Applied Energy, Vol.233, 854-893, 2019
The role of renewable hydrogen and inter-seasonal storage in decarbonising heat - Comprehensive optimisation of future renewable energy value chains
Demands for space and water heating constitute a significant proportion of the total energy demands in Great Britain and are predominantly satisfied through natural gas, which makes the heat sector a large emitter of carbon dioxide. Renewable hydrogen, which can be injected into the gas grid or used directly in processes for generating heat and/or electricity, is being considered as a low-carbon alternative energy carrier to natural gas because of its suitability for large-scale, long- and short-term storage and low transportation losses, all of which help to overcome the intermittency and seasonal variations in renewables. This requires new infrastructures for production, storage, transport and utilisation of renewable hydrogen - a hydrogen value chain - the design of which involves many interdependent decisions, such as: where to locate wind turbines; where to locate electrolysers, close to wind generation or close to demands; whether to transport energy as electricity or hydrogen, and how; where to locate storage facilities; etc. This paper presents the Value Web Model, a novel and comprehensive spatio-temporal mixed-integer linear programming model that can simultaneously optimise the design, planning and operation of integrated energy value chains, accounting for short-term dynamics, inter-seasonal storage and investments out to 2050. It was coupled with GIS modelling to identify candidate sites for wind generation and used to optimise a number of scenarios for the production of hydrogen, from onshore and offshore wind turbines, in order to satisfy heat demands. The results show that over a wide range of scenarios, the optimal pathway to heat is roughly 20% hydrogen and 80% electricity. Hydrogen storage, both in underground caverns and pressurised tanks, is a key enabling technology.
Keywords:Hydrogen for heat;Hydrogen supply chain;Value chain optimisation;MILP;Value Web Model;Design, planning and operation;Integrated multi-vector networks