluate the distribution network and its interconnected equipment with experiment or measurement.

System topology and interaction, compensation and corrective Objective: To provide a verified set of tools and determine the risk of electromagnetic interference in complex systems by employing statistical approach.

Activities All of the SCENT activities are the result of collaboration between the University of Twente (UT), the University of Zielona Gora (UZ) the University of Nottingham (UN) and industries. Based on MSCA-ITN-EJD-European Join Doctoral scheme each Early Stage Researcher (ESR) of SCENT must study and take courses at these three Universities. Besides academic activities, the SCENT also involves in several activities including the ICT COST Action in Prague in 2019, the APEMC in Sapporo Japan in 2019, the EMC Europe in Barcelona Spain in 2019, Summer School at University of Twente in 2019, SENE conference in Łódź in 2019, APEMC in Sydney Australia in 2020, ETOPIA Workshop in 2020, IEEE EMC+SIPI virtual conference in 2020, ENEA workshop in Poland in 2020, IEEE EMC+SIPI in Glasgow in 2021, SCENT Summer School II in Zielona Gora Poland in 2021, ETOPIA Summer School II in Politechnico di Milan Italy in 2021, APEMC Bali in Indonesia in 2021 and Girls Day at University of Twente in 2022 as an outreach activity.

Partners European Union Universities

The University of Twente The University of Nottingham The University of Zielona Góra Industries

Siemens Motion Control Ursus Lambda Engineering Eko Energetyka Thales Enea Operator Network Rail Solaris RH Marine Atkins Tauron Jaguar Land Rover Other partners

IEEE EMC Society, Technical Committee (TC7) Nederlandse EMC-ESD Vereniging (EMC-ESD)

References

Illustrations

Worked examples

Example 1 — a first encounter with Smart Cities EMC Network for Training

Start with the simplest possible case. Write down what Smart Cities EMC Network for Training claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Smart Cities EMC Network for Training before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Smart Cities EMC Network for Training ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Smart Cities EMC Network for Training

In research: Smart Cities EMC Network for Training appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Smart Cities EMC Network for Training in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Smart Cities EMC Network for Training is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2018 establishments in Europe, College and university associations and consortia in Europe, Electromagnetic compatibility, so understanding it makes those chapters shorter.
In everyday life: Look for Smart Cities EMC Network for Training outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Smart Cities EMC Network for Training in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Smart Cities EMC Network for Training means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Smart Cities EMC Network for Training out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Smart Cities EMC Network for Training in simple terms?

Why does Smart Cities EMC Network for Training matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Smart Cities EMC Network for Training?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Smart Cities EMC Network for Training.