Aleksander Grochowicz

• Grochowicz, Aleksander; van Greevenbroek, Koen & Bloomfield, Hannah C. (2024). Using power system modelling outputs to identify weather-induced extreme events in highly renewable systems. Environmental Research Letters. ISSN 1748-9326. 19(5), p. 1–15. doi: 10.1088/1748-9326/ad374a. Full text in Research Archive
• Grochowicz, Aleksander; Benth, Fred Espen & Zeyringer, Marianne (2024). Spatio-temporal smoothing and dynamics of different electricity flexibility options for highly renewable energy systems—Case study for Norway. Applied Energy. ISSN 0306-2619. 356. doi: 10.1016/j.apenergy.2023.122338. Show summary

  In this article, we investigate the mismatch of renewable electricity production to demand and how flexibility options enabling spatial and temporal smoothing can reduce risks of variability. As a case study we pick a simplified (partial) 2-region representation of the Norwegian electricity system and focus on wind power. We represent regional electricity production and demand through two stochastic processes: the wind capacity factors are modelled as a two-dimensional Ornstein–Uhlenbeck process and electricity demand consists of realistic base load and temperature-induced load coming from a deseasonalised autoregressive process. We validate these processes, that we have trained on historical data, through Monte Carlo simulations allowing us to generate many statistically representative weather years. For the investigated realisations (weather years) we study deviations of production from demand under different wind capacities, and introduce different scenarios where flexibility options like storage and transmission are available. Our analysis shows that simulated loss values are reduced significantly by cooperation between regions and either mode of flexibility. Combining storage and transmission leads to even more synergies and helps to stabilise production levels and thus reduces likelihoods of inadequacy of renewable power systems.

• Grochowicz, Aleksander; van Greevenbroek, Koen; Benth, Fred Espen & Zeyringer, Marianne (2023). Intersecting near-optimal spaces: European power systems with more resilience to weather variability. Energy Economics. ISSN 0140-9883. 118. doi: 10.1016/j.eneco.2022.106496. Full text in Research Archive Show summary

  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 three-hourly temporal resolution and 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 more than 50% less CO2 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 (MGA) and Modelling All Alternatives (MAA), 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. Our implementation is open-sourced, adaptable and is based on PyPSA-Eur.

• Craig, Michael T.; Wohland, Jan; Stoop, Laurens P.; Kies, Alexander; Pickering, Bryn & Bloomfield, Hannah C. [Show all 23 contributors for this article] (2022). Overcoming the disconnect between energy system and climate modeling. Joule. ISSN 2542-4351. 6(7), p. 1405–1417. doi: 10.1016/j.joule.2022.05.010. Full text in Research Archive Show summary

  Energy system models underpin decisions by energy system planners and operators. Energy system modeling faces a transformation: accounting for changing meteorological conditions imposed by climate change. To enable that transformation, a community of practice in energy-climate modeling has started to form that aims to better integrate energy system models with weather and climate models. Here, we evaluate the disconnects between the energy system and climate modeling communities, then lay out a research agenda to bridge those disconnects. In the near-term, we propose interdisciplinary activities for expediting uptake of future climate data in energy system modeling. In the long-term, we propose a transdisciplinary approach to enable development of (1) energy-system-tailored climate datasets for historical and future meteorological conditions and (2) energy system models that can effectively leverage those datasets. This agenda increases the odds of meeting ambitious climate mitigation goals by systematically capturing and mitigating climate risk in energy sector decision-making.

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• Grochowicz, Aleksander (2023). Spatio-temporal smoothing and dynamics of different electricity flexibility options.
• Grochowicz, Aleksander (2023). Identifying weather stress events from power system optimisation outputs.
• Grochowicz, Aleksander; Greevenbroek, Koen van & Bloomfield, Hannah C. (2023). Identifying weather stress events from power system optimisation outputs.
• Grochowicz, Aleksander (2023). The role of historical weather data and how that can be used for a more resilient energy transition.
• Grochowicz, Aleksander; van Greevenbroek, Koen; Benth, Fred Espen & Zeyringer, Marianne (2023). Intersecting Near-Optimal Spaces for Policy Information.
• van Greevenbroek, Koen; Grochowicz, Aleksander & Bloomfield, Hannah C. (2023). Identifying Weather Stress Events from Power System Optimisation Outputs.
• Greevenbroek, Koen van; Grochowicz, Aleksander; Zeyringer, Marianne; Noll, Josef & Vågerö, Oskar (2023). Vi treng uavhengig forsking, ikkje drøymetenking om kjernekraft. Aftenposten (morgenutg. : trykt utg.). ISSN 0804-3116.
• Grochowicz, Aleksander & Zeyringer, Marianne (2023). Managing the variability in time and space of renewable power generation.
• Grochowicz, Aleksander & Zeyringer, Marianne (2023). Managing the variability in time and geography of renewable power generation.
• van Greevenbroek, Koen; Zeyringer, Marianne; Noll, Josef; Grochowicz, Aleksander & Vågerö, Oskar (2023). Kjernekraft er ikkje naudsynt for Noreg. Det vil heller ikkje lønna seg. Aftenposten (morgenutg. : trykt utg.). ISSN 0804-3116.
• Melteig, Elina & Grochowicz, Aleksander (2023). Strømmarkedet: Hva skjer hvis vi kobler Nord- og Sør-Norge? . [Internet]. forskning.no, tu.no, titan.uio.no.
• Grochowicz, Aleksander; van Greevenbroek, Koen; Benth, Fred Espen & Zeyringer, Marianne (2022). Intersecting near-optimal spaces for robust energy systems.
• Zeyringer, Marianne; Benth, Fred Espen; Roithner, Maximilian; Grochowicz, Aleksander & Sirotko-Sibirskaya, Natalia (2022). Climate-resilient net-zero energy system design.
• van Greevenbroek, Koen & Grochowicz, Aleksander (2022). Effect of different weather years on policymakers’ decision space.
• Grochowicz, Aleksander (2022). Intersecting near-optimal spaces for more resilience against weather variability.
• Grochowicz, Aleksander; Heineken, Daniel & Wennberg, Sondre (2021). The reliability of wind power in the Longyearbyen area. Universitetssenteret på Svalbard. Full text in Research Archive Show summary

  This report in a white paper format was written as part of the course AGF-353/853 "Sustainable Arctic Energy Exploration and Development" at the University Centre in Svalbard (UNIS). --- Within this decade the current energy system in Longyearbyen has to be revolutionised. Right now, it relies entirely on fossil fuels, but in the future it is envisioned to be a front-runner of renewable systems in the Arctic. Due to the polar night and restricted renewable resources, the reliability of wind power is of crucial importance in this transition. Additionally, the permafrost and remote location demand high robustness and simple maintenance. In this report, we analyse on-shore wind potential in three different locations over the previous decade, including an evaluation of stability and extreme events in Svalbard's harsh climate. To ensure long-term success of this transition, we look at interannual, seasonal, and sub-monthly variations that should be included in suitability assessments. Based on our analysis, disregarding this could lead to installations that can jeopardise the stability of the system. With generated input data that we feed into an energy systems model, we find that if one considers interannual variability and a set of different locations, one can ensure a viable and reliable renewable energy system for Longyearbyen, with on-shore wind as a key component.

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