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Abstract
District energy provides opportunity for effective integration between energy sectors, particularly electricity, heating, cooling and fuels. Analysing and optimising the operation of district energy plants is possible in the software tool energyPRO. This tool is widely applied in industry and academia. The user must manually define sets of technologies and their capacities, whereafter energyPRO optimises the operation. Since choice of optimal investment is often the purpose of such analyses, adding investment optimisation to the capabilities of energyPRO would be a substantial improvement.
As an intermediary step towards adding the capability of optimising investments in energyPRO, this report documents the development of automated model-runs and selection of optimal investments. It is directly applicable for the advanced user with the sufficient licensing for energyPRO and is provided as is and with no responsibility for the outcomes.The development is documented through analysis of a generic case, optimising on the capacities of CHP engines, thermal storage and heat pump. From an iterative VBA code, different configurations were found with the accompanying set of net present values. From these, the maximum net present value was identified.
As it the case with the combination of detailed operational optimisation and investment optimisation, the computational requirements increase substantially with the amount of variables. Thus, the investment optimisation is feasible with a limited set of options, unless substantial computing capacity is available.
As an intermediary step towards adding the capability of optimising investments in energyPRO, this report documents the development of automated model-runs and selection of optimal investments. It is directly applicable for the advanced user with the sufficient licensing for energyPRO and is provided as is and with no responsibility for the outcomes.The development is documented through analysis of a generic case, optimising on the capacities of CHP engines, thermal storage and heat pump. From an iterative VBA code, different configurations were found with the accompanying set of net present values. From these, the maximum net present value was identified.
As it the case with the combination of detailed operational optimisation and investment optimisation, the computational requirements increase substantially with the amount of variables. Thus, the investment optimisation is feasible with a limited set of options, unless substantial computing capacity is available.
Original language | English |
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Publisher | DTU Management Engineering |
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Number of pages | 19 |
Publication status | Published - 2021 |
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Dive into the research topics of 'Automating analyses and exploring investment optimisation in energyPRO'. Together they form a unique fingerprint.Projects
- 1 Finished
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Heat 4.0 Digitally supported District Heating
Liu, X. (Project Manager), Nielsen, P. S. (Project Manager), Ben Amer, S. (Project Participant), Dai, W. (Project Participant), Buchholz, S. (Project Participant), Petrovic, S. (Project Participant), Scheller, F. (Project Participant), Keles, D. (Project Participant), Nielsen, V. (Project Participant) & Khan, B. S. (Project Participant)
15/04/2019 → 14/08/2022
Project: Research