(724a) Low-CO2 Integrated Networks for Heat and Electricity Based on Hydrogen: A Comprehensive Spatio-Temporal MILP Model for Planning, Design and Operation of Future Value Chains

Samsatli, S. - Presenter, University of Bath
Demands for space and water heating constitute a significant proportion of society’s overall demand for energy and can be several times those for electricity. As heat demands are primarily satisfied using natural gas boilers, the heat sector produces a significant amount of CO2 emissions. An alternative low carbon solution is to combine heat pumps with renewable electricity but the cycling of the heat pumps can put a strain on existing electricity networks and renewable generation does not always match heat demands, particularly solar energy, which is highest in the summer months when heat demands are at their lowest. Further, large-scale seasonal electricity storage may not be possible for the foreseeable future. Therefore, another low-carbon alternative that can overcome these limitations is required and hydrogen is one of the possibilities. Low-carbon hydrogen can be produced using electrolysers powered by renewable electricity or from natural gas via steam methane reforming coupled with CCS. Clean hydrogen produced in this way has the following advantages when used as a carrier for heat: (1) it can be transported with little loss of energy, which is an advantage over electricity networks, which have losses of about 9% of production, and certainly much lower losses than transporting heat through a district heating network (which are limited in scale due to the cost and inefficiencies of transporting heat long distances); and (2) hydrogen can be stored with little or no loss. Long term direct thermal storage is generally not possible due to the difficulty in insulating the storage devices.

A mixed integer programming model was developed that can optimise different scenarios for generation, storage and transportation of renewable hydrogen to satisfy heat demands. The model considers the spatial distribution of both the heat demands and the availability of primary resources in order to make a comparison between centralised and distributed generation, as well as to determine the location of hydrogen plants and storage facilities and the transmission and distribution networks required. The temporal representation simultaneously captures the short-term operational issues, such as intermittency of renewable sources, and long-term planning decisions up to 2050 to examine different pathways from the present time to various potential optimal solutions. The model optimises the design and operational decisions to determine the most cost effective/environmentally-friendly transition to the future heat network while also determining what that network should be.


[1] S. Samsatli, N.J. Samsatli (2018). A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies. Applied Energy. DOI: 10.1016/j.apenergy.2017.09.055.

[2] S. Samsatli, I. Staffell, N.J. Samsatli (2016). Optimal design and operation of integrated wind-hydrogen-electricity networks for decarbonising the domestic transport sector in Great Britain. Int. J. of Hydrogen Energy, 41, 447-475.

[3] S. Samsatli, N.J. Samsatli (2015). A general spatio-temporal model of energy systems with a detailed account of transport and storage. Computers and Chemical Engineering, 80, 155-176.

[4] S.M. Jarvis, S. Samsatli (2018). Technologies and infrastructures underpinning future CO2 value chains: a comprehensive review and comparative analysis. Renewable & Sustainable Energy Reviews, 85, 46-68.


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