A step towards a carbon neutral tomorrow – Savon Voima invests in biofuel quality testing equipment at Iisalmi power plant
Savon Voima invests in automatic sampling equipment at Iisalmi power plant. A sampling robot will automatically take samples directly from trucks carrying biomass before unloading. Sampling plays an important role in determining the quality of the biomass to be burned. Knowing the exact quality per load improves the energy efficiency of the power plant by optimizing the logistics and combustion process. This investment is one step towards Savon Voima’s carbon neutrality target. The sampler is scheduled to be in operation in 2023 and will be supplied by Prometec Tools Oy of Kajaani.
“We have found Prometec’s sampler to be a very effective solution in Joensuu, from where we have a good experience over several years. This positive experience and good results helped us a lot in making the investment decision in Iisalmi,” says Kari Anttonen, Production Manager at Savon Voima.
“For us, safety at work is also an important part of our values, and by automating the sampling process, we can secure the working safety of our drivers and make our fuel quality control process more efficient,” Anttonen continues.
“Our cooperation with Savon Voima has already started in 2017, when we delivered the automated sampling equipment to the Joensuu power plant,” says Juha Huotari, CEO of Prometec, and continues, “The continuation of our cooperation and the additional investments are proof that Savon Voima has found Q-Robot and the sample handling equipment useful and that the company wants to invest in the quality of its fuel and thus in the sustainable use of biomass.
The automated sampler is expected to bring efficiency to the use of biomass in Iisalmi by increasing knowledge of the material being burned.
– We want to contribute to the well-being of the region and provide sustainable energy services to our customers. The investment in the automatic sampler will provide us with valuable information on biomass, which will enable us to optimize our processes and use biomass efficiently and sustainably,” says Anttonen.
Prometec Tools Oy is a Finnish technology company established in 2015, specializing in the production of biomass quality control equipment and services. Prometec currently operates in four countries and its automated sampling equipment collects samples from more than 65,000 trucks and 12,000 railcars every year. Prometec’s main product is the Q-Robot automatic sampler.
Savon Voima Oyj is an energy group offering a wide range of energy services and the best-known energy brand in Eastern Finland. Our goal is to be fully carbon neutral by 2030. The Savon Voima Group consists of the parent company Savon Voima Oyj and its subsidiaries Savon Voima Verkko Oy and Savon Voima Joensuu Oy. The Group is wholly owned by Savon Energiaholding Oy, which is owned by 20 municipalities in the area of operations. The Group’s business activities include electricity transmission, electricity generation and district heating, as well as customer services for energy operators. The group’s turnover in 2021 was approximately EUR 229 million and it employs approximately 210 people.
Prometec, the biomass quality control company from Finland, is delivering a comprehensive sampling solution to Fjernvarme Fyn’s site at Odense. This large biomass project will be fully commissioned in 2023, and Prometec’s fully automatized sampling solution will obtain real-time information from each biomass load to optimize energy efficiency and help improve safety at work.
The sampling solution will be installed in the sampling building at Odense. The sampler collects representative samples directly from each biomass delivery and provides real-time moisture information from each load before the truck leaves the sampling station. Prometec’s patented Q-Robot is equipped with an innovative technology measuring device that measures the moisture content of the sample as soon as the sampling is completed. The moisture data is usually used as the basis for the fuel load payments. In addition, a fully automatic bagging system has been integrated into this sampling solution to bag the samples taken by the Q-Robot for laboratory analysis. This comprehensive sampling solution is the first of its kind to be fully automated, including sample handling and moisture measurement, which significantly reduces the amount of laborious laboratory work which saves time and money.
“Moisture information is vital for power plants to optimize their combustion processes and know exactly how much energy has been delivered to their sites,” said Juha Huotari, Prometec CEO.
“We are committed to sustainability and work safety, and technological solutions are essentialMore information about biomass material means that we can operate in a more energy efficient way, ” stated Thomas Knudsen, Project Manager at Fjernvarme Fyn.
Marlene Kronborg Robanke, Strategic Buyer says, “Fjernvarme Fyn is building a state-of-the-art biomass plant. We are delighted to start a cooperation with Prometec.”
“There has been much discussion about biomass usage. We aim to be the company to deliver accurate information to our clients about biomass so that they can adjust their processes and operate in a highly energy efficient way,” said Henna Karlsson, Prometec CTO.
“The cooperation with Prometec is bringing the market a groundbreaking solution where the heterogenous biomass material can be checked in representative way and automatically in rea-time. We have developed a moisture device with Prometec for several years,” said Markku Tiitta, Puumit CEO.
Fjernvarme Fynis Denmark’s third largest district heating company and is owned by the municipalities of Odense and Nordfyn. The company owns the largest combined heat and power plants on Funen, has almost 300 employees, and is one of Europe’s largest heat suppliers. We cover approximately 97% of the heating demand in Odense and the surrounding area, corresponding to more than 200,000 residential units. District heating is supplied according to the general guidelines set out in the heating plan, which defines supply areas and more. Fjernvarme Fyn’s aim is to provide customers with the best possible heat supply at the cheapest possible prices, while helping to increase customers’ energy and environmental awareness.
Prometec is a Finnish technology company specializing in the quality control of biomass. Prometec has improved fuel quality control and energy efficiency in more than 20 heat and power plants since 2012. Sampling has been recognized as a key element in quality control due to the heterogeneity of wooden biomass material. The moisture of the material varies even within one load, and it is necessary for energy efficiency to have accurate moisture information about each biomass delivery. Prometec’s Q-Robot automated sampler systems analyze more than 60,000 truckloads and 12,000 train containers of fuel per year in three countries.
Juha Huotari, CEO, Prometec, juha.huotari@prometec.fi +358 50 591 7350
The measurement of fuel quality in power plants has been developed considerably in recent years and its importance will become even more important as the share of fossil fuels is replaced by less homogeneous biomass. The biomass to be burned arrives at the power plant in trucks or trains or vessels. One load may contain forest residue chips imported from the surrounding area, one lorry can contain recycled wood chips, and one may contain by-products of the forest industry, such as sawdust and bark. These loads can be very different in terms of moisture and energy content – and the variation between individual loads can also be very high. However, the quality information of the loads, of which moisture information is the most important, is currently only available when the fuel is already being unloaded and the fuel is entering the boiler or in some cases it has already been burnt.
Prometec’s product development goal has been to provide real-time moisture information on biomass loads before the load is unloaded at the power plant. The development has been based on a fully automated sampling robot, almost a decade of fuel measurement data and mathematical prediction models refined with intelligent machine learning solutions.
As a result of long-term product development, Prometec is now the first in the world to provide real-time fuel moisture data before unloading. Data is available throughout the supply chain via the Q-Data cloud service system developed by Prometec. As a result, the moisture data will enable better control of the entire fuel quality chain, as the fuel supplier will already be able to react to quality issues with real-time data. At the power plant, moisture data is an essential control parameter for the entire combustion process: the better the moisture data of the fuel unloaded into the storage silos, the more efficiently the boiler combustion can be controlled, and combustion losses and emissions minimized.
Q-Data fuel management system
A prototype of the Q-Data system has already been developed and tested in Kajaani, but the first actual Q-Data system will be built for Kuopio Energia within next few months. The use of the real-time moisture data produced by the system will be developed in cooperation with Kuopion Energia. The first objective is to use the real-time fuel moisture data to instruct the truck driver where to unload the fuel. In this way, for example, dry fuel can be driven to one storage silo and more moist fuel to another, and the boiler feed can be directed to the storage silos to ensure that the fuel flow is as even as possible in terms of moisture. In the future, the aim is to provide quality data directly to the power plant control system so that the boiler combustion process can be controlled as energy-efficiently as possible by optimizing the fuel supply.
“This solution, developed by Prometec, will for the first time allow immediate forecasting of delivery lots with different moisture content. This is exactly the data we need, for example to use artificial intelligence to tune our combustion process for optimum efficiency and to get the most out of the fuels we buy. It is also really important that we can react immediately and intervene if he fuel supplied does not meet the quality requirements,” says Peter Seppälä, Production Director of Kuopion Energia.
“It’s great that we can put our innovation into practice with our long-term partner Kuopion Energia and use the data to find ways to improve energy efficiency and reduce emissions in plants,” says Henna Karlsson, Business Director at Prometec. “We want to be a pioneer in biomass quality control and we believe that our innovation will help power plants to achieve significant cost savings while promoting more sustainable use of natural resources,” says Henna Karlsson.
Decommissioning of peat burning – in a controlled way towards biomass
Finland intends to halve the energy use of peat by 2030. However, how the challenge is to be tackled over the next nine years is still open. In March, Minister of the Environment and Climate Krista Mikkonen stated that the government must make a clear plan for shutting down the energy use of peat. Where are we now? Last year, fossil fuels accounted for 13.8 per cent of Finland’s electricity production and 40 per cent of district heating was produced by burning peat, coal, oil and natural gas. Peat produces only about six percent of Finland’s total energy needs, but it accounts for up to one-fifth of the energy sector’s emissions – and 12 percent of Finland’s total emissions.
There are more than 50,000 hectares of peat production in Finland. About 90 percent of peat is burned for energy. It is five years since the Paris Climate Agreement was signed, but our government is still in the process of creating a plan for peat.
The keyword seems to be “controlled” downtime. Still, for example, the Confederation of Finnish Agricultural and Forestry Producers MTK described the downsizing of peat energy use as “reckless” in its December statement. The Finnish people also have an opinion on the matter: at the beginning of 2021, news was announced about the citizens’ initiative on ending the use of peat energy, which received the required 50,000 signatures and went to Parliament. According to the initiative’s proposal, peat should be phased out five years earlier than planned, ie by May 2025. Would it even be in a hurry? We believe that decommissioning peat use should be controlled and planned.
What happens when a power plant switches from peat to biomass?
In the 1970s and 1980s, peat-fired power plants were built in Tampere, Kuopio and Oulu, among others. Already in the 90s, boilers began to be converted into multi-fuel boilers, ie in addition to peat, power plants were ready to burn wood-based fuels. The forthcoming decommissioning of peat production will force power plants to look for new energy sources – and that means millions of investments in many locations. In practice, this might mean that, boiler technology, fuel reception system, conveyors and sampling system will be renewed in power plants. At the same time, environmental permits must also be updated, as the permit is always based on the fuel fractions and quantities burned.
As the material to be burned changes from peat to biomass, quality determination plays a significant role. The biomass to be burned enters the power plant in trucks, where one may contain forest residue chips imported from the vicinity, the other wood chips imported from Russia and the third, for example, forest industry by-products such as sawdust and bark. These loads can be very different in terms of moisture and energy content – the variation in individual loads can also be really large.
If we place two identical full trailer trucks carrying 150 cubic meters of fuel side by side, we will be able to concretize the difference: there are only about 1 to 3 percentage points difference in the moisture content of the peat truck load between the measurement points – at most only 5%. The moisture content of biomass, on the other hand, can vary between 30 and 60%. That is, the biomass load may be wet at one point of the truck running off the water and the sample taken from the other point may be relatively dry.
Peat is thus homogeneous as a fuel for power plants. When biomass is burned in a boiler instead of peat, the fuel is heterogeneous, the quality of which should be measured particularly carefully to determine the correct price for the load. Errors in sampling and moisture measurement accumulate as an additional cost to the power plant.
Winter has a major impact on biomass quality measurement
On the scale of power plants, small human errors can cause large differences in the material flows of thousands of tons. In Finland, one human thing to consider is winter: snow and ice inevitably affect winter moisture measurements. The largest errors occur in the actual sampling, but measurement errors are also caused by sample handling and storage.
It is not uncommon for tens of kilos of ice to fall to the unloading site when unloading a truck load. It is far from homogenous material. The example in the photo below shows the winter reality: the load is layered with ice, snow, wood chips and forest debris. If the load were manually sampled with a small shovel into the bucket right from the top of the cart – would the surface sample represent the moisture of the entire load?
Positive results from the change in Kuopio Energy
Kuopion Energia introduced an automated Q-Robot sampling robot in 2017 at its power plant. Production director Peter Seppälä states that the world was lying in a different position at the time.
– Compared to the plans of that time, the shutdown of peat burning will take place much faster under the guidance of emissions trading. At that time, Kuopion Energia was Prometec’s pilot project to solve the challenges of manual biomass sampling. Quite positive results began to show almost immediately, Seppälä says.
Kuopion Energia’s electricity and heat production is centralized at the Haapaniemi power plant and the Pitkälahti power plant. A total of about 14,000 truckloads of wood and peat arrive in Haapaniemi every year, producing 1.3 million megawatt hours of energy. This can be proportioned, for example, by comparing the need for an ordinary detached house: the annual energy demand for heating and hot water is about 20 megawatt hours.
– Manual metering and fuel moisture fluctuations produced us 50 gigawatt hours less energy per year than the price paid for the fuel. Roughly speaking, our annual fuel costs are in the order of EUR 25 million, and the percentage error is EUR 250 000. With Q-Robot, our savings over the past few years are worth millions.
– Significantly more fuel is needed during the winter. If we look at, for example, three months from June to August, during these three months the same amount of fuel is used to produce electricity and district heating as in two weeks in the winter, Seppälä concretizes.
A hall was built for Q-Robot in the area of the Haapaniemi power plant, where a truck arriving with biofuel will drive for weighing and automated sampling. The robotic auger takes several samples at randomly selected points and depths, and combines them into a representative sample of the entire load, following solid biofuel sampling and sample handling standards ISO 18135 and ISO 14780.
– In the past, sampling involved human errors and I also understand the power of fuel producers from a great point of view, because, for example, a few percent change in dry matter percentage has an effect of hundreds of euros on the price of fuel load, states Seppälä.
Q-Robot – what’s the question?
The automated Q-Robot sampling robot takes a reliable and representative sample of the raw material load quickly before unloading it.
Sampling works seamlessly with a variety of solid and crushed materials.
In addition to the sampling unit, the Q-Robot includes a machine vision system that measures the volume of the load in real time
Q-Robot can generate calculated load moisture data and energy content data immediately after sampling
Samples taken by the Q-Robot can be analyzed immediately on site with rapid measurement equipment or taken to the laboratory for analysis.
EU Green Deal and Q-Robot – from fossil fuels to biomass
I listened with an interest to the Bioenergy Winter Days (28.1.2021) presentation, in which Bioenergy Europe associationsGiuliaCancia reported on the bioenergy situation in Brussels. In EU countries, the use of biomass for heating has grown steadily since 2000. According to Giulia Cancia presentation based on Eurostat statistics, in 2018 the share of biomass in heating was 16.7%. By 2030, the figure should rise to 25%. Bioenergy Europe, predicts that the use of biomass will increase the most in the residential and industrial sectors.
The review was naturally linked to the EU’s Green Deal and the decarbonisation of the EU’s energy system. More than 75% of the EU’s greenhouse gas emissions come from energy production and use. According to Giulia Cancia, in 2017, Hungary, Lithuania, Estonia, Latvia, Luxembourg, Poland and Finland used the most bioenergy in the EU. Large EU countries such as France and Germany lagged far behind in comparison.
According to Bioenergy Europe association, the use of bioenergy relies mainly on the sustainable use of biomass. The question is, what are the barriers to the transition from fossil fuels to biomass combustion in power plants?
FACT 1:
The biomass material can be anything from straw stalks to felling waste, from branch pieces to plant leaves.
Solution: Prometec’s Q-Robot takes an automated sample of the material at the moment of arrival at the power plant and sends the data to both the power plant and the material driver. Q-Robot is able to take samples of all kinds of crushed and granular materials.
FACT 2:
A large number of power plants use an oven drying method to analyze biomass samples, the result of which is completed approximately two days after sampling. Quality information cannot be utilized in process or combustion optimization.
Solution: Prometec’s Q-Robot works in real time. The quality data can be utilized already when the truck transporting the material is at the sampling point. It enables the optimization of the process: a truck transporting poor quality biomass can be turned away, a certain quality of biomass can be stored in terminals, for example for frosty periods. For example, dry biomass should be directed to a terminal storage and wetter for direct incineration, as studies have found that the shelf life of wet biomass material is poorer. Sampling takes less than 10 minutes.
Different biomasses can be mixed to form an optimal fuel mix. When quality data is utilized proactively, for example, dry and moist biomass can be alternately directed into the power plant’s discharge channels so that the moisture fluctuations in the fuel are evened out in the boiler`s material supply.
FACT 3:
Some power plants authorize the truck driver to take a sample of the biomass they transport. The driver may act either knowingly or unknowingly incorrectly when taking a sample. Drivers have been studied to take drier samples than the fuel load actually is, as it affects the price of the load to their advantage. There is also an occupational safety risk associated with sampling: there may be a risk of falling or being injured when working at an unloading site.
Solution: The Q-Robot always takes a sample systematically at random from the entire load area at different depths. In addition, the robot sampler auger is always clean and the material is never mixed between suppliers or species.
FACT 4:
In Scandinavian and Northern European conditions, the load brought by a biomass truck may contain snow and ice in winter, which affects the weight of the load and the quality of the biomass.
Solution: Q-Robot tells you the exact energy content and moisture of the fuel. According to a VTT study, there is an error of up to 2 percentage points in moisture in determining the quality of biomass, which contributes to the price paid for fuel, the optimization of fuel logistics and the combustion process. Together, these affect the profitability of biomass combustion relative to, for example to coal.
Our company was founded in 2012 and currently employs 15 people. We operate in three countries. Q-Robots are currently in use in Finland, Sweden and the Baltic countries. We believe that our total solution will play a key role in reducing the use of fossil fuels in the EU’s Green Deal in the coming decades – Asia will also be a major market for us.
Deloittebelieves the same: In January, Prometec Tools was ranked 23rd in the list of Finland’s fastest growing technology companies.
Finland’s new bioeconomy strategy, which will be completed in summer 2021, will take a stronger position on circular economy solutions and the utilization of renewable natural resources. The strategy has been made public, with the aim of securing the sustainable use of renewable resources as part of the EU’s climate goals. A significant part of greenhouse gas emissions is generated in energy production. In Finland, almost half of our energy comes from fossil fuels that produce greenhouse gas emissions, such as peat and coal.
As part of the preparation of the bioeconomy strategy, the Ministry of Agriculture and Forestry and the Ministry of Employment organized several regional bioeconomy forums last autumn as webinars, which we also followed at Prometec. It was eye-opening to see the bioeconomy know-how and operators from different provinces.
Whatever the carbon neutrality targets to be achieved in the national strategy that are to be achieved by 2035, our Q-Robot solution will help facilitate the transition of power plants from the burning of coal and peat to burning biomass.
When peat is replaced by biomass in Finland, it will also affect truck traffic. One peat truck contains an average of 130 megawatts of energy, but when replaced by a biomass truck of the same size, it does contain 100 megawatts of energy. As a result of moving into biomass the truck transportation is increasing.
Annual savings of one million euros for the power plant
Peat and coal are homogeneous materials, i.e. the transition to biomass means burning more inhomogeneous material. In this case, the key factor is how the quality can be determined reliably and how it is taken into account in with combustion in the boiler. For example, in a forest residue chip load, the humidity can vary between 30-60%. In this case, it is really important that the sample is taken systematically correctly and reliably so that the sample taken corresponds as closely as possible to the material in the load.
The importance of determining the quality of biomass has been studied both by us and by VTT, among others. One of the results of the studies was discovered a large finding of a 2 % average error of moisture content result determined at the biomass quality definition. The error is due to manual sampling when the biomass truck driver takes a sample of his load, for example with a shovel, at a point in the load where the sample is most easily available. The biggest problem has been the effect of snow and ice on wintertime measurement results. The humidity error imposes a large additional cost on the power plant – on an annual basis, it can mean 5 % of the fuel purchase price.
The fuel consumption of a large power plant can be a thousand gigawatts per year. With an energy balance error of 5% and a megawatt price of biofuel in the order of EUR 20, the annual cost will rise to EUR 1 million. For example,this of course, affects the profitability of biomass combustion in relation to coal.
Subheading: Quality information helps to minimize CO2 emissions
Q-Robot’s reliable biomass receiving inspection provides real-time information on load quality. Thus, the right price is paid for biomass and variations in fuel quality are considered in the formation of the fuel mixture for the power plant boiler. Biomass may be a by-product of harvesting, forest maintenance work and the forest industry, for example. Quality information enables the minimization of CO2 emissions when the right quality material is brought to the plant in a timely manner and the combustion process can be optimized.
According to the energy sector low carbon roadmap , fossil fuels are being phased out in transport, services, base machines, industry, heating and agriculture.
At present, the EU Commission sees Finland as an example country for the bioeconomy in the EU region. The national bioeconomy strategy has a major role to play in maintaining this pioneering role. Prometec’s quality measurement solution will support the implementation of the bioeconomy strategy in various industries – in addition to the heat and power plants used as an example, in the pulp, mining and food industries.
Fact: How can Q-Robot’s real-time quality information be used?
Prometec’s automatic sampling has been verified by VTT
A comparative study carried out by VTT (Technical research center of Finland) was made in November 2020 at Kuopio Energy’s Haapaniemi power plant. For five days, samples from different types of biofuel loads were collected in both ways, with a Q-robot and manually by VTT. So, the comparison included automatic sampling and manual sampling. Load-specific samples were taken daily from all loads delivered during the 10-hour test period. Samples for the comparison were collected from a total of 59 loads, of which 26 loads were forest residue chips, 20 loads of whole wood and stem chips, 8 loads of peat and the remaining loads were sawdust and bark.
The comparative study followed the principles of the Wood Fuels Quality Guide (VTT-M-07608-13) and manual sampling was carried out in accordance with the standard ISO 18135: 2017. Manual increments were taken during the unloading from the falling material stream. According to the quality guideline, at least 6 individual samples (2 truck + 4 trailer) are taken from a combination of truck+trailer vehicle (100 – 160 m3), in which case these sample volumes have the possibility to achieve an accuracy requirement of about 3% in moisture with 3 – 5 load deliveries. Automated sampling was performed by a Q-robot that took load-specific samples according to its normal operating sequence. The Q-robot takes samples fully automatically and randomly from different depths and different points of the load in accordance with the sampling standard EN ISO 18135: 2017. Moisture was analyzed from the samples and particle size distributions were also analyzed from forest residue chip samples.
Automatic sampling is important. The picture shows a sorted load.
Research results
The difference in average moisture of all fuel types over the reference period between sampling methods was 0.7 percentage points. In the comparison, there was a particular interest in the differences between the sampling methods for inhomogeneous forest residue chips, where the moisture variations within the load can be very large. In comparison, the average moisture difference between the sampling methods for all forest residue chip loads was 1.5 percentage points. For forest residue chips, as for all other fuel types, the moisture variations between the loads were reasonably large and the moisture between the sampling methods were scattered in one and the other, but no systematic difference was observed between the sampling methods. As a result of the verification, no clear systematic difference between the methods affecting the results in one direction could be observed from the results. In the light of these research results, the automatic sampling of the Q-robot meets the requirements of the standard for reliable sampling.
It is important for us to know how to develop our operations and products as well as our services. We at Prometec believe that our current customers are the best opportunities for sparrers and that’s why we actively want to hear how we have succeeded. Development doesn’t happen over one night and it requires enthusiastic doing and investing in new, not forgetting well-functioning models. We want to be Reliable, Innovative and Eager.
The latest customer survey was sent about a month ago. The purpose of the survey was to find out our customers’ satisfaction with the products and services, and in a bigger picture, the customers’ opinions about us. Therefore, we would like to say thank you to all the respondents, we greatly appreciate your answers. Based on the responses, we can say that we have succeeded in creating good and reliable relationship with our customers. In particular, we received praise for working close to the customer and being active towards the customer. We will continue this work. Also, we received positive feedback from the quick response to the contacts. Our customers’ willingness to recommend was very good 9.4 (max 10) based on the international NPS = Net Promoter Score scale. The answers encourage us to continue our innovative work in both products and services.
Thanks again to the respondents. We are happy to return to development ideas in our personal conversations.
