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Electricity- and hydrogen-based sector coupling contributes to realizing the transition towards greenhouse gas neutrality in the European energy system. Energy system and integrated assessment models show that, to follow pathways compatible with the European policy target of net-zero greenhouse gas emissions by 2050, large amounts of renewable electricity and H 2 need to be generated, mostly by scaling-up wind and solar energy production capacity. With a set of such models, under jointly adopted deep decarbonisation scenario assumptions, we here show that the ensuing direct penetration of electricity and H 2 in final energy consumption may rise to average shares of around 60% and 6%, respectively, by 2050. We demonstrate that electrification proves the most cost-efficient decarbonisation route in all economic sectors, while the direct use of H 2 in final energy consumption provides a relatively small, though essential, contribution to deep decarbonisation. We conclude that the variance observed across results from different models reflects the uncertainties that abound in the shape of deep decarbonisation pathways, in particular with regard to the role of H 2 . Multiple energy system models are used under jointly adopted deep decarbonisation scenarios to conclude that the direct penetration of electricity and hydrogen in final energy consumption may rise to shares of, respectively, 60% and 6%, in Europe by 2050.

Ethiopia is a low-income country, with low electricity access (45%) and an inefficient power transmission network. The government aims to achieve universal access and become an electricity exporter in the region by 2025. This study provides an invaluable perspective on different aspects of Ethiopia’s energy transition, focusing on achieving universal access and covering the country’s electricity needs during 2015–2065. We co-developed and investigated three scenarios to examine the policy and technology levels available to the government to meet their national priorities. To conduct this analysis, we soft-linked OnSSET, a modelling tool used for geospatial analysis, with OSeMOSYS, a cost-optimization modelling tool used for medium to long-run energy planning. Our results show that the country needs to diversify its power generation system to achieve universal access and cover its future electricity needs by increasing its overall carbon dioxide emissions and fully exploit hydropower. With the aim of achieving universal access by 2025, the newly electrified population is supplied primarily by the grid (65%), followed by stand-alone (32%) technologies. Similarly, until 2065, most of the electrified people by 2025 will continue to be grid-connected (99%). The country’s exports will increase to 17 TWh by 2065, up from 832 GWh in 2015, leading to a cumulative rise in electricity export revenues of 184 billion USD.

National infrastructure systems spanning energy, transport, digital, waste, and water are well recognised as complex and interdependent. While some policy makers have been keen to adopt the narrative of complexity, the application of complexity-based methods in public policy decision-making has been restricted by the lack of innovation in associated methodologies and tools. In this paper we firstly evaluate the application of complex adaptive systems theory to infrastructure systems, comparing and contrasting this approach with traditional systems theory. We secondly identify five key theoretical properties of complex adaptive systems including adaptive agents, diverse agents, dynamics, irreversibility, and emergence, which are exhibited across three hierarchical levels ranging from agents, to networks, to systems. With these properties in mind, we then present a case study on the development of a system-of-systems modelling approach based on complex adaptive systems theory capable of modelling an emergent national infrastructure system, driven by agent-level decisions with explicitly modelled interdependencies between energy, transport, digital, waste, and water. Indeed, the novel contribution of the paper is the articulation of the case study describing a decade of research which applies complex adaptive systems properties to the development of a national infrastructure system-of-systems model. This approach has been used by the UK National Infrastructure Commission to produce a National Infrastructure Assessment which is capable of coordinating infrastructure policy across a historically fragmented governance landscape spanning eight government departments. The application will continue to be pertinent moving forward due to the continuing complexity of interdependent infrastructure systems, particularly the challenges of increased electrification and the proliferation of the Internet of Things.

Africa’s economic and population growth prospects are likely to increase energy and water demands. This quantitative study shows that energy decarbonisation pathways reduce water withdrawals (WWs) and water consumption (WC) relative to the baseline scenario. However, the more aggressive decarbonisation pathway (1.5 °C) leads to higher overall WWs than the 2.0 °C scenario but lower WC levels by 2065. By 2065, investments in low-carbon energy infrastructure increase annual WWs from 1% (52 bcm) in the 2.0 °C to 2% (85 bcm) in the 1.5 °C scenarios of total renewable water resources in Africa compared to 3% (159 bcm) in the baseline scenario with lower final energy demands in the mitigation scenarios. WC decreases from 1.2 bcm in the 2.0 °C to 1 bcm in the 1.5 °C scenario, compared to 2.2 bcm in the baseline scenario by 2065, due to the lower water intensity of the low-carbon energy systems. To meet the 1.5 °C pathway, the energy sector requires a higher WW than the 2.0 °C scenario, both in total and per unit of final energy. Overall, these findings demonstrate the crucial role of integrated water-energy planning, and the need for joined-up carbon policy and water resources management for the continent to achieve climate-compatible growth.

Modeling energy systems with a large share of cascaded hydropower requires an adequate representation of reservoir and plant interactions within a national power system. However, many energy system models rely on simplified or aggregated hydropower representations that neglect hydraulic interconnections, affecting operational results. This study quantifies the compound impact of hydropower cascade simplification, comprising hydraulic topology, inflow representation, and parameters aggregation, on national power system modeling. A hydropower cascade formulation is integrated into the open-source Dispa-SET unit commitment and economic dispatch model and compared with two simplified formulations with different levels of hydraulic detail, typically applied in mid and long-term energy system models. The analysis is applied to the Bolivian power system, where hydropower represents a significant share of electricity generation. The results show that simplified formulations significantly impact system operation. Hydropower generation is overestimated during the wet season and underestimated during the dry season. This leads to operational cost underestimation of 7% and up to 28.9% during the wet season depending on the formulation, and affects key operational indicators, including transmission congestion, reservoir operation, and the detection of shed load events. These findings highlight the importance of explicitly representing hydropower cascade dynamics when assessing the operation of hydro-dominated national power systems.

Located in Southern Europe, the Drina River Basin is shared between Bosnia and Herzegovina, Montenegro, and Serbia. The power sectors of the three countries have an exceptionally high dependence on coal for power generation. In this paper, we analyse different development pathways for achieving climate neutrality in these countries and explore the potential of variable renewable energy (VRE) and its role in power sector decarbonization. We investigate whether hydro and non-hydro renewables can enable a net-zero transition by 2050 and how VRE might affect the hydropower cascade shared by the three countries. The Open-Source Energy Modelling System (OSeMOSYS) was used to develop a model representation of the countries’ power sectors. Findings show that the renewable potential of the countries is a significant 94.4 GW. This potential is 68% higher than previous assessments have shown. Under an Emission Limit scenario assuming net zero by 2050, 17% of this VRE potential is utilized to support the decarbonization of the power sectors. Additional findings show a limited impact of VRE technologies on total power generation output from the hydropower cascade. However, increased solar deployment shifts the operation of the cascade to increased short-term balancing, moving from baseload to more responsive power generation patterns. Prolonged use of thermal power plants is observed under scenarios assuming high wholesale electricity prices, leading to increased emissions. Results from scenarios with low cost of electricity trade suggest power sector developments that lead to decreased energy security.

This study applies Global Sensitivity Analysis (GSA) to an optimization model for Kenya based on the Climate, Land, Energy, and Water systems (CLEWs) framework. The model provides insights into the interdependencies among energy, land, and water systems, and the sensitivity analysis allows to evaluate its ability to capture sectoral interactions and trade-offs while identifying key influential parameters shaping the overall system behavior. Using the Morris screening method, the analysis emphasizes the key role of discount rates—both global and technology- specific—influencing the energy sector, biomass use for cooking, renewable energy sources penetration, and forest land cover. The findings also show that all inputs influence forest cover, demonstrating the CLEWs model’s capacity to capture system interactions. By using a fully open methodology, this work enhances CLEWs model transparency and provides actionable insights for policymakers to address trade-offs and support resilient resource management.

This study explores the implications of technology availability constraints on the decarbonisation pathways of the EU power sector, drawing on scenario results from five European energy supply models: MEESA, LIMES, ENERTILE, ACSG, and OSeMBE. The analysis evaluates how limiting the deployment of key low-carbon generation technologies, namely carbon capture and storage (CCS), nuclear power, bioenergy, solar photovoltaics, and wind energy, affects the electricity generation mix, emissions reduction, investment needs, and power system costs by 2030 and 2050. Results within the model ensemble indicate that variable renewable energy sources (VRE), wind and solar, are indispensable for deep decarbonisation. Constraints on solar or wind power substantially increase electricity generation costs and require major shifts in technology portfolios, often resulting in greater reliance on remaining renewable options or fossil fuel generation with CCS. The unavailability of CCS leads to higher system emissions and increased investment in renewables and storage. In contrast, removing nuclear or bioenergy has a more moderate impact, though some regional effects are significant. All models show that achieving ambitious emission reductions in the power sector remains technically feasible under individual technology constraints, but the mitigation effort shifts across generation technologies, and system costs rise considerably in low VRE futures. Policy implications include the need for robust support for wind and solar deployment, cross-border system integration, flexible technologies, and backup capacity. The findings underscore the value of a diversified technology portfolio, strategic infrastructure investments, and EU-level coordination to preserve cost efficiency and ensure stable power system performance under uncertainty in future technology availability.

The Nationally Determined Contributions (NDCs) are key documents providing the starting point for increasingly ambitious ‘pledge-and-review’ cycles leading to the implementation of the Paris Agreement. However, current NDCs often lack consistent and transparent targets and indicators to ensure their in-country realisation and their monitoring, tracking, and reporting in compliance with the current climate change regime. This is particularly true for developing countries, where resources and capacity to define and implement climate action plans are still largely lacking among practitioners. To tackle this problem, this essay proposes a framework for NDCs development focusing on the practitioners’ – i.e., modellers and expert analysts – uptake of open science practices, particularly concerning open-source tools and open data, via capacity-building initiatives as a first step towards transparent and accountable NDCs delivery and implementation to the benefit of national and international climate governance. The framework is applied to the case study of Costa Rica, to test its relevance and applicability.

Legislation to decarbonise energy systems within overall greenhouse gas reduction targets represents an immense and unprecedented energy policy challenge. However there is a dichotomy between this level of policy ambition and prior modelling studies that find such targets economically, technologically and socially feasible under idealised ― first-best policies. This paper makes a significant contribution to current analytical efforts to account for realistic ― second-best climate mitigation policy implementation. This is achieved via a technical classification of secondbest common mode issues at a detailed national level: both internal (behavioural change, infrastructure implementation) and external (new technologies, resource availability). Under a combinatory second-best scenario, meeting targets greater than a 70% reduction in CO 2 by 2050 entail costs above a subjective barrier of 1% of GDP, while extreme mitigation scenarios (>90% CO 2 reduction) are infeasible. These high costs are equally due to disappointing progress in behavioural and technological mitigation efforts. Expensive second-best mitigation scenarios can still rely on extreme assumptions including the full deployment of the UK‘s offshore wind resource or the complete diffusion of energy efficiency measures in end-use sectors. By demonstrating the fragilities of a low carbon energy system pathway, policy makers can explore protective and proactive strategies to ensure targets can actually be met. Additionally, systematic analysis of failure in stringent long term decarbonisation scenarios teaches energy analysts about the trade-offs in model efficacy vs. confidence.