Authors: Merlinda Andoni, Benoit Couraud, Valentin Robu, Jamie Blanche, Sonam Norbu, Si Chen, Satria Putra Kanugrahan, David Flynn

Abstract:

Amid global interest in resilient energy systems, green hydrogen is considered vital to the net-zero transition, yet its deployment remains limited by high production cost. The cost is determined by the its production pathway, system configuration, asset location, and interplay with electricity markets and regulatory frameworks. To compare different deployment strategies in the UK, we develop a comprehensive techno-economic framework based on the Levelised Cost of Hydrogen (LCOH) assessment. We apply this framework to 5 configurations of wind-electrolyser systems, identify the most cost-effective business cases, and conduct a sensitivity analysis of key economic parameters. Our results reveal that electricity cost is the dominant contributor to LCOH, followed by the electrolyser cost. Our work highlights the crucial role that location, market arrangements and control strategies among RES and hydrogen investors play in the economic feasibility of deploying green hydrogen systems. Policies that subsidise low-cost electricity access and optimise deployment can lower LCOH, enhancing the economic competitiveness of green hydrogen.

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Authors: Mohamed Abuella , Adib Allahham, Sara Walker

Abstract:

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Authors: Sonam Norbu, Benoit Couraud, Valentin Robu, Merlinda Andoni, Si Chen, Jennifer Challinor, Gwilym Gibbons, H. Vincent Poor, David Flynn

Abstract:

Community-based energy initiatives, such as local energy markets (LEMs), are gaining attention as a means to foster a more equitable and participatory energy transition. To fulfill this potential, local communities require robust energy-sharing mechanisms that ensure the fair distribution of financial benefits among participants. This paper presents a novel algorithm for virtual energy distribution in a Peer-to-Community (P2C) local energy market. The algorithm first determines the optimal number of participants in each time period of the LEM, based on their current energy supplier tariffs, to ensure benefits for all participants. It then applies an egalitarian energy-distribution method, called the Glass-Filling algorithm, to allocate locally produced energy within the community. Using real-world data from a UK trial involving 200 households, half of which are prosumers with solar PV and residential batteries, we demonstrate that the proposed mechanism improves equity in energy sharing compared with a benchmark double-auction mechanism. The proposed market mechanism yields an average annual bill reduction of 9.9% for producers and 5% for consumers.

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Authors: Zoya Pourmirza, Mehmet Bozdal, Mohamad Khalil, Emily Judson, Sara Walker

Abstract:

Modern energy systems face increasing operational challenges due to the growing penetration of renewables, variability in generation and network congestion, which contribute to curtailment, inefficiencies and avoidable emissions. These issues constrain system flexibility and hinder progress towards net-zero targets. Digitalisation offers a means to address these challenges by improving system observability, enabling real-time coordination and supporting data-driven decision-making through technologies such as the Internet of Things, artificial intelligence and digital twin. As a result, digitalisation has enhanced the efficiency, reliability and flexibility of energy systems, supporting progress towards net-zero emissions targets. This paper reviews key technologies that enable energy system digitalisation and examines challenges arising from increased connectivity. Unlike existing studies that consider individual technologies, market mechanisms or policy frameworks in isolation, this work adopts an integrated perspective encompassing enabling technologies, data-driven applications, data governance and cyber security within digitalised energy systems. This study is guided by a horizon scanning methodology to identify emerging technological and cyber-physical challenges shaping future energy system design. Additionally, a six-dimensional framework for energy data governance is used to structure current practices and identify gaps related to data quality, discoverability, sharing, privacy and emerging responsibilities. This paper offers actionable insights for researchers, policymakers and industry stakeholders while identifying areas that require further technical and regulatory development.

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Authors: Hu Q, Li G, Huang B, Yang Q, Sun S, Bie Z, Wu J, Zhou Y, Bian Y

Abstract:

Time-varying renewable energy sources (RES), influenced by climate conditions, create seasonal power mismatches. Allocation of hydrogen energy storage (HES) can mitigate long-duration seasonal power mismatch caused by load variation, climate variability and seasonal meteorological conditions. However, one single uncertainty set cannot well consider the characteristics of RES uncertainty in different seasons impacted by long-term climate conditions. To address the above challenges and optimally size and allocate HES in power systems, this paper proposes a hybrid tri-level planning framework that integrates RES interannual long-term and seasonal fluctuation, using a combination of distributionally robust optimization (DRO) and adaptive robust optimization (ARO). Specifically, a RES probability distribution ambiguity set under typical climate conditions is constructed using norm constraints, and data-driven DRO is introduced to address RES long-term uncertainty. RES seasonal uncertainty is then
adaptively modelled using multiple uncertainty sets based on the seasonal meteorological characteristics of RES, and ARO is proposed to reformulate the lower-level problem for the worstcase scenarios. The proposed framework is solved using the
improved column and constraint generation algorithm (C&CG) with duality-free decomposition. Simulations on IEEE 39-bus system and IEEE 118-bus system confirm the effectiveness of the proposed planning framework and solution algorithm.

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Authors: Peihao Chen, Dawei Wu, Yiqing Yang, Yan Zhang, Athanasios Tsolakis, Karl Dearn

Abstract:

Current hybrid wave–tidal energy conversion technologies remain inadequate in fully leveraging the complementarity between wave and tidal energy, limiting overall efficiency and output stability. Moreover, conventional modeling approaches rely on idealized continuous sinusoidal wave inputs, making them unsuitable for capturing real ocean conditions or performing time-domain analysis. To address these gaps, this study proposes a hybrid wave-tidal energy converter (HWTEC) featuring a nonlinear motions rectification and coupling device (NLMRCD). Within the NLMRCD, a mechanical motion rectifier (MMR) converts reciprocating wave motion into unidirectional rotation, mitigating energy loss from frequent motion reversals. A bevel gearbox with one-way clutches couples wave and tidal energy inputs, enhancing power continuity and increasing voltage output. A novel discretization modeling methodology is developed to characterize the nonlinear interaction between wave and tidal modules. It accepts discrete input data and automatically identifies overrunning phases, simplifying time-domain calculations without requiring continuous input functions. Simulations under ocean-like conditions yield a peak power output of 18.72 W and an efficiency of 60.94 %. Experimental validation on a custom dual-input test bench confirmed these results, achieving 19.65 W and 61.34 %, respectively. The NLMRCD enhances output power and voltage stability by coupling intermittent wave and tidal energy, thereby improving system usability and conversion efficiency. The proposed discretization modeling approach overcomes limitations of continuous inputs in traditional methods, and offers a robust framework for simulation using measured wave data.

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Authors: Joseph A, Allahham A, Walker S

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Meeting carbon reduction targets and enhancing energy supply flexibility necessitate the integration of natural gas and electricity networks, coupled with increased adoption of renewable energy. Bidirectional hydrogen-based Vector-Coupling Storage (VCS) offers a promising avenue for efficiently utilising surplus power from renewables, linking hydrogen as an energy carrier and storage with the Integrated Energy System (IES). This paper introduces a game-theoretic planning model for IES, encompassing natural gas, electricity, and independent VCS participants in a liberalised market. A game-theoretic model for capacity investment under an oligopolistic market structure in the liberalised energy market context is developed to capture the strategic behaviour of market participants. An annual investment model and an hourly operation simulation model are used to evaluate the value of hydrogen production, coupling components, and vector coupling storage in long-term investment decisions. The model, applied to the North of Tyne region in the UK, employs a scaled-down Future Energy Scenario dataset, reflecting a regional trajectory towards a net-zero emission target by 2050. Simulation results highlight market liberalisation’s crucial role in attracting investments in renewable energy and hydrogen systems. Conversion efficiencies of electrolysers and fuel cells emerge as key profitability determinants, emphasising the significance of achieving at least 50% round trip efficiency for profitable vector coupling storage. The findings quantify the advantages of large-scale VCS investments over Li-ion battery storage.

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Authors: Hadi Heidary, Vahid Nasrollahi, Daniel Wilmot, Jacob Bracegirdle-Morais, Sophie C. Cox, Stefan Dimov, Moataz M. Attallah, Ahmad El-kharouf, Sara Walker, Robert Steinberger-Wilckens

Abstract: The integration of hydrogen fuel cells into aerospace applications is limited by the weight and volume of fuel cell systems. Currently, bipolar plates account for 80 % of fuel cell stack mass and 60 % of its volume. Herein, we leverage a range of advanced manufacturing techniques to develop novel lightweight-compact porous distributors with ultrahigh power densities. Research begins with a graphene-coated nickel foam porous distributor, which enhances reactants transport and interfacial conductivity, achieving a power density of 1.52 W/cm², ∼50 % improvement over conventional designs. To further boost gravimetric power density, titanium was adopted as a base material, and porous architectures were optimized using Computational Fluid Dynamics to ensure optimal reactant distribution and water management. To realize these porous titanium designs, two advanced manufacturing techniques were leveraged: laser powder bed fusion (LPBF) and laser micromachining. While the optimized LPBF lattice structure reached 1.36 W/cm², the laser-patterned non-homogeneous architecture demonstrated a breakthrough performance of 1.62 W/cm², translating to volumetric and gravimetric power densities of over 10 kW/L and 9 kW/kg, respectively. These values surpass current commercial benchmarks and exceed EU/UK 2030 targets. We demonstrate how integrating digital design, flow control, advanced materials, and manufacturing enables lightweight, high-power fuel cells, with broader impact on electrolyzers, heat exchangers, and batteries.

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Authors: Vargas-Ferrer, P., Sauma, E., Jalil-Vega, F.

Abstract:

The integration of variable renewable energy sources (VRE) and electrolytic hydrogen production is a key factor in the cost-effective production of hydrogen. The challenge lies in designing systems where electrolyzers can flexibly adapt to the inherent temporal variability of VRE sources. This relationship is difficult to model, as it involves phenomena across a wide range of timescales, from sub-hourly fluctuations to long-term operational dynamics. In this work, we propose a mathematical model to represent the behavior of a renewable hydrogen production system over its lifetime, incorporating sub-hourly information on the balance between renewable generation and the flexibility of the electrolysis stage. Our approach is unique because it takes detailed sub-hourly behavior and efficiently embeds it into a standard hourly framework. It allows us to realistically model the complex interplay between VRE generation and electrolyzer flexibility over a system’s entire lifespan. The model is evaluated at four locations in Chile – two wind-based and two solar PV-based – and a variety of scenarios are constructed considering factors such as the temporal hydrogen dispatch profile, the flexibility of the alkaline electrolysis stage, and the electrolysis technology mix. Based on projected costs for the year 2030, the main results show that the levelized cost of hydrogen across the four sites ranges from $2.96 to $7.59/kg, although these values can be significantly affected by the temporal profiles of hydrogen dispatch. It was found that modeling intra-hourly characteristics can alter levelized cost predictions by up to 10 %. We also found that the optimal technology mix is influenced by the renewable resource. Specifically, wind-based sites need more flexible proton exchange membrane electrolysis capacity to handle their high sub-hour variability, whereas sites with less variable photovoltaic sources can rely more on alkaline technology.

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Authors: Khalid Alanazi, Nilay Shah, Shivika Mittal, Adam Hawkes

Abstract:

Global renewable hydrogen trade is expected to play a key role in decarbonizing future energy systems. Yet hydrogen exporters may deviate from perfectly competitive behaviour to influence prices, similarly to the existing fossil fuel market, with important implications for consumer welfare and the pace of the energy transition. This study develops a global renewable hydrogen trade model that captures potential strategic interactions among exporters using a Stackelberg game-theoretic framework. The model is formulated as an Equilibrium Problem with Equilibrium Constraints (EPEC) and solved under three alternative equilibria: a profit-maximizing Nash equilibrium, a cost-minimizing Nash equilibrium, and a welfare-maximizing benchmark representing perfect competition. Results indicate that producers may strategically reduce their export quantities by up to 40 % relative to perfect competition to maximize profits. Such behaviour raises prices to a minimum of 4.5 USD/kg in 2050 across major import markets, thereby significantly eroding consumer surplus. Strategic behaviour of dominant exporters also shifts trade flows, reshaping the global allocation of hydrogen supply. Sensitivity analysis further reveals that financing costs play a key role in shaping strategic producers’ behaviour, with lower financing costs helping to reduce prices and stimulate demand. These findings highlight the implications of imperfect competition in global hydrogen trade and suggest that policy measures may be needed to mitigate potential negative consequences.

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