In MENER project, journey of burnable wood from forest to power plant’s boiler is optimized using AI

 

The most important quality characteristic of wood-based fuel used in power plants is moisture. If a power plant can estimate the moisture content of the fuel before combustion, the combustion process can be adjusted to operate efficiently. Variation in moisture poses a particular challenge to the operation of the power plant’s boiler. Typically, the fluctuation caused by moisture variation has been stabilized with the help of peat, which is currently being phased out. To continue controlling the combustion process as efficiently as possible without compromising the boiler’s operation, new methods are needed to optimize the process.

 

The goal of the From Forest to Energy (MENER) project is to optimize the combustion process of wood-based fuels burned in power plants. The issue is approached through data and artificial intelligence. Through power plants and their collaborators, truck load data and process data are collected, which hasn’t been fully utilized yet. Additionally, data can be collected from the original forest locations and harvesting times, and supplemented with local storage time weather information.

 

“In the ideal scenario, the journey of wood-based fuel is known all the way from the harvesting area to the power plant’s boiler, and the fuel can be provided with the most accurate moisture forecast for different stages of the journey. The more precisely power plants know the quality characteristics of fuel coming from different sources, the better its flow can be guided at the power plants, and the combustion process optimized,” states Mr. Petri Koponen, the head of the MENER project and a senior lecturer at Kajaani University of Applied Sciences.

 

Previously, fuel quality information wasn’t available before unloading the load, which is why combustion or logistics optimization hasn’t been possible on this scale. Now that real-time quality information is available, we can achieve significant improvements on an entirely different level in enhancing both power plant energy efficiency and optimizing the logistics of timely fuel loads. The project is carried out as a collaborative effort involving Kajaani University of Applied Sciences (KAMK) and the Natural Resources Institute Finland (Luke). The work is divided so that Luke focuses on the journey of the fuel from the forest to the power plant gate, and KAMK focuses on the journey of the fuel from the gate to the boiler. The project started in June 2023, lasts for 2 years, and is funded by the Regional Council of Kainuu. The project budget is nearly 500 k€. From this, the share of KAMK is 300 k€ and the share of Luke is 200 k€.

 

The project involves several energy industry collaborators: power plants Kainuun Voima, Kuopion Energia and Oulun Energia; forestry management company Laania; automated sampling systems provider Prometec Tools; and Valmet Automation.

 

For more information:

Kajaani University of Applied Sciences

Senior lecturer and contact person for the MENER Project, Dr. Petri Koponen

+358 40 660 9709

petri.koponen@kamk.fi

 

Natural Resources Institute Finland

Research Scientist, Mr. Jari Lindblad

+358 29 532 3072

jari.lindblad@luke.fi

We will participate third time to Bio360 expo in Nantes. This time we are exhibition in Finnish pavilion H24.

We would be more than happy to tell you about our brand new innovation Q-Robot M. It is a automated sampler with moisture analyzer.

See you soon!

ENLIT Europe 2022

We will be present at the Enlit Europe fair in Frankfurt 29.11. – 1.12. You will find us together with 10 other companies at the Business Oulu stand 12.0.E80.

We will organise a Finland Afternoon at our stand on Wednesday at 15:30. Welcome!

After two years we are able to go to exhibition again.

You can download your FREE visitor pass HERE

Please find more information about the Exhibition HERE

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 Fyn is 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

Dorthe Due Head of procurement due@fjernvarmefyn.dk, +45 21 70 9259

Company links:

https://prometec.fi/en/

https://www.fjernvarmefyn.dk/

 

Moisture information available before unloading

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.

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 EN 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.

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.

Best regards,

Prometec

A certified quality management system tells our customers that our company’s processes meet the requirements set for them. Certification is also a clear indication that our organization is systematically improving its operations. Key factors for sustainable business include reliability, customer satisfaction and continuous improvement. Quality system certification demonstrates our company’s commitment to these issues. An efficient quality system ensures my company we have the ability to supply compliant products and services.