PhD: Climate- and Energy Drought-Resilient Energy System Decarbonisation

Are you interested in developing weather-resilient energy systems that are robust against climate impacts, energy droughts, and aligned with climate mitigation targets? Do you enjoy working on interdisciplinary research that bridges energy modelling with climate science, hydrology, risk analysis, and integrated assessment? Join us as a PhD candidate.

Your job

The rapid decarbonisation of the energy system requires the large-scale expansion of renewable energy sources for electricity generation, coupled with the electrification of end-use sectors such as space heating and cooling. It is projected that by 2050, approximately 80% of the global electricity supply will come from variable renewable energy (VRE) sources like wind, solar, and hydropower to meet the 1.5–2°C Paris Agreement target. However, the increasing reliance on VRE in decarbonised energy systems exposes both supply and demand to greater vulnerability from variable and uncertain weather conditions.

One emerging challenge threatening the reliability and security of energy supply is energy droughts—extended periods of energy shortfall or low production, analogous to hydrological droughts. These events are driven by prolonged periods of low weather-resource availability, such as calm wind conditions or insufficient water in hydro reservoirs or rivers. They may also be triggered by other weather extremes, such as storms forcing wind turbines offline or heatwaves and droughts reducing cooling water availability for thermal power generation. Of particular concern are compound energy droughts, where multiple stressors occur simultaneously. A well-known example is Dunkelflaute (or "dark doldrums"), which often coincides with high energy demand during cold winter spells. As climate change increases the frequency and intensity of extreme weather events, future energy transition pathways must be designed to anticipate and withstand these risks.

This PhD project focuses on designing climate- and energy drought-resilient decarbonised energy systems, integrating both climate mitigation and adaptation strategies. The project aims to improve the spatiotemporal representation of weather and hydrological extremes, interannual weather variability, and long-term climate change impacts in energy system modelling. While the interconnected European energy system will serve as a case study, the developed methodology is intended to be scalable and applicable to other global regions. The results will also inform the integration of energy drought-related risks into global integrated assessment models.

To achieve these goals, the project combines high-resolution, open-access climate projection ensembles with statistical and machine learning-based resampling techniques (e.g., k-nearest neighbours) to simulate weather-dependent energy supply and demand. Drawing on insights from hydrology and quantitative risk management, the project will also develop improved methods to identify energy droughts and detect "worst-case" weather years for energy security. These methods will be applied to map global energy drought risks, using scenario databases of renewable energy installations from global integrated assessment models.

The identified worst-case weather years will then be integrated into state-of-the-art, detailed energy system models (e.g., PLEXOS, PyPSA) to support more robust planning of future decarbonised systems and to stress test their operational reliability. This can be further embedded within a stochastic or robust optimisation framework to enhance planning decisions under uncertainty.

An integral part of this project is the exploration of synergies between virtual storage (arising from spatiotemporal complementarity), conventional grid integration options (e.g., storage, interconnectors, firm low-carbon generation), and emerging renewable technologies (e.g., floating offshore wind, floating PV, and green hydrogen) in mitigating and managing energy droughts.

Finally, the project will provide evidence-based recommendations on modelling practices and implementable policy options for energy drought identification, management, and the development of climate- and drought-resilient energy systems.

In practice, your tasks and responsibilities are the following:

• Analysing recent developments in the identification and characterisation of (energy) droughts across the energy field and related domains (climate science, hydrology, and risk management), including threshold-based and index-based approaches, the sequent-peak algorithm, extreme value analysis, and multivariate copulas. Based on this, you will develop an improved method to map global energy drought risk and storage requirements.
• Evaluating the global potential of conventional and emerging renewable energy technologies (e.g., floating offshore wind, floating PV), and improving their representation in energy system models and integrated assessment models.
• Identifying the most critical weather years for energy security under both current policy and Paris-aligned climate scenarios for key global regions, leveraging both high-resolution, open-access climate projection ensembles and statistical/machine learning-based resampling techniques.
• Integrating “worst-case” weather years into detailed energy system models to design climate- and energy drought-resilient energy portfolios and decarbonisation pathways for the interconnected European energy system toward 2050. You will explore the synergy between virtual storage (from technological and spatial complementarity) and hydrogen storage, alongside conventional grid integration strategies, to mitigate and manage energy droughts.
• Publishing your research findings in peer-reviewed academic journals and contributing to Open Science by developing open-access databases derived from your research. You are expected to actively participate in a series of doctoral workshops and present your work at international conferences.
• Contributing to education by teaching in one of our Bachelor’s or Master’s programmes (approximately 10% of your time).

Your qualities

• You have a strong interest in both the fundamental and applied aspects of energy system modelling, particularly in integrating spatiotemporally explicit weather, climate, and hydrology datasets with energy system models.
• You have a relevant Master’s degree in Energy Science, Energy System Modelling, (Energy) Meteorology, (Energy) Engineering, (Energy) Economics, Climate Risk/Impact Assessment, or a related field.
• You are excited to work in an interdisciplinary research environment.

Required Skills

• Experience with energy system modelling, a solid understanding of its basic principles, and a commitment to further developing your modelling expertise.
• Basic understanding of the physics and techno-economics of (renewable) energy technologies, storage systems, and transmission networks.
• Proficiency in statistical and programming tools (e.g., Python, R, or MATLAB), ideally with experience working with spatiotemporally explicit datasets in raster or NetCDF formats.
• Familiarity with optimisation techniques such as mixed-integer linear programming and scenario-based stochastic optimisation, or motivation to learn about them.
• Strong communication skills in academic and professional settings.
• Good problem-solving skills and the ability to work independently.
• Eagerness to acquire new knowledge and skills (e.g., machine learning, high-performance computing) that will support both the project and your personal development.

Other Requirements

• A good command of written and spoken English (C1 level).
• You do not already hold a PhD degree and are willing and able to relocate to the Netherlands for the duration of the project.

Our offer

• A position for one year, with an extension to a total of four years upon a successful assessment in the first year, and with the specific intent that it results in a doctorate within this period;
• a working week of 36 hours and a gross monthly salary between €2,901 and €3,707 in the case of full-time employment (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU));
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University has a number of schemes and facilities of its own for employees. This includes schemes facilitating professional development, leave schemes and schemes for sports and cultural activities, as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest in their growth. For more information, please visit Working at Utrecht University.

About us

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability. Sharing science, shaping tomorrow.

Utrecht University’s Faculty of Geosciences studies the Earth: from the Earth’s core to its surface, including man’s spatial and material utilisation of the Earth – always with a focus on sustainability and innovation. With 3,400 students (BSc and MSc) and 720 staff, the faculty is a strong and challenging organisation. The Faculty of Geosciences is organised in four Departments: Earth Sciences, Human Geography & Spatial Planning, Physical Geography, and Sustainable Development.

More information

For more information about this position, please contact Dr Jing Hu at [email protected] and Dr Vinzenz Koning at [email protected].

Candidates for this vacancy will be recruited by Utrecht University.

Apply now

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To apply, please send your curriculum vitae, including a letter of motivation, via the ‘apply now’ button.