@misc{JalboutGengeMuesgens, author = {Jalbout, Eddy and Genge, Lucien and M{\"u}sgens, Felix}, title = {H2Europe: an analysis of long-term hydrogen import-potentials from the MENA region}, series = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, journal = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-0896-7}, issn = {2165-4093}, doi = {10.1109/EEM54602.2022.9921055}, pages = {1 -- 7}, abstract = {Our paper assesses the economic viability of green hydrogen exports from the middle east and north Africa to the EU in the long-term (for the year 2050). For this purpose, we simulate a techno-economic hydrogen supply chain based on generation from renewable energy sources. The chain of production, conversion, and transportation costs, in combination with potentials, yields a merit order of hydrogen supply. The paper focuses on one low-cost option for imports from the middle east and north Africa region. In addition, it provides a classification of additional options. We find that due to proximity, retrofitting and potentially even installing new pipelines from Morocco, Algeria and Tunisia could provide nearly half the expected European demand of 60 million tons p.a. by 2050. Based on our assumptions, the costs would be around 2 €/kgH 2 .}, language = {en} } @incollection{MuesgensRadke, author = {M{\"u}sgens, Felix and Radke, Silvian}, title = {Warmer Lichtsturm - Umgang mit Erzeugungsspitzen aus PV und Wind : Arbeitspaket 1}, series = {Warmer Lichtsturm - Umgang mit Erzeugungsspitzen aus PV und Wind}, volume = {2024}, booktitle = {Warmer Lichtsturm - Umgang mit Erzeugungsspitzen aus PV und Wind}, pages = {13 -- 30}, abstract = {{\"U}ber das Scientific Advisory \& Project Board Die vorliegende Kurzstudie wurde von einem Konsortium entwickelt, das sich aus Mitgliedern des 50Hertz Scientific Advisory and Project Boards (SAPB) zusammensetzt. Das SAPB ist ein Kreis von Professorinnen und Professoren, die 50Hertz darin unterst{\"u}tzen, neue Denk- und L{\"o}sungsans{\"a}tze zu entwickeln und Erkenntnisse aus der Forschung - wo angemessen - in die Praxis von 50Hertz zu {\"u}bernehmen. Disclaimer Im Kontext der durch 50Hertz beauftragten SAPB-Studien forschen die beteiligten Wissenschaftlerinnen und Wissenschaftler frei und ergebnisoffen. Alle durch das Konsortium entwickelten Handlungsempfehlungen werden von 50Hertz eingehend gepr{\"u}ft und diskutiert, letztendlich entsprechen aber nicht alle Positionen denen von 50Hertz.}, language = {de} } @misc{MuesgensGenge, author = {M{\"u}sgens, Felix and Genge, Lucien}, title = {European hydrogen infrastructure planning : insights from the TransHyDE project system analysis}, series = {Flagship Project TransHyDE}, volume = {2024}, journal = {Flagship Project TransHyDE}, pages = {67}, abstract = {The white paper was developed by a selected authorship of the TransHyDE Project System Analysis. The contents of the TransHyDE publications are produced in the project independently of the Federal Ministry of Education and Research.}, language = {en} } @book{MuesgensBade, author = {M{\"u}sgens, Felix and Bade, Alexander}, title = {Energy trading and risk management}, edition = {1. Auflage}, publisher = {Springer Link}, address = {Schweiz}, isbn = {978-3-031-57237-1}, doi = {10.1007/978-3-031-57238-8}, pages = {211}, abstract = {This book offers important insights into the intricacies of energy trading and risk management to students and professionals in the liberalized electricity and natural gas markets. In its opening chapter, the book delves into fundamental concepts, including price formation on wholesale markets. The various market places and trading products are presented, and the distinguishing characteristics of electricity and natural gas compared to other commodities are emphasised. Moving forward, the next chapter concentrates on portfolio management, offering insights into the trading process through the perspectives of various agents. It begins with proprietary traders and progresses to encompass the portfolio management activities of integrated companies responsible for both generation assets and a retail client base. The book then looks at risk management, explaining the diverse risks that impact the value of energy portfolios inthe market. It places emphasis on credit risk, price risk, quantity risk, and product liquidity risk as the most influential factors and presents effective practices for their management. Furthermore, readers will gain a comprehensive understanding of how to manage quantity risk and its interconnectedness with price risk. Additionally, the book addresses the measurement of product liquidity and its disparities across different energy market products. The book then looks at risk management, explaining the diverse risks that impact the value of energy portfolios inthe market. It places emphasis on credit risk, price risk, quantity risk, and product liquidity risk as the most influential factors and presents effective practices for their management. Furthermore, readers will gain a comprehensive understanding of how to manage quantity risk and its interconnectedness with price risk. Additionally, the book addresses the measurement of product liquidity and its disparities across different energy market products. In summary, this book is an accessible introduction and a concise reference for students and professionals across all fields of energy.}, language = {en} } @misc{BenAmorAkkalDeviMuesgens, author = {Ben Amor, Souhir and Akkal Devi, Prashanth and M{\"u}sgens, Felix}, title = {Meta-forecasting for solar power generation: algorithm-based swarm intelligence}, series = {20th International Conference on the European Energy Market (EEM)}, journal = {20th International Conference on the European Energy Market (EEM)}, publisher = {IEEE}, issn = {2165-4093}, doi = {10.1109/EEM60825.2024.10608959}, pages = {5}, abstract = {Our paper introduces a dynamic meta-forecasting approach that optimizes the weights of several available forecasts using a swarm intelligence algorithm, named Particle Swarm Optimization. This algorithm was chosen for its efficiency and convergence performance in solving optimization problems. We apply the methodology to solar photovoltaic day-ahead forecasts utilizing regional data from Germany. Our sample covers the period between 2019 and 2022 at a quarter-hourly frequency. We provide day-ahead forecasts using a rolling estimation window. Alongside benchmark models, Particle Swarm Optimization predictive accuracy is comparable to state-of-the-art models, particularly a dynamic elastic net benchmark model. However, there are slight differences. The investor can choose between Particle Swarm Optimization for its simple implementation and computational efficiency, or dynamic elastic net models for its parameters explainability.}, language = {en} } @misc{GrueblerMuesgens, author = {Gr{\"u}bler, Lene Marie and M{\"u}sgens, Felix}, title = {Applying spatial decomposition in energy system models}, series = {20th International Conference on the European Energy Market (EEM)}, volume = {2024}, journal = {20th International Conference on the European Energy Market (EEM)}, issn = {2165-4093}, doi = {10.1109/EEM60825.2024.10608869}, pages = {8}, abstract = {The European energy transition requires the expansion of renewable generators and consequently, the expansion of grid infrastructure and flexibility options. When modelling complex energy systems, the application of decomposition techniques is reasonable to keep models computationally tractable. Our paper focuses on the efficient optimization of energy systems covering large geographic areas. To accelerate the solving process, we apply a variant of Benders decomposition, which does not only apply temporal but also spatial decomposition. We show that by applying our decomposition approach, the solving time decreases up to 75\% compared to the runtime of the equivalent monolithic model solved by a commercial solver and the barrier algorithm. Furthermore, we show that additionally applying spatial decomposition results in time savings compared to an only temporally decomposed approach.}, language = {en} } @misc{BenAmorMoebiusMuesgens, author = {Ben Amor, Souhir and M{\"o}bius, Thonas and M{\"u}sgens, Felix}, title = {Bridging an energy system model with an ensemble deep-learning approach for electricity price forecasting}, series = {General Economics (econ.GN)}, volume = {2024}, journal = {General Economics (econ.GN)}, doi = {10.48550/arXiv.2411.04880}, pages = {1 -- 49}, abstract = {This paper combines a techno-economic energy system model with an econometric model to maximise electricity price forecasting accuracy. The proposed combination model is tested on the German day-ahead wholesale electricity market. Our paper also benchmarks the results against several econometric alternatives. Lastly, we demonstrate the economic value of improved price estimators maximising the revenue from an electric storage resource. The results demonstrate that our integrated model improves overall forecasting accuracy by 18 \%, compared to available literature benchmarks. Furthermore, our robustness checks reveal that a) the Ensemble Deep Neural Network model performs best in our dataset and b) adding output from the techno-economic energy systems model as econometric model input improves the performance of all econometric models. The empirical relevance of the forecast improvement is confirmed by the results of the exemplary storage optimisation, in which the integration of the techno-economic energy syst}, language = {en} } @misc{SgarciuMuesgensOsorioetal., author = {Sgarciu, Smaranda and M{\"u}sgens, Felix and Osorio, Sebastian and Pahle, Michael}, title = {Is Germany on track to achieve 2030 climate and energy targets?}, series = {List Forum f{\"u}r Wirtschafts- und Finanzpolitik}, volume = {49}, journal = {List Forum f{\"u}r Wirtschafts- und Finanzpolitik}, issn = {2364-3943}, doi = {10.1007/s41025-023-00255-0}, pages = {93 -- 107}, abstract = {The future development of CO2emissions in the German electricity sector by 2030 is unclear: On the one hand, the amendment to the Climate Protection Act (from August 2021) aims to tighten emission reduction targets in order to promote the path to a decarbonised energy system. On the other hand, the complex interplay between the main instruments for reducing carbon emissions, fuel prices and the current energy shortage as a result of Russia's attack on Ukraine is creating pressure for an increase in emissions. In our study, we examine whether Germany is on track to achieve its climate protection targets for 2030 and which measures can increase the likelihood. To do this, we use an energy system model parameterized to reflect the situation in the energy market in 2021, i.e. before Russia's attack on Ukraine. In addition to the quantitative side, we provide a qualitative analysis of the energy market in the light of recent events. We stress the importance of introducing a carbon price floor that can be dynamically changed in response to the development of other market forces and policies. This instrument would institutionalize a more plausible path to decarbonization and provide reassurance to investors.}, language = {en} } @misc{HoffmannByrukuriGangadharMuesgens, author = {Hoffmann, Christin and Byrukuri Gangadhar, Shanmukha Srinivas and M{\"u}sgens, Felix}, title = {Smells Like Green Energy - Quasi-Experimental Evidence on the Impact of Bioenergy Production on Residential Property Values}, series = {SSRN eLibrary}, journal = {SSRN eLibrary}, issn = {1556-5068}, doi = {10.2139/ssrn.4760312}, pages = {1 -- 26}, abstract = {Residents' acceptance of bioenergy is a prerequisite for its fast and efficient development but is ambiguously discussed in practice and research. We interpret a causal impact of bioenergy plant commissioning on housing prices in their vicinity as the average net external effects for residents. We utilize bioenergy plant construction data in Germany between 2007 and 2022 as a quasi-experiment with naturally occurring control groups in their vicinity and apply recently improved difference-in-difference estimation procedures to analyze instantaneous and heterogeneous treatment effects. We find a significant and negative impact on housing prices if plants use gaseous biofuel, generate electricity on-site, and are medium-sized. The magnitude of the effect is comparable to those for solar fields. In contrast, we find no impact for small and large bioenergy plants and those that use solid or liquid biofuels.}, language = {en} } @misc{SgarciuScholzMuesgens, author = {Sgarciu, Smaranda and Scholz, Daniel and M{\"u}sgens, Felix}, title = {How CO2 prices accelerate decarbonisation - The case of coal-fired generation in Germany}, series = {Energy Policy}, volume = {173}, journal = {Energy Policy}, issn = {0301-4215}, doi = {10.1016/j.enpol.2022.113375}, abstract = {This paper analyses the potential impact of the world's two main coal phase-out instruments: 1) direct regulatory intervention restricting the operation of existing coal-fired generation capacity and prohibiting investment in new capacity and 2) market-based CO2-pricing instruments that make emission-intensive coal-fired generation less competitive. We quantify these instruments' potential effects in the empirical setting of Germany, where both instruments are employed concurrently. However, this paper's approach and methodology can be applied in any jurisdiction or energy system worldwide. Our paper provides quantitative results with a pan-European partial-equilibrium electricity system model. The model applies an innovative three-step approach. Step 1 solves an investment and dispatch problem with reduced technical and temporal complexity for European countries. Step 2 computes the dispatch problem at a bihourly resolution and step 3 solves the investment and dispatch problem for Germany with increased technical complexity. Our results confirm that both a regulated phase-out as well as a price on CO2 emissions can reduce the amount of coal-fired generation in an electricity system. If CO2 prices remain at current levels, coal-fired power plants leave the market significantly before the regulated phase-out date, reducing demand for employees in the Lusatian lignite industry. Regions and federal governments should take this finding into account when planning and preparing for structural change.}, language = {en} } @misc{GengeSchellerMuesgens, author = {Genge, Lucien and Scheller, Fabian and M{\"u}sgens, Felix}, title = {Supply costs of green chemical energy carriers at the European border: A meta-analysis}, series = {International Journal of Hydrogen Energy}, volume = {48}, journal = {International Journal of Hydrogen Energy}, number = {98}, issn = {0360-3199}, doi = {10.1016/j.ijhydene.2023.06.180}, pages = {38766 -- 38781}, abstract = {Importing green chemical energy carriers is crucial for meeting European climate targets. However, estimating the costs of supplying these energy carriers to Europe remains challenging, leading to a wide range of reported supply-cost estimates. This study analyzes the estimated supply costs of green chemical energy carriers at the European border using a dataset of 1050 data points from 30 studies. The results reveal significant variations in supply costs, with a projected four-fold difference in 2030 and a five-fold difference in 2050 across all energy carriers. The main drivers of cost differences are varying production costs, particularly influenced by the weighted average costs of capital and capital expenditures of renewable energy sources, electrolyzers, and carrier-specific conversion processes. Transport costs also contribute to variations, mainly influenced by the choice of energy carrier and the weighted average costs of capital. To optimize cost-efficiency and sustainability in the chemical energy carrier sector, this paper recommends prioritizing transparency and sensitivity analyses of key input parameters, classifying energy carriers based on technological and economic status, and encouraging research and development to reduce production costs.}, language = {en} } @misc{WatermeyerMoebiusGrotheetal., author = {Watermeyer, Mira and M{\"o}bius, Thomas and Grothe, Oliver and M{\"u}sgens, Felix}, title = {A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling}, series = {arXiv}, journal = {arXiv}, doi = {10.48550/arXiv.2304.09336}, pages = {1 -- 38}, abstract = {The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such predictions challenging. We propose a hybrid model that combines a techno-economic energy system model with stochastic models to address this challenge. The techno-economic model in our hybrid approach provides a deep understanding of the market. It captures the underlying factors and their impacts on electricity prices, which is impossible with statistical models alone. The statistical models incorporate non-techno-economic aspects, such as the expectations and speculative behaviour of market participants, through the interpretation of prices. The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape. Probabilistic forecasts are particularly valuable because they account for market uncertainty, facilitating informed decision-making and risk management. Our model delivers state-of-the-art results, helping market participants to make informed decisions and operate their systems more efficiently.}, language = {en} } @misc{MoebiusWatermeyerGrotheetal., author = {M{\"o}bius, Thomas and Watermeyer, Mira and Grothe, Oliver and M{\"u}sgens, Felix}, title = {Enhancing energy system models using better load forecasts}, series = {Energy Systems}, journal = {Energy Systems}, issn = {1868-3975}, doi = {10.1007/s12667-023-00590-3}, pages = {1 -- 30}, abstract = {Since energy system models require a large amount of technical and economic data, their quality significantly affects the reliability of the results. However, some publicly available data sets, such as the transmission system operators' day-ahead load forecasts, are known to be biased and inaccurate, leading to lower energy system model performance. We propose a time series model that enhances the accuracy of transmission system operators' load forecast data in real-time, using only the load forecast error's history as input. We further present an energy system model developed specifically for price forecasts of the short-term day-ahead market. We demonstrate the effectiveness of the improved load data as input by applying it to this model, which shows a strong reduction in pricing errors, particularly during periods of high prices and tight markets. Our results highlight the potential of our method the enhance the accuracy of energy system models using improved input data.}, language = {en} } @misc{BatzLineiroMuesgens, author = {Batz Li{\~n}eiro, Taimyra and M{\"u}sgens, Felix}, title = {Evaluating the German onshore wind auction programme: An analysis based on individual bids}, series = {Energy Policy}, volume = {172}, journal = {Energy Policy}, issn = {1873-6777}, doi = {10.1016/j.enpol.2022.113317}, abstract = {Auctions are a highly demanded policy instrument for the promotion of renewable energy sources. Their flexible structure makes them adaptable to country-specific conditions and needs. However, their success depends greatly on how those needs are operationalised in the design elements. Disaggregating data from the German onshore wind auction programme into individual projects, we evaluated the contribution of auctions to the achievement of their primary (deployment at competitive prices) and secondary (diversity) objectives and have highlighted design elements that affect the policy's success or failure. We have shown that, in the German case, the auction scheme is unable to promote wind deployment at competitive prices, and that the design elements used to promote the secondary objectives not only fall short at achieving their intended goals, but create incentives for large actors to game the system.}, language = {en} } @misc{MoebiusRiepinMuesgensetal., author = {M{\"o}bius, Thomas and Riepin, Iegor and M{\"u}sgens, Felix and van der Weijde, Adriaan H.}, title = {Risk aversion and flexibility options in electricity markets}, series = {Energy Economics}, volume = {126}, journal = {Energy Economics}, issn = {0140-9883}, abstract = {Investments in electricity transmission and generation capacity must be made despite significant uncertainty about the future developments. The sources of this uncertainty include, among others, the future levels and spatiotemporal distribution of electricity demand, fuel costs and future energy policy. In recent years, these uncertainties have increased due to the ongoing evolution of supply- and demand-side technologies and rapid policy changes designed to encourage a transition to low-carbon energy systems. Because transmission and generation investments have long lead times and are difficult to reverse, they are subject to a considerable - and arguably growing - amount of risk.}, language = {en} } @misc{HoffmannZiemannPenskeetal., author = {Hoffmann, Christin and Ziemann, Niklas and Penske, Franziska and M{\"u}sgens, Felix}, title = {The value of secure electricity supply for increasing acceptance of green hydrogen - First experimental evidence from the virtual reality lab}, series = {19th International Conference on the European Energy Market (EEM), 06-08 June 2023, Lappeenranta, Finland}, journal = {19th International Conference on the European Energy Market (EEM), 06-08 June 2023, Lappeenranta, Finland}, isbn = {979-8-3503-1258-4}, issn = {2165-4093}, doi = {10.1109/EEM58374.2023.10161844}, pages = {9}, abstract = {To unlock the high potential of green hydrogen in reaching the ambitious 1.5 °C goal declared by the Paris Agreement, enormous (public) investments are needed. Social acceptance of these investments is required in order to implement hydrogen technologies as fast and efficiently as possible. This study investigates which benefits associated with green hydrogen foster its social acceptance. Using a between-subject design, we implement two different treatments. Both treatments have in common that the participants experience the transformation into a hydrogen economy in a virtual reality scenario. In "Info Security of Supply", we provide the participants information about the benefits of green hydrogen regarding the security of energy supply and climate protection. In Control, we inform them only about the benefits of climate protection. Subsequently, the participants decide about the financial support of a hydrogen project. Our preliminary results show a higher support if the focus is solely on the positive impact of green hydrogen for climate protection.}, language = {en} } @misc{RiepinSgarciuBerneckeretal., author = {Riepin, Iegor and Sgarciu, Smaranda and Bernecker, Maximilian and M{\"o}bius, Thomas and M{\"u}sgens, Felix}, title = {Grok It and Use It: Teaching Energy Systems Modeling}, series = {SSRN eLibrary}, journal = {SSRN eLibrary}, issn = {1556-5068}, doi = {10.2139/ssrn.4320978}, abstract = {This article details our experience developing and teaching an "Energy Systems Modeling" course, which sought to introduce graduate-level students to operations research, energy economics, and system modeling using the General Algebraic Modeling System (GAMS). In this paper, we focus on (i) the mathematical problems discussed in the course, (ii) the energy-related empirical interpretations of these mathematical problems, and (iii) the best teaching practices (i.e., our experiences regarding how to make the content interesting and accessible for students).}, language = {en} } @misc{HoffmannByrukuriGangadharMuesgens, author = {Hoffmann, Christin and Byrukuri Gangadhar, Shanmukha Srinivas and M{\"u}sgens, Felix}, title = {Smells like green energy the impact of bioenergy production on residential property values in Germany}, series = {Science Direkt}, volume = {145}, journal = {Science Direkt}, publisher = {Elsevier B.V.}, address = {Amsterdam}, doi = {10.1016/j.eneco.2025.108404}, pages = {1 -- 16}, abstract = {One requirement for the fast and efficient development of bioenergy is a clear understanding of the negative externalities bioenergy facilities cause. At this point, discussions in practice and research as to which externalities have an impact and how strong this potential impact actually is remain inconclusive. We utilize bioenergy plant construction data from Germany between 2007 and 2022 and match it with information about real estate in the plants' vicinity. Applying improved difference-in-difference estimation procedures to analyze heterogeneous treatment effects, we interpret a causal impact of bioenergy plant commissioning on housing prices in the vicinity in terms of the average net external effects affecting the vicinity. Overall, we find a minor negative impact of -0,5 \% on home prices within 1 km of bioenergy plants but no statistically significant effect beyond this distance. This suggests that visual pollution has a limited role as an externality of bioenergy plants. However, if we restrict the sample to homes downwind of bioenergy plants, we find a significant yet small negative impact on home prices, ranging from -1,0 \% to - 1,3 \%. Additionally, homes near bioenergy plants that use gaseous inputs - which emit stronger odors - experience price reductions between -0,4 \% to -0,7 \%. This lets us conclude that, besides visual pollution, odor emission may play a more significant role in affecting nearby home prices.}, language = {en} } @misc{HoffmannJalboutVillanuevaetal., author = {Hoffmann, Christin and Jalbout, Eddy and Villanueva, Monica and Batz Li{\~n}eiro, Taimyra and M{\"u}sgens, Felix}, title = {Positive and Negative Externalities from Renewable and Conventional Power Plants in the Backyard: The Value of Participation}, series = {SSRN eLibrary}, journal = {SSRN eLibrary}, issn = {1556-5068}, doi = {10.2139/ssrn.4203184}, pages = {1 -- 33}, abstract = {We quantify the net external effects of conventional and renewable electricity generators by analyzing housing prices in their vicinity. Using a Differences-in-Differences approach, we find that (1) wind turbines reduce prices significantly, (2) solar fields have no significant impact, and (3) conventional plants over 1 km away show positive net effects. We set out to explain this result by disentangling the positive local external effects of energy generation, which we measure in terms of local purchasing power and tax revenues. Our results show that the commissioning of conventional power stations results in a significant increase in both purchasing power and business tax income in the vicinity. We thus conclude that significant financial participation of the local public in the development of renewable energy projects, especially wind turbines, could be key to increasing their acceptance and accelerating their expansion.}, language = {en} } @misc{BerneckerGebhardtBenAmoretal., author = {Bernecker, Maximilian and Gebhardt, Marc and Ben Amor, Souhir and Wolter, Martin and M{\"u}sgens, Felix}, title = {Quantifying the impact of load forecasting accuracy on congestion management in distribution grids}, series = {International journal of electrical power \& energy systems}, volume = {168}, journal = {International journal of electrical power \& energy systems}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {0142-0615}, doi = {10.1016/j.ijepes.2025.110713}, pages = {1 -- 27}, abstract = {Digitalization is a global trend in energy systems and beyond. However, it is often unclear what digitalization means exactly in the context of energy systems and how the benefits of digitalization can be quantified. Providing additional information, e.g., through sensors and metering equipment, is one concrete angle where digitalization contributes. This paper provides a framework to quantify the value of such additional information in distribution grids. We analyze to what extent smart meters improve the accuracy of day-ahead load forecasts and quantify the savings in congestion management costs resulting from the improved accuracy. To quantify the cost reduction, we conduct a case study employing a simplified IEEE test system. Historical electricity load data from over 6,000 smart meters was used to improve day-ahead load forecasts. We assessed and compared the forecasting performance to estimates based on standard load profiles with multiple load forecast simulations in the network based on uncertainty parameterizations from forecasts with and without smart meter data. Calculating redispatch cost in the distribution grid, we find that the forecast based on smart meter data reduces key redispatch parameters such as the share of expected voltage violations, the amount of rescheduled generation by more than 90\%. These improvements translate into a reduction in congestion management costs by around 97\%. Furthermore, we shed light on whether the gains increase linearly with the number of smart meters and available data in the grid. When smart meter shares are increased uniformly throughout the grid, savings are concave, i.e., the first 10\% of smart meters reduces congestion management costs by around 20\% while the last 10\% reduces these costs only marginally. Focusing smart meter installation on the most congested nodes reduces congestion management costs by around 60\% with just 10\% smart meter coverage, significantly outperforming a uniform rollout. However, savings in congestion management alone are not likely to recover the installation and operation costs of the installed smart meter.}, language = {en} }