Smart Energy Systems with an exciting battery project

- The goal is to reduce people's electricity expenses

Energy Bank can help reduce private households' electricity bills by at least 20 per cent. That is the goal of the AI Battery Optimizer project that Alexander Finn (tv) and Fred Martin Langøy at Smart Energy Systems are working on together with Smart Innovation Norway. - Our battery solution is a solution for efficient storage of electricity, and storing electricity contributes to reduced grid rent and lower electricity bills, says Langøy. PHOTO: Smart Energy Systems
20 percent lower electricity bill. Fred Martin Langøy of Smart Energy Systems believes that it is possible to achieve this with their battery solution Energy Bank. They will develop the technology together with Smart Innovation Norway.

Solar panel on the roof and battery in the shed. These two elements are all that is needed to turn private households into small independent power plants that produce and store their own electricity.

The Fredrikstad company Smart Energy Systems will work until October next year to develop technology that makes it profitable for the private market to install the solution.

- Our aim is for people to reduce their electricity bill by at least 20 per cent through our battery Energy Bank, says general manager Fred Martin Langøy.

Regionale forskningsfond Viken (RFF Viken) has approved the entire application of NOK 3.13 million, and Langøy is pleased that more people have faith in the project and see the usefulness of the technology to be developed.

Several advantages of storing electricity

According to the website , the number of solar panels in Norway has increased enormously in recent years. But one of the challenges is that there are no storage options for excess electricity. Thus, the power that the panel produces, but which is not used, disappears into the local power grid.

- Surplus power from solar panels is usually more profitable to store in batteries than to be delivered to the grid. Our battery solution is a solution for efficient storage of electricity, and storing electricity contributes to reduced grid rent and lower electricity bills, says Langøy.


Project Name: AI Battery Otimizer

Purpose of the project: Develop AI technology to make optimal use of the battery Energy Bank and commercialize the battery technology

Project participants: Smart Energy Systems and Smart Innovation Norway

Project support: 2 million

Project period: 2 years

In the Energy Bank, you can store self-produced excess electricity as well as electricity that you buy from the grid when prices are low. This electricity can be used when electricity prices are high or to avoid high network rent.

- You can set the battery so that it takes over the power supply when the consumption crosses a certain power limit. That way, each individual household can control their electricity expenses in a better way, explains Langøy.

By power is meant the amount of electricity that is used at the same time. The electricity rent is calculated based on how much electricity the household uses, and the introduction of power tariffs will make customers use electricity in a smarter way for better utilization of the electricity grid. An even consumption throughout the day is more profitable than using a lot of electricity at the same time.

Environmentally friendly and cost-saving

Society is facing extensive electrification, and Langøy sees Energy Bank as part of the solution. The more households that can provide part or all of their own electricity consumption, the less the need for development of the local electricity grid.

A feature of social development that causes a large part of the need for electricity is the proportion of electric cars on Norwegian roads. Figures from Statistics Norway show that in 2021, two out of three new passenger cars in Norway were electric cars. Charging an electric car is one of the things that require the most electricity in Norwegian households, and Langøy believes that it will mean big savings for the grid companies if more private individuals adopt battery technology.

- If, for example, "everyone" in a residential area has an electric car, this leads to an increased demand for electricity and, in most cases, a requirement for more and larger cables into the houses. With Energy Bank, the need for the development of a local power grid is reduced, he says.

Langøy also highlights the environmental perspective of utilizing modern battery technology. The CO2 footprint is smaller when there is no need to expand the electricity grid.

- Together with Smart Innovation Norway, we have been working on developing AI-based technology for a few months already, and we are looking forward to the continuation. By commercializing the Energy Bank through this EU project, we save private individuals and grid companies costs and the environment from CO2 emissions, summarizes Fred Martin Langøy.

Stig Ødegaard Ottesen

Stig Ødegaard Ottesen
Head of Energy Systems

Telephone: +47 909 73 124

Email: stig.ottesen@smart

Almost 500 registered when AI+ was organized for the second time

Almost 500 registered when AI+ was organized for the second time:

- A conference at the top international level

When AI+ 2021 got off the ground digitally on Wednesday and Thursday last week, it was with a varied and highly topical program packed with quality speakers. First up was Norway's Prime Minister.

By Mari Kristine Buckholm , 25 May 2021

- Data and artificial intelligence will be important in solving the challenges of the future. That is why I am happy that this ambitious conference can be organized even though we are in the middle of a pandemic. But AI is also important for fighting the pandemic. Over the next two days, you will discuss topics that will shape society in the years to come. I hope you have an interesting and productive conference!

This is what the Prime Minister of Norway, Erna Solberg, said to participants from both Norway and abroad when she opened AI+ 2021 on Wednesday morning.

Changed view of artificial intelligence

The conference was held for the second time on 19 and 20 May and the aim was to offer both Norwegian and international environments and companies an arena of expertise and interaction within applied artificial intelligence (AI), which will provide good conditions for success with data-driven economics and innovation in the future.

The digital event was broadcast from the Simulator center at Remmen Kunnskapspark in Halden and led by journalist, meeting leader and writer, Ruth Astrid Sæter.

- I must say that being allowed to lead AI+ 2021 has been incredibly educational. I knew very little about artificial intelligence before, and not least about applied artificial intelligence. Now I have learned a little more, and I also see that there are many areas that need to work more together - both to accelerate development, but also to ensure that all the important considerations are taken into account. There is still a lot to go on, comments Sæter after the end of the conference.

This year's conference host admits that her view of what artificial intelligence is and how the technology can be used has changed after hearing varied presentations from universities, research companies, large technology companies and small startups over two days.

- That perception "God, are we going to let the machines take over?" is not there to the same extent anymore. I am excited when the algorithms become so smart that they have detected everything, what kind of acceleration will we see then?, she asks.

"Clean air for everyone"

Business developer at the start-up AirMont, Ole Gabrielsen, was among the companies that pitched their solution and use of artificial intelligence to the digital audience. In addition, he participated in the panel debate on day 2.

- The conference provides an opportunity to make contacts. Since it's digital, it gets a little more difficult, but you also get inspired to check out new things. When you hear what Oda (formerly tells about its experiences and what the Norwegian School of Economics says about new innovation models, it is very useful input for us. As a new startup, we don't get this anywhere else. It is absolutely crucial to be part of such an environment early on, says Gabrielsen.

AirMont's vision is "clean air for all" and the company aims to ensure better air quality with the help of artificial intelligence and sensor technology. The first product on the market is pipe sensors with a built-in digital system which will be rolled out to all households with pipes in Halden municipality during autumn 2021.

- The sensors use artificial intelligence to correlate research results and historical data. When you collect many data sets, for example from the Norwegian Road Administration, the municipality, the EU, weather and traffic data and sensor data from us, this data can be used to predict poor air quality with the help of artificial intelligence. It is almost impossible for a human being to do, explains the business developer.

In the long term, Gabrielsen envisions that such predictions can be used to encourage residents to burn less from their fireplaces in given periods of time, as it is often burning that is the main cause of poor air quality in cities. An incentive could, for example, be that residents who stop lighting the fireplace, something that will be possible to monitor with the help of sensors, can get half price for electricity during the relevant period.

Microsoft offers assistance

On the way there, however, a start-up company needs help, both with financing, good advice and follow-up. This is where the giant Microsoft comes in. The technology company has massive expertise in digital systems and was well represented at the conference, both as a sponsor and partner in the industry cluster Cluster for Applied AI, but also as a speaker and participant in the panel debate.

Izabela Hawrylko is a solutions consultant within Data&AI at Microsoft and co-leader of the Microsoft for Startups Norway Team. She was Microsoft's emissary in the panel debate.

- The most important thing for us to bring with us is different perspectives. Being here and hearing from start-up companies like AirMont allows us to think about how Microsoft can assist with its resources and, not least, funding. With the size we have, I believe there follows a responsibility to support companies and academia. That's why it's important to take part in conferences like this one, talk to people and hear what kind of challenges they have, says Hawrylko.

She is clear that there are far too many people who talk about artificial intelligence and want to test it out in their organisation, but without being willing to make the organizational changes required to succeed with new technological solutions.

- Technology is important, but you must also be able to use the technology and change the organization so that you get the most out of the technology. There is no point in acquiring an innovative solution if you don't know how to use it, or he a plan to use it. We see that artificial intelligence has been very hyped up and used as a buzzword, and I hope that more companies eventually understand that you also have to have a plan to put it into use, she points out.

Even bigger next year

Two of the initiators behind AI+ are Knut Johansen, managing director of eSmart Systems, and Tomas Nordlander, research director at the Institute of Energy Technology (IFE). They were both very satisfied with the implementation of this year's digital conference and are looking forward to next year - which will hopefully be a physical event.

- This has become a conference at the top international level. Those who participate get very good and useful input, says Johansen.

- During the first conference this autumn we learned a great deal and we have now had a second conference which has gone very well, but there is still much to improve. Then maybe the third conference will be an even bigger physical event, and then we've had two training rounds, adds Nordlander with a smile.

AI+ was organized by Smart Innovation Norway, eSmart Systems , Institute of Energy Technology (IFE) and Halden municipality , in collaboration with the industry cluster Cluster for Applied AI .


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Artificial intelligence – what is it and why is it on everyone's lips?


Artificial intelligence – what is it and why is it on everyone's lips?

Used correctly and in the right circumstances, artificial intelligence has the power to help businesses in the private sector as well as the public sector become more efficient and most importantly; more sustainable.

By Research Director at Institute for Energy Technology Tomas Nordlander and journalist Mari Kristine Buckholm

The history of artificial intelligence (AI) goes back to the Dartmouth Conference in New Hampshire in the summer of 1956. That is when the word was first coined. The conference gathered some of the key researchers in the United States, who were computer scientists, to look at the potential of the computer. The researchers had already started looking into making the computer intelligent before that, but the Dartmouth Conference is considered to be the founding event of artificial intelligence as a field.

From that time until now, we have had AI winters and AI springs. Every time there is an AI spring, like 1956, we have a lot of funds coming in. Several companies put a lot of money in, and a lot of promises as well, but some of these promises are not realistic. For example, in 1956, they were talking about the autonomous car and the universal translator, and it was promised to be ready in 10-15 years. But, as we all know, 15 years later there were no autonomous cars.

What happens next is that people get disappointed when AI does not deliver, and almost all the funding stops. A lot of good researchers leave the field and move to other fields. So, every time the AI winter comes, we lose a lot of excellent AI researchers.

Then the spring comes again, because someone has gotten a breakthrough, and the funding comes back. Also, every time we have an AI spring, the charlatans show up as well. People who do not really have AI experience, capabilities or AI products come because there is a lot of money involved. They also make promises, which lead to disappointment – and affect the AI hype.

The lasting AI spring

Today, we are in the middle of an AI spring, but there are still some cold winds. The difference this time, compared to previous AI springs that have turned into winter, is that we have available data from Internet-of-Things (IoT), we have mature algorithms, and we have processing power in the cloud. All this makes the current AI spring unique, and I think it is here to stay. With that said, there will be a lot of disappointments as well, where people are promised gold, but get coal in return.

This is why it is important to remember the history of AI. When I bump into young people around 25-35 years old, they tend to think that AI is only about deep neural networks and that everything written about AI that is older than 10 years, is irrelevant. That is a huge mistake. You might think that the autonomous vehicle came from the DARPA (Defense Advanced Research Projects Agency) Grand Challenge or Tesla, but in the 1980s there were autonomous Mercedes Benz cars driving on the highways of France, Germany and Denmark, using AI.

We had cars driving autonomously already in the 80s and people don't know. We have so much more to learn from the history of AI, but people are too short-sighted back in time. Some of the most relevant research papers are not as young as five years old; they might in fact be 20-40 years old.

Hence, if you wish to focus on AI, do not ignore research and results of AI that is older than 5-10 years. You will only do yourself a disfavor and create more work than you need to do.

Definitions of AI

Through the years, there have been many attempts to define what artificial intelligence is. The simplest and most common definition, but a problematic one, is "intelligence demonstrated by machines and software". The problem is that we do not have a universally agreed upon definition of the word intelligence. If you and I have two different views of what intelligence is, it means we would also have two different views of artificial intelligence.

Therefore, a more comprehensive definition that does not contain the word intelligence would be better: "Machines and software that try to achieve a goal or solve a problem in a changing environment using reasoning, memory, planning, scheduling." That is artificial intelligence.

Machine learning, on the other hand, is a group of AI techniques (some statistical techniques also belong under the machine learning umbrella). It enables a system to automatically learn and progress from experience without being explicitly programmed.

The most important reason why people and companies should have competence within AI today, is that AI has the potential to help with digitalisation. For the Institute for Energy Technology (IFE) , digitization means how organizations use digital technology to enable them to do more with less effort and get it done quicker, safer, and cheaper. If AI can help with that, you will get a competitive advantage compared to those who do not utilize it. Basically, it is about staying in the game and being competitive.

It is also necessary to remember that AI might not always be the solution. There are some problems where people apply AI, when other techniques like statistics or mathematical modeling are way better. I have seen instances where people choose to apply AI to a problem simply because it attracts funding, but they end up using the wrong technique to the problem. They would have had a much more efficient solution if they used mathematical modeling instead.

Nevertheless, used correctly and in the right circumstances, AI has the power to help a large number of businesses in the private sector as well as the public sector become more efficient and most importantly; more sustainable.

When is AI the solution?

We have several examples of smart use of AI in the new Cluster for Applied AI . Many of our cluster members already utilize artificial intelligence in a way that is both efficient and environmentally friendly. In the following, I will present some of the most relevant cases.

At IFE, we produce medicine for prostate cancer. It is a radioactive medicine that is given intravenously to patients, but it has a half-life of two weeks. This means that from the time we produce it, we have two weeks to give it to the patients, otherwise it does not work. We deliver this medicine from our facility at Kjeller to the entire world, and it must reach the patients, wherever they are, within two weeks. The medicine is kept in a vial and we need to identify if there are dust or particles that make it necessary to discard it.

Previously, this was done manually by people looking at and shaking them against light to check. First of all, they would get a small dose of radiation, which is not dangerous, but not great either. Secondly, it is hard for the human eye to detect these particles. Now, we have project where we use a robot hand to shake the vials and we use machine vision with AI to identify the particles, which can do the job faster, more accurate, and safer than humans, which means better medicine reach the patient faster .

A second example is that of eSmart Systems . The software company uses AI to detect maintenance needs on the masts of power lines.

Previously, when you were inspecting power lines, you would rent a helicopter and fly along the power lines with a camera and/or binoculars to try to identify what might be broken. This is traditionally known as one of the more dangerous helicopter trips that you can take. There is always high risk involved when working close to power lines, but this method also has a high carbon footprint.

eSmart Systems' solution is to use drones to inspect instead. These drones can be autonomous or controlled by man and are equipped with a camera connected to artificial intelligence which analyzes the power lines and masts in real-time. This means that the operator will know exactly which mast to go to, which tools and parts to bring, and which error to climb up and fix. The AI has been fed with a broad spectrum of images showing all different kinds of masts and potential errors and trained to detect and identify all types of errors. It can recognize and analyze 200,000 images in one hour, whereas a human being would need one year to analyze 100,000 images.

Before, the utilities left a big carbon footprint, there was more risk involved with the helicopter, it was more expensive, and they still did not get as accurate information.

The third example from the cluster is Husqvarna 's production of saw blades for chain saws in Sarpsborg, Norway. They are interested in AI to look at the quality early in the production line. Very often, if there is a mistake early in the production line, they want to detect it as quickly as possible. Because when you build a product and it is faulty early on, but you do not know, you invest more money and time building things on top of it. In the end, after spending a lot of time and resources, you find out it does not hold the standard and must throw it away.

Husqvarna wishes to know early in the process if the tolerance, width and height of the product is perfect. If it is not, they will discard it early on. Hence, the company uses AI to detect faults early in the production process, so that they do not invest or use resources unnecessarily.

A fourth example is predictive maintenance. Here, IFE has been using AI techniques since the 1980s to assist in safety critical industries. We predict when failure will occur (based on sensor inputs such as vibrations, sound, and electrical profile used) which allows for optimal selection of time to do maintenance. For example, predictive maintenance is used on large water pumps for nuclear installations.

From the public sector, the most relevant examples of smart, and in some cases lifesaving, use of AI are within healthcare. For example, AI can be used to predict breast cancer and help identify tumors. It can analyze databases of people's medical records to identify pre-diabetics, so that measures can be made and medicine given to prevent them from ever becoming diabetic. Of course, today we have laws and regulations that prevent the sharing of medical records, but these things could be evaluated against how much it is worth.

AI can also be used to analyze what some schools are doing correctly in terms of teaching and learning compared to other schools, or to make sure that the elderly can stay at home as long as possible with the help of smart sensors.

AI in the future

To sum up, there are many ways that AI can help both private businesses and entire sectors, including the public sector, to become both more efficient and more sustainable. As discussed, AI is nothing new. The reason why AI is in the wind again, seemingly for good this time, and has become a popular buzzword all over the world, has a combined explanation.

Every time there has been an AI spring, it is because one of the AI techniques has made significant progress. In the 1980s, it was a so-called expert system (computer program that emulates the decision-making ability of a human expert) that suddenly started being able to handle industrial problems which gave the industry a huge benefit. Thus, the AI spring blossomed, before it became winter once again.

What initiated the current AI spring, is neural networks and the progress we have made within that field. A neural network model is originally inspired in design by the human brain (but it is not an artificial brain) and is programmed to recognize patterns. We have managed to, in several different areas, use neural networks with a higher degree of accuracy than humans. For example, a neural network can learn how to play chess against itself and get better and better, until it is better than any human chess player.

Even though we have had great success with neural networks, the focus should shift to other AI techniques as well – which could work very well with neural networks. Because AI is much more than machine learning. The latter has the downside that it is "black box", which means that we cannot see how the knowledge is represented in the AI model. But a big part of AI techniques and algorithms are "white box", that people have forgotten a little bit about, where you can actually explain the reasoning for everything. In the future, the important thing will be to combine them.

Going forward, everyone should gain more knowledge about AI. Attending courses is one thing, but what we really need, are initiatives like Siva's Catapult centers and the newly formed Cluster for Applied AI , where people and companies can connect, ask questions, test products, share knowledge and experience, and establish collaborations.

If we succeed in creating such a national AI team and work together instead of competing against each other, we will be able to create value within our own borders and become a force to reckon with internationally as the world enters the AI age.