Contact: Dag Henning (

The MODEST energy-system optimisation model calculates how energy demand is covered at lowest possible cost. MODEST can include energy flows from sources via conversion and distribution to demand and measures influencing demand. An analysed energy system can consist of many different kinds of equipment and demand, which are represented with chosen level of detail. MODEST is an acronym for Model for Optimisation of Dynamic Energy Systems with Time dependent components and boundary conditions.


Existing and potential components and energy flows can have almost arbitrary combinations of properties. Input parameters include efficiencies and revenues, as well as plant and storage capacities. MODEST can also consider energy spillage, load management and emission limits. Any two components can be connected by an energy flow, and any flows can be related to each other.


Short and long term variations of costs, capacities, demand, etc. are considered by a flexible time division. A year is divided into seasons (1-99, e.g. weeks, months). Each season is divided into diurnal periods, representing any set of hours (e.g. weekend nights). Long-term studies can have many linked periods (1-99) consisting of a certain number of years.


Time-dependent availability factors can reflect wind and solar energy fluctuations and energy-conservation impact, etc. Resource use (e.g. waste heat) can be restricted for almost arbitrary sets of time periods.


MODEST has a user-friendly interface [1] for data input and output, and can be used for most energy systems where the important properties can be described by linear relations. Linear programming is used to find optimal system design and operation.


MODEST results include:

Best use of energy carriers and demand-side measures in each time period

Optimal types, sizes and occasions for investments

• Time-dependent marginal cost for covering demand [2]

• Total cost and annual cash flow of costs and revenues

• Emissions

• Duration diagram of energy supply


MODEST has been used for production of heat, electricity, steam, cooling and biofuels but can also be applied to other energy forms.


MODEST has been used for 60, primarily Swedish, district-heating systems during more than 20 years, often for studying policy instruments [3]. Interplay between waste incineration and combined heat and power (CHP) is also elucidated, e.g. [4]. Suitable CHP electricity-to-heat ratio was found to increase with electricity price [5]. District-heating-driven absorption chillers may reduce costs and CO2 emissions [6]. Electricity conservation reduces CO2 emissions more than heat savings, due to CHP [7], but decreased heat demand still reduces global CO2 emissions, and electricity price variations control CHP operation [8]. Integration of biofuel production with district heating has also been analysed [9].


Connection of some district-heating systems and industries with waste heat was studied [10]. More regional wood fuel should be used when external costs are considered [11]. A study of Swedish electricity supply showed that conservation can achieve net electricity export and reduce net CO2 emissions [12]. Biomass-CHP investments require green certificates to be profitable in the Norwegian power system [13]. The electricity system in Northern Europe, together with a district-heating system, has also been modelled with MODEST [14].


MODEST is thoroughly described in [15,16,17]. A short overview is given in [18] and a long one in [19].


1. Gebremedhin, A. Regional and Industrial Co-operation in District Heating Systems, 2003. PhD Thesis No. 849, Division of Energy Systems, Linköping University, Linköping, Sweden.

2. Sjödin, J. & Henning, D. (2004) Calculating the marginal costs of a district heating utility. Applied Energy, 78(1), pp. 1-18, 2004.

3. Henning, D., Danestig, M., Holmgren, K., Gebremedhin, A. Modelling the impact of policy instruments on district heating operations – experiences from Sweden. in: Lectures, 10th International Symposium on District Heating and Cooling, Hanover, Germany, 3-5 September 2006,

4. Holmgren, K. The role of a district heating network as a user of waste heat supply from various sources – the case of Göteborg. Applied Energy, 83, pp. 1351-1367, 2006.

5. Danestig, M., Gebremedhin, A., Karlsson, B. Stockholm CHP potential – An opportunity for CO2 reductions? Energy Policy, 35, pp. 4650–4660, 2007.

6. Trygg, L. & Amiri, S. European perspective on absorption cooling in a combined heat and power system – A case study of energy utility and industries in Sweden. Applied Energy, 84, pp. 1319–1337, 2007.

7. Difs, K., Bennstam, M., Trygg, L., Nordenstam, L. Energy conservation measures in buildings heated by district heating – A local energy system perspective. Energy, 35, pp. 3194-3203, 2010.

8. Åberg, M., Widén, J., Henning, D. Sensitivity of district heating system operation to heat demand reductions and electricity price variations – A Swedish example. Energy, 41(1), pp. 525-540, 2012.

9. Djuric Ilic, D., Dotzauer, E., Trygg, L., Broman, G. Introduction of large-scale biofuel production in a district heating system – an opportunity for reduction of global greenhouse gas. Journal of Cleaner Production, 64(1), pp. 552-561, 2014.

10. Karlsson, M., Gebremedhin, A., Klugman, S., Henning, D., Moshfegh, B. Regional energy system optimization – Potential for a regional heat market. Applied Energy, 86, pp. 441-451, 2009.

11. Carlson, A. Energy Systems and the Climate Dilemma – Reflecting the Impact on CO2 emissions by Reconstructing Regional Energy Systems. Energy Policy, 31(10), pp. 951-959, 2003.

12. Henning, D. & Trygg, L. Reduction of Electricity Use in Swedish Industry and its Impact on National Power Supply and European CO2 Emissions. Energy Policy, 36(7), pp. 2330-2350, 2008.

13. Gebremedhin, A. & De Oliveira Granheim, J. Is there a space for additional renewable energy in the Norwegian power system? Potential for reduced global emission? Renewable and Sustainable Energy Reviews, 16, pp. 1611-1615, 2012.

14. Gebremedhin, A. Optimal utilisation of heat demand in district heating system – A case study. Renewable and Sustainable Energy Reviews, 30, pp. 230-236, 2014.

15. Henning, D. Cost Minimization for a Local Utility through CHP, Heat Storage and Load Management. International Journal of Energy Research, 22(8), pp. 691-713, 1998.

16. Henning, D. Optimisation of Local and National Energy Systems – Development and Use of the MODEST Model, 1999. PhD Thesis No. 559, Division of Energy Systems, Linköping University, Linköping, Sweden.

17. Henning, D., Amiri, S., Holmgren, K. Modelling and optimisation of electricity, steam and district heating production for a local Swedish utility. European Journal of Operational Research, 175(2), pp. 1224-1247, 2006.

18. Optensys Energianalys AB,

19. Henning, D. MODEST: Model for Optimization of Dynamic Energy Systems with Time dependent components and boundary conditions. in: Interdisciplinary Energy System Methodology: A compilation of research methods used in the Energy Systems Programme, ed. M. Karlsson, J. Palm, J. Widén, Arbetsnotat Nr 45, Program Energisystem, IEI, Linköping University, Linköping, Sweden, 2011, pp. 44-51,