arXiv subjects

Machteld van den Broek

Publications and source records attributed to Machteld van den Broek.

4 recordsLinked to original sources

arXiv2024

The Climatological Renewable Energy Deviation Index (CREDI)

We propose an index to quantify and analyse the impact of climatological variability on the energy system at different timescales. We define the Climatological Renewable Energy Deviation Index (CREDI) as the cumulative anomaly of a renewable resource with respect to its climate over a specific time period of interest. For this we introduce the smooth, yet physical, hourly rolling window climatology that captures the expected hourly to yearly behaviour of renewable resources. We analyse the presented index at decadal, annual and (sub-)seasonal timescales for a sample region and discuss scientific and practical implications. CREDI is meant as an analytical tool for researchers and stakeholders to help them quantify, understand, and explain, the impact of energy-meteorological variability on future energy system. Improved understanding translates to better assessments of how renewable resources, and the associated risks for energy security, may fare in current and future climatological settings. The practical use of the index is in resource planning. For example transmission system operators may be able to adjust short-term planning to reduce adequacy issues before they occur or combine the index with storyline event selection for improved assessments of climate change related risks.

physics.ao-ph↗

arXiv2024

Detection of Critical Events in Renewable Energy Production Time Series

The introduction of more renewable energy sources into the energy system increases the variability and weather dependence of electricity generation. Power system simulations are used to assess the adequacy and reliability of the electricity grid over decades, but often become computational intractable for such long simulation periods with high technical detail. To alleviate this computational burden, we investigate the use of outlier detection algorithms to find periods of extreme renewable energy generation which enables detailed modelling of the performance of power systems under these circumstances. Specifically, we apply the Maximum Divergent Intervals (MDI) algorithm to power generation time series that have been derived from ERA5 historical climate reanalysis covering the period from 1950 through 2019. By applying the MDI algorithm on these time series, we identified intervals of extreme low and high energy production. To determine the outlierness of an interval different divergence measures can be used. Where the cross-entropy measure results in shorter and strongly peaking outliers, the unbiased Kullback-Leibler divergence tends to detect longer and more persistent intervals. These intervals are regarded as potential risks for the electricity grid by domain experts, showcasing the capability of the MDI algorithm to detect critical events in these time series. For the historical period analysed, we found no trend in outlier intensity, or shift and lengthening of the outliers that could be attributed to climate change. By applying MDI on climate model output, power system modellers can investigate the adequacy and possible changes of risk for the current and future electricity grid under a wider range of scenarios.

physics.soc-ph↗

arXiv2023

New efficient ADMM algorithm for the Unit Commitment Problem

The unit commitment problem (UC) is an optimization problem concerning the operation of electrical generators. Many algorithms have been proposed for the UC and in recent years a more decentralized approach, by solving the UC with alternating direction method of multipliers (ADMM), has been investigated. For convex problems ADMM is guaranteed to find an optimal solution. However, because UC is non-convex additional steps need to be taken in order to ensure convergence to a feasible solution of high quality. Therefore, solving UC by a MIL(Q)P formulation and running an off-the-shelf solver like Gurobi until now seems to be the most efficient approach to obtain high quality solutions. In this paper, we introduce a new and efficient way to solve the UC with ADMM to near optimality. We relax the supply-demand balance constraint and deal with the non-convexity by iteratively increasing a penalty coefficient until we eventually force convergence and feasibility. At each iteration the subproblems are solved by our efficient algorithm for the single UC subproblem developed in earlier work and our new ADMM algorithm for the transmission subproblems. Computational experiments on benchmark instances demonstrated that our algorithm produces high-quality solutions. The computation time seems to grow practically linear with the length of the time horizon. For the case with quadratic generation cost our algorithm is significantly faster than solving the problem by a state-of-the-art MIL(Q)P formulation. For the case of linear generation cost, it outperforms the MILP approach for longer time horizons.

math.OC↗

arXiv2023

Linking Unserved Energy to Weather Regimes

The integration of renewable energy sources into power systems is expected to increase significantly in the coming decades. This can result in critical situations related to the strong variability in space and time of weather patterns. During these critical situations the power system experiences a structural shortage of energy across multiple time steps and regions, leading to Energy Not Served (ENS) events. Our research explores the relationship between six weather regimes that describe the large scale atmospheric flow and ENS events in Europe by simulating future power systems. Our results indicate that most regions have a specific weather regime that leads to the highest number of ENS events. However, ENS events can still occur during any weather regime, but with a lower probability. In particular, our findings show that ENS events in western and central European countries often coincide with either the positive Scandinavian Blocking (SB+), characterised by cold air penetrating Europe under calm weather conditions from north-eastern regions, or North Atlantic Oscillation (NAO+) weather regime, characterised by westerly flow and cold air in the southern half of Europe. Additionally, we found that the relative impact of one of these regimes reaches a peak 10 days before ENS events in these countries. In Scandinavian and Baltic countries, on the other hand, our results indicate that the relative prevalence of the negative Atlantic Ridge (AR-) weather regime is higher during and leading up to the ENS event.

physics.soc-ph↗