SmartCHP project

SmartCHP is an EU-funded project (Grant n° 815259), coordinated by BTG, that aims at developing a novel and flexible small-scale cogeneration unit to produce heat and electricity from sustainable biomass, through fast-pyrolysis oil, for the tertiary sector. The long-term objective is thus to boost the use of renewables in the electricity and heating and cooling sectors, contributing to the 2030 climate and energy targets.

DOWEL led the work package 6 “Market assessment, business development and case studies” that aimed to determine the most likely end-users of the SmartCHP solution and the associated market segments; assess their commercial potential; conduct a techno-economic analysis to appraise the competitiveness of the SmartCHP system; list the relevant standards, the possible regulatory barriers and provide policy recommendations.

Highlights on the techno-economic analysis

The SmartCHP techno-economic analysis has been realised by DOWEL, to determine the best conditions at which SmartCHP would be profitable in the future. This analysis was based on the data available at prototype stage, since the project ended at TRL5. To assess the profitability of seven use cases, an Excel simulator has been developed.

Over the project duration, DOWEL developed and implemented the following methodology:

1/ Preparatory works

  1. Technical understanding
    A first step consisted in the analysis of the SmartCHP unit based on technical drawings and numerous exchanges with consortium experts, to identify all technical elements having an impact on the installation’s profitability, and its efficiency. A data collection process on these technical features was then initiated as well as the first architecture of the profitability simulator.
  2. Use cases selection
    The selection of use cases was based on the results of the market analysis, which identified the countries (Croatia, Greece, Netherlands, Romania and Sweden) and the costumers’ segments (Educational buildings, hotels, office buildings, hospitals, retails and greenhouses) that could be of interest to deploy SmartCHP units. Energy data (power and heat consumption, as well as power production when the use case was coupled with solar panels or wind energy). This data was collected through literature review and direct contacts. Some of the data collected through literature review represented a yearly consumption and was enhanced at a smaller time step (daily) to allow their processing. This process was based on local weather data and typical energy consumption patterns for similar end-users.
  3. Determination of OPEX and CAPEX
    OPEX and CAPEX definition was part of a specific task conducted by SmartCHP’s partner Abato Motoren. This data was integrated in DOWEL’s model for profitability assessment. A major part of the OPEX was the FPBO (fuel) price, which was given by BTG, the coordinator. For this profitability analysis, regional price differences have not been considered: OPEX and CAPEX were calculated based on Dutch prices. A flat rate for terrestrial transport has been taken into account as part of the OPEX. The flat rate was also the same for all use cases except for one (Greenhouse in the Netherlands) that had an additional need for maritime transport, to import FPBO from Sweden to the Netherlands. For this use case, quotations for maritime transport were asked and the associated costs were added to the OPEX for the profitability analysis.

2/ Profitability analysis per use case

  1. Adjustments of technical parameters and sizing of SmartCHP units for each use case
    The use case selection had an important impact on the techno-economic parameters, that needed to be adjusted. Once the energy data from a use case entered into the Excel simulator, the optimal size of the SmartCHP unit needed to be identified, among the six different sizes of SmartCHP: 100kWe, 175 kWe, 250kWe, 500kWe, 750kWe and 1000kWe. Then the use case’s country was selected. This country choice, and therefore the feedstock used to produce FPBO, influenced the FPBO calorific values and therefore the unit’s efficiency and OPEX.
  2. Calculation of a reference bill
    To assess the profitability of SmartCHP, its costs are compared to a “reference bill”. This “reference bill” is a fictive energy bill resulting from the energy actual consumption valorised at the local market energy prices (taken from Eurostat). This energy bill is fictive, because energy contracts for non-residential customers are dependent on many factors, including the energy providers, specific negotiations and the type of energy used for heat. However, the actual energy bills remain, most of the time, confidential.
  3. Selection of operation modes and priorities
    Based on all parameters previously entered in the simulator and in light of the energy consumption patterns specific to the use case, operation modes (when is the CHP running, when is it off? do we have a different operation mode for day and night?) and priorities (does the CHP aim to cover the base heat needs, base power needs or the peak heat or power needs?) are selected. For example, schools are often closed during the summer, and it may therefore be more profitable to turn the CHP off, while hotels may be running only during summer, at least in touristic sites. For most use cases, these were adapted at the monthly or bi-monthly time step which appeared to be a relevant proxy to capture the energy value of the system.
    The profitability of three use cases was also tested using the flexible control developed by DTU, partner of the project. This control allows instant adaptation to the end-user’s needs, based on the clustering of energy consumption data (see papers developed as part of the project by DTU).
  4. Calculation of SmartCHP’s bill with excel simulator
    The Excel simulator calculates the energy unbalances (when are power and heat produced in excess or when do we need the grid and a boiler to cover the end-user’s energy needs?) created by SmartCHP, and the resulting energy costs over a period of 15 years (estimated SmartCHP’s minimum lifetime). A financial analysis is then conducted to assess the profitability of the installation in the given use case, and the most impacting factors on this profitability.
  5. Sensitivity analysis, including flexibility
    SmartCHP as an energy system reaches the maturity of TRL5 in 2024 still requires R&I and industrialisation efforts. Indeed since some very important parameters may change until it is, sensitivity analyses were conducted to assess the range of expected profitability while changing a set of critical parameters such as operational expenditures and energy prices.


This study has demonstrated an interesting economic potential of SmartCHP. The installation can indeed become very profitable under various circumstances, and this profitability is expected to grow with a lower CAPEX (due to higher TRL levels) and constantly increasing energy prices, which is definitely a profitability driver.

Furthermore, the installation provides other benefits that will be attractive to customers, including its potential for flexibility and sustainability. The flexible control indeed proves to be very efficient and reduces both the costs for additional heat and electricity in all cases.

The EC funded project has ended in November 2023 and enters a new stage of industrial development.

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