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Koen van Greevenbroek

Publications and source records attributed to Koen van Greevenbroek.

9 recordsLinked to original sources

Reducing health and climate impacts of the global food system

The global food system contributes to tens of millions of years of human life lost every year through unhealthy diets, and accounts for roughly a third of greenhouse gas (GHG) emissions. Researchers have thus often sought opportunities to simultaneously redress these large impacts on human health and climate; "dietary shifts" are frequently identified as key to both improving health and reducing land-related GHG emissions. Here we develop a new, spatially-explicit, detailed model of the global food system, and use it to highlight enormous and low-cost opportunities to both improve dietary health and reduce food system emissions. However, we find that health and climate goals are surprisingly independent; for example, reducing red meat intake benefits climate, but may only modestly improve health outcomes. Similarly, there is very large potential both to achieve healthier diets that do not lead to emissions reductions and to reduce emissions without dietary change. Our results highlight both the potential for, and the separability of, food-related policies that advance public health and climate goals.

physics.soc-ph

Exploring near-optimal energy systems with stakeholders: a novel approach for participatory modelling

Involving people in energy systems planning can increase the legitimacy and socio-political feasibility of energy transitions. Participatory research in energy modelling offers the opportunity to engage with stakeholders in a comprehensive way, but is limited by how results can be generated and presented without imposing assumptions and discrete scenarios on the participants. To this end, we present a methodology and a framework, based on near-optimal modelling results, that can incorporate stakeholders in a holistic and engaging way. We confront stakeholders with a continuum of modelling-based energy system designs via an interactive interface allowing them to choose essentially any combination of components that meet the system requirements. Together with information on the implications of different technologies, it is possible to assess how participants prioritise different aspects in energy systems planning while also facilitating learning in an engaging and stimulating way. We showcase the methodology for the remote Arctic settlement of Longyearbyen and illustrate how participants deviate consistently from the cost optimum. At the same time, they manage to balance different priorities such as emissions, costs, and system vulnerability leading to a better understanding of the complexity and intertwined nature of decisions.

cs.CY

Little to lose: the case for a robust European green hydrogen strategy

The EU targets 10 Mt of green hydrogen production by 2030, but has not committed to targets for 2040. Green hydrogen competes with carbon capture and storage, biomass and imports in reaching emissions reductions; earlier studies have demonstrated the great uncertainty in future cost-optimal development of green hydrogen. In spite of this, we show that Europe risks little by setting green hydrogen production targets at around 25 Mt by 2040. Employing an extensive scenario analysis combined with novel near-optimal techniques, we find that this target results in systems that are within 10% of cost-optimal in most considered scenarios. Setting concrete targets is important in order to resolve significant uncertainty which hampers investments. Targeting green hydrogen reduces the dependence on carbon capture and storage and green fuel imports, making for a more robust European climate strategy.

eess.SY

Trading off regional and overall energy system design flexibility in the net-zero transition

The transition to net-zero emissions in Europe is determined by a patchwork of country-level and EU-wide policy, creating coordination challenges in an interconnected system. We use an optimisation model to map out near-optimal energy system designs for 2050, focussing on the planning flexibility of individual regions while maintaining overall system robustness against different weather years, cost assumptions, and land use limitations. Our results reveal extensive flexibility at a regional level, where only few technologies (solar around the Adriatic and wind on the British Isles and in Germany) cannot be substituted. National policymakers can influence renewable energy export and hydrogen strategies significantly, provided they coordinate this with the remaining European system. However, stronger commitment to solar in Southern Europe and Germany unlocks more design options for Europe overall. These results on regional trade-offs facilitate more meaningful policy discussions which are crucial in the transition to a sustainable energy system.

eess.SY

Balancing Act: The Cost of Wind Restrictions in Norway's Electricity Transition

To meet its commitments under the Paris Agreement and reduce its dependency on energy imports, the pace, and scale of renewable energy deployment across Europe must increase dramatically over the next decade. Such a steep change in the net-zero transition will inevitably necessitate trade-offs with other societal priorities. Here we investigate a case study focused on the opposition towards onshore wind and the compromises that may need to be made to deliver its plans for deep electrification. Using an electricity system model, we explore the implications of key social and environmental dimensions shaping the future deployment of onshore wind on the costs and design of electricity systems for Norway in 2030. We find that under restrictions that allow for almost no additional onshore wind, demand can not be met and load has to be shed. Yet, when reducing the restrictions on onshore wind or allowing for in-country transmission expansion, feasible system designs at a small fraction of that cost can be found. To meet the net-zero targets, compromises will need to be made on either wind power deployment, transmission expansion, non-electrification of industry or demand reduction.

physics.soc-ph

Using power system modelling outputs to identify weather-induced extreme events in highly renewable systems

In highly renewable power systems the increased weather dependence can result in new resilience challenges, such as renewable energy droughts, or a lack of sufficient renewable generation at times of high demand. The weather conditions responsible for these challenges have been well-studied in the literature. However, in reality multi-day resilience challenges are triggered by complex interactions between high demand, low renewable availability, electricity transmission constraints and storage dynamics. We show these challenges cannot be rigorously understood from an exclusively power systems, or meteorological, perspective. We propose a new method that uses electricity shadow prices - obtained by a European power system model based on 40 years of reanalysis data - to identify the most difficult periods driving system investments. Such difficult periods are driven by large-scale weather conditions such as low wind and cold temperature periods of various lengths associated with stationary high pressure over Europe. However, purely meteorological approaches fail to identify which events lead to the largest system stress over the multi-decadal study period due to the influence of subtle transmission bottlenecks and storage issues across multiple regions. These extreme events also do not relate strongly to traditional weather patterns (such as Euro-Atlantic weather regimes or the North Atlantic Oscillation index). We therefore compile a new set of weather patterns to define energy system stress events which include the impacts of electricity storage and large-scale interconnection. Without interdisciplinary studies combining state-of-the-art energy meteorology and modelling, further strive for adequate renewable power systems will be hampered.

physics.soc-ph

Intersecting near-optimal spaces: European power systems with more resilience to weather variability

We suggest a new methodology for designing robust energy systems. For this, we investigate so-called near-optimal solutions to energy system optimisation models; solutions whose objective values deviate only marginally from the optimum. Using a refined method for obtaining explicit geometric descriptions of these near-optimal feasible spaces, we find designs that are as robust as possible to perturbations. This contributes to the ongoing debate on how to define and work with robustness in energy systems modelling. We apply our methods in an investigation using multiple decades of weather data. For the first time, we run a capacity expansion model of the European power system (one node per country) with a 3-hourly temporal resolution with 41 years of weather data. While an optimisation with 41 weather years is at the limits of computational feasibility, we use the near-optimal feasible spaces of single years to gain an understanding of the design space over the full time period. Specifically, we intersect all near-optimal feasible spaces for the individual years in order to get designs that are likely to be feasible over the entire time period. We find significant potential for investment flexibility, and verify the feasibility of these designs by simulating the resulting dispatch problem with four decades of weather data. They are characterised by a shift towards more onshore wind and solar power, while emitting up to 50% less $CO_2$ than a cost-optimal solution over that period. Our work builds on recent developments in the field, including techniques such as Modelling to Generate Alternatives and Modelling All Alternatives, and provides new insights into the geometry of near-optimal feasible spaces and the importance of multi-decade weather variability for energy systems design. We also provide an effective way of working with a multi-decade time frame in a highly parallelised manner.

math.OC

Approximating Length-Restricted Means under Dynamic Time Warping

We study variants of the mean problem under the $p$-Dynamic Time Warping ($p$-DTW) distance, a popular and robust distance measure for sequential data. In our setting we are given a set of finite point sequences over an arbitrary metric space and we want to compute a mean point sequence of given length that minimizes the sum of $p$-DTW distances, each raised to the $q$\textsuperscript{th} power, between the input sequences and the mean sequence. In general, the problem is $\mathrm{NP}$-hard and known not to be fixed-parameter tractable in the number of sequences. On the positive side, we show that restricting the length of the mean sequence significantly reduces the hardness of the problem. We give an exact algorithm running in polynomial time for constant-length means. We explore various approximation algorithms that provide a trade-off between the approximation factor and the running time. Our approximation algorithms have a running time with only linear dependency on the number of input sequences. In addition, we use our mean algorithms to obtain clustering algorithms with theoretical guarantees.

cs.CG

A new structure for difference matrices over abelian $p$-groups

A difference matrix over a group is a discrete structure that is intimately related to many other combinatorial designs, including mutually orthogonal Latin squares, orthogonal arrays, and transversal designs. Interest in constructing difference matrices over $2$-groups has been renewed by the recent discovery that these matrices can be used to construct large linking systems of difference sets, which in turn provide examples of systems of linked symmetric designs and association schemes. We survey the main constructive and nonexistence results for difference matrices, beginning with a classical construction based on the properties of a finite field. We then introduce the concept of a contracted difference matrix, which generates a much larger difference matrix. We show that several of the main constructive results for difference matrices over abelian $p$-groups can be substantially simplified and extended using contracted difference matrices. In particular, we obtain new linking systems of difference sets of size $7$ in infinite families of abelian $2$-groups, whereas previously the largest known size was $3$.

math.CO