(258d) Optimisation-Based Strategic Energy System Planning with Hydrogen Integration for Heat and Power Decarbonisation

Fossil fuel combustion stands as the primary driver behind the increased concentrations of greenhouse gases in the atmosphere, which are responsible for global temperature rise. In order to hedge against climate change adverse effects, there is a growing urgency to pursue Net-Zero target and explore low-carbon alternative pathways towards emissions reduction. The UK was the first major economy globally, which legislated to reach zero carbon emissions by 2050. A Net-Zero Strategy was published setting out clear policies and proposals for a decarbonised economy [1]. Delivering this target requires actions towards energy sector including heat and power decarbonisation which accounts for 21% and 10% of the carbon footprint in the UK, respectively [2]. Thus, reducing CO­₂ emissions from buildings is central to the challenge of meeting carbon budgets. To achieve this, the phase out of natural gas boilers is required while the most prominent decarbonisation routes include the electrification of heat and hydrogen based heat systems [3]. In this context, hydrogen constitutes a key element in reducing the environmental footprint of energy systems either with its direct use as an alternative of natural gas or as an energy carrier for renewable energy generation.

In the last decade, energy systems models aiming at heat decarbonisation have received considerable attention in the literature. Many works developed mathematical models to investigate the impact of the electrification of the heat sector using different case studies [4-6]. Moreover, the transition of the heat sector to a hydrogen-based infrastructure was studied using mathematical optimisation [7-8]. However, the examination of the entire system concurrently is essential to provide a more holistic view and get insights for strategical decisions regarding future energy mix [9-11]. Similarly, power decarbonisation was studied using energy system models that assess the integration of low-carbon technologies and grid expansion strategies to support deep emissions reductions [12-13].

In this work, we propose a spatially explicit multi-period Mixed Integer Linear Programming (MILP) framework for infrastructure decisions planning to achieve Net-Zero emissions in the heat and power sector. The model considers 13 regions in Great Britain according to local gas distribution zones. Representative days with hourly resolution are incorporated in each year-bin to capture demand variability and renewables availability. The proposed model considers both hydrogen and electrification route and simultaneously optimises operating and investment decisions to provide useful insights regarding the performance of a future energy system. Due to the spatio-temporal resolution and the number of considered technologies, the model exhibits a significant combinatorial complexity, leading to intractable computational times. Thus, novel decomposition and clustering techniques are employed to preserve the quality of the solutions while reducing computational effort. The investigated case study demonstrates the applicability of the model in infrastructure development for heat and power in the UK up to 2050. Using real-world gas consumption data, we perform an in-depth analysis on the optimal role of hydrogen and the strategic investment of power and heat technologies across the domestic, commercial and industrial heat sectors in order to answer the question of the primary role of hydrogen in the a future decarbonised energy system.

Acknowledgments

The financial support from the Engineering and Physical Sciences Research Council (EPSRC) under the project EP/T022930/1 is gratefully acknowledged.

References

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