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Internship in eSmart Systems

We have been fortunate to have Christian Børke working with us this January. In this blog post he describes what it is like to be an intern in eSmart Systems.

What is it like being an intern at eSmart Systems?

As a MSc student at Norwegian School of Economics with a major in Energy, Natural Resources and the Environment, eSmart Systems was a natural place to apply for an internship.On my first day, I was instantly greeted by smiling faces and a lot of help to get into the swing of things. Working as an intern for a short period of four weeks can sometimes seem a bit chaotic, as there is a lot of information to read up on and concepts to grasp on a short notice. Thus, any help in settling in and understanding the business model and market early on is of great help. My internship period has been hectic, varied and very enjoyable so far!

How does a regular day look like?

Although no day is the same at eSmart, a regular day at the office for my internship period starts at around 9 am with a fresh cup of coffee and lasts to 5 pm. Typically, I either attend meetings with customers or other eSmarter´s, work with reports and presentations or solve other tasks that are of relevance to the business development part of the company.

What tasks have you been performing?

I have been working in the Business Development department close to the management group. My task is mainly creating value propositions that can be presented for customers of eSmart´s Connected Grid software. Furthermore, with the large industrial player Kongsberg Digital investing 100 million NOK in eSmart, I have been attending strategic meetings and workshops hosted by consulting firm McKinsey at Kongsberg´s offices in Trondheim twice, and also attended product demo’s at customers. This has helped me learn more about the business environment eSmart is currently in, but also future possibilities in other markets and niches.

In the two last weeks of my internship I will be concluding my work and learning experience by looking at three important areas that can provide value on the balance sheet for the customers through the use of Connected Grid. This will be presented through a report. Although four weeks is a short time to conclude with anything, scratching the surface of all the advantages Connected Grid gives customers is definitely possible!

What´s the most exciting thing about an internship at eSmart Systems?

Working in a fast paced and engaging environment with forward looking solutions and technologies every day is highly motivational. Combining my studies in the areas of renewable energy sources, electricity market design and sustainability from an economical perspective with the more technical aspects of digitalization and software products also provide insight to areas that aren´t normally discussed in lectures at school.

Any tips for students considering applying for an internship in eSmart Systems?

Jump right into it! As an intern at eSmart you are included in a great work environment from day one, are offered exciting tasks and responsibilities and get to work with something that actually has an environmental impact. That combination is not something you will get at many other companies.

An introduction to the Big Data Landscape

What is Big Data?

Data has always been an important asset in every industry. Since the early days of the information age, business intelligence and descriptive statistics have been used as the standard tools for extracting information and make important decisions from all kinds of collected data. However, as the cost of collecting, storing, and processing data has been dropping exponentially, the amount and the diversity of the data has reached the point where traditional approaches are no longer feasible. In fact, the term Big Data is often used to refer to any data that requires new techniques and tools in order for it to be processed and analyzed.

A more formal definition of Big Data was introduced by Gartner in 2012, in which the well-known 3Vs – Volume, Velocity, and Variety – were used to characterize Big Data. Since then, the 3Vs model has been expanded to several other characteristics, including a fourth V for Veracity and more recently a fifth for Value. Without going into the details of each V, and resisting the temptation to look for a sixth V, we could also look at Big Data from the point of view of the new set of technologies that are helping to solve the challenges in collecting, managing, and analyzing Big Data. These technologies include cloud computing and cluster computing (with Hadoop MapReduce as the most well-known example) for data storage and manipulation, and machine learning for data analysis.

What value does Big Data bring?

The value of Big Data comes from two main use cases: as a source of analytics, and as an enabler of new products and services. In the first use case, big data analytics is used to improve an existing business model by revealing insights from data which was previously too costly to store or process. Amazon’s recommendation system, USPS’s preventive maintenance system, or Walmart’s demand forecasting system are all very good examples. These companies track, collect, and store all available data, from customer transactions to social data, from GPS trails to geographical and meteorological data, then combine them together and use big data analytics to produce high value actionable insights. This would not be possible without the new big data technologies such as cluster computing and machine learning.

In the second use case, big data technologies open up completely new business models and introduce new products and services. Many recent so-called unicorn startups, such as Airbnb, Uber, or Snapdeal, are founded on and enabled by big data analytics. Their products have unique features thanks to the new technologies that they are using. Without following the big data approach, their products would not be able to compete against all the traditional business models.

Big data at eSmart Systems

Since the early of the company, big data has always been considered as our core value. Big data analytics and machine learning are involved in many of our products.  They are used to forecast electricity demand at substation level, segment customers based on their power consumption patterns, and implement demand response strategies. We have also started to use machine learning to automate the analysis of power lines imaging surveys autonomously conducted by drones with the aim of assisting failure detection and preventive maintenance.

Written by:
Dang Ha The Hien
Dang Ha The Hien2
PhD-student, eSmart Systems

Study Big Data Analytics at Østfold University College

Being able to extract insights from massive amount of data has become a key to success in many industries. This Big Data Analytics (BDA) course will survey state-of-the-art topics in big data, focusing on data analysis and machine learning technologies. Participants will gain an understanding of what opportunities big data can bring to their business through hands-on experience with real applications. The topic will be approached from both the practical and theoretical sides.

Østfold University College
Østfold University College

From the practical side:

Participants will have a chance to practice with state-of-the-art big data toolkits and platforms, such as R, Hadoop, Spark,… There will be hands-on assignments which let you build your first spam classifier, recommendation system, and anomaly detector. At the end of the course, participants will be able to answer these following questions:

  • What is big data and why the big data era has come to be?
  • What are the main challenges of big data? How to tackle those challenges using state-of-the-art big data technologies?
  • What is the difference between data and “information”?
  • What is the grammar of data manipulation and how to manipulate data?
  • What is the grammar of graphics and how to visualize things?
  • What are the common statistical machine learning models used in big data? What techniques are suitable in different

From the theoretical side:

Besides introducing state-of-the-art big data toolkits and technologies, this course will also pay a lot of attention on the theory of learning from data, from both the statistical and the machine learning perspectives. To provide a solid foundation for your future big data project, the following concepts will be carefully covered during the course:

  • Sample bias problem
  • Occam’s razor and the inherently imperfect definition of simplicity
  • Bias and Variance Tradeoff
  • Curse of Dimensionality
  • Overfitting and Regularization

Who should participate?

This is the second time we run this course. Thus, many materials and assignments have been adapted to allow participants with different backgrounds to take the most out of the course. No prior programming experience is needed, although there will be challenging programming exercises for those who are serious about becoming a data scientist. Participants may include:

  • Engineers who need to learn the data analysis skills and the new Big Data technologies to apply to their work.
  • Technical managers who need to familiarize themselves with these emerging technologies.
  • Computer science students who want to become a data scientist.

Apply within May 15th 2016! 

Østfold University College and NCE Smart Energy Markets also offer a short program in Big Data Analytics. Read about it here (in Norwegian).

Written by:
Dang Ha The Hien
Dang Ha The Hien2
PhD-student, eSmart Systems

Prosumer bidding and scheduling in electricity markets

Stig Ødegaard Ottesen, Head of R&D in eSmart Systems, recently got accepted for publication an article in the international research journal Energy.

Kontor22

The title of the article is “Prosumer bidding and scheduling in electricity markets” and is about how a smart grid aggregator should take optimal bidding decisions when trading in day-ahead markets and further how to operate flexible energy appliances.

The main part of the article is the mathematical formulation of the decision problems, also taking into consideration the fact that some information (like prices and loads) is not known with certainty at the decision time. It also contains a case study based on data from Norske Skog Saugbrugs and the municipality of Hvaler. Co-authors are Asgeir Tomasgard and Stein-Erik Fleten, both professors at NTNU, Department of Industrial Economics and Technology Management.

Download and read the article here

ChargeFlex strengthening its research capacity

The R&D project ChargeFlex is coming close to ending its first out of three project years, and in November the second workshop in the project was held at Remmen Kunnskapspark in Halden.

The workshop focused on the research, analysis and preliminary results so far. In addition, a live demonstration of the platform Connected Vehicle based on values from Ladetorget was conducted, and live minute date verified by Fortum Charge & Drive.

Since the group was last gathered, the ChargeFlex project has strengthened its research capacity. We are glad to announce that Senior Researcher Jayaprakash Rajasekharan from Smart Innovation Østfold and Post.Doc Chiara Bordin have joined the team, in addition to eSmart’s own Chief Analytics officer PhD, Davide Roverso. In short, three very enthusiastic people ready to take on the project challenges!

Chiara Bordin recently moved to Norway solely to start her combined employment at NTNU and SINTEF and especially to work with ChargeFlex. We took a quick chat with Chiara to ask her about her background and her first impressions so far.

Mathematical optimization applied to the energy sector

Chiara is originally from Italy and has a PhD in Operational Research from the Department of Electrical Electronic and Information Engineering of the University of Bologna in Italy.

She has a strong interest for mathematical optimization applied to the energy sector in both the thermal and the electrical side.

On the thermal side, she worked mainly on a project related to large-scale district heating strategic network design optimization. This work has been in collaboration with Hera – an Italian multiutility that provides energy services both for private and industrial customers –  and OPTIT, a university spinoff that provides consultancy services in the Optimization field.

On the electrical side, Chiara worked in collaboration with the School of Engineering and Computing Sciences of Durham University in UK, where she firstly joined a project related to mathematical models for the battery degradation analysis and optimization in off grid power systems with renewable integration. The study was supported by the Durham Energy Institute and applied to some real world rural sites in Africa, with particular regard to hospital buildings in Rwanda.

After her PhD Chiara was offered a position as Research Associate at Durham University where she worked on a second project in close collaboration with the Engineering Department of Cambridge University. The objective was the creation of mathematical models for a novelty storage technology that is called Pumped Thermal Electricity Storage, in order to analyze its impact on the electric systems behavior, both for grid connected and offgrid systems.

chiara bordin

Chiara is excited about being in Norway, and is planning to stay here on a long term.

“I am very happy. I see combining two scientific jobs both at NTNU and SINTEF, working closely with ChrageFlex people is a great opportunity to do “research that matters” and it is just what I wanted to do after my PhD”, says Chiara.

In ChargeFlex she will mainly contribute with studying business models and optimization processes for smart charging of electrical vehicles. But, with such an eager and competent resource we presume that her skills and competency will be both challenged and put to good work in ChargeFlex.

We predict that after living some years in Northern England, what potential weather challenges a Norwegian winter might provide, and that might deter the average Italian, by now is considered normal rather than having a discouraging effect.

We are glad to have Chiara on the team, and wish her the best. Welcome to Norway, and welcome to the ChargeFlex team!

About ChargeFlex

The ChargeFlex Consortium consists of eSmart Systems (project manager), Smart Innovation Østfold, Norwegian University of Science and Technology, Østfold County Council, Proxll, Fortum Charge & Drive and grid operators Fredrikstad EnergiNett and Sogn og Fjordane Nett.  ChargeFlex is funded by The Norwegian Research Council’s program ENERGIX, through a special call «Pioneering research – new concepts in business».

To follow the project, feel free to like and follow ChargeFlex on facebook

Written by
Henriette Næss Forsetlund

Marketing and Communications Manager, eSmart Systems