@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} } @misc{BatzLineiroMuesgens, author = {Batz Li{\~n}eiro, Taimyra and M{\"u}sgens, Felix}, title = {Pay-back time : increasing electricity prices and decreasing costs make renewable energy competitive}, series = {Energy policy}, volume = {199}, journal = {Energy policy}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1873-6777}, doi = {10.1016/j.enpol.2025.114523}, pages = {1 -- 14}, abstract = {The global energy transition needs a large-scale rollout of electricity generation from renewable energy sources (RES). Leading nations such as Spain, Japan, and Germany have invested early and substantially in RES. This leadership has been associated with high expenditures, but the trend is reversing as RES become more competitive. First, levelized costs of electricity for RES have decreased significantly and second, wholesale prices for electricity have increased, due to more ambitious climate protection and rising fuel prices. Despite favorable developments indicating a decline in the financial support needed for renewable deployment—and the fact that many countries still need to significantly increase their renewable capacities to meet climate objectives—renewable support has once again come under criticism. This paper demonstrates that cost-related criticism and concern is often unwarranted. By quantifying the aggregated subsidies of all RES units in Germany, which arguably are among the highest in the world, our findings reveal that: i) the net support costs of RES have been high in the past, ii) most net subsidies have already been paid and iii) newer installations of wind offshore, wind onshore and ground mounted PV are economically profitable. In addition, we show that wind onshore has been the most cost-efficient technology over time and explore the remarkable evolution of solar technologies, transitioning from one of the costliest to one of the most cost-effective options.}, language = {en} } @misc{AntweilerMuesgens, author = {Antweiler, Werner and M{\"u}sgens, Felix}, title = {The new merit order : the viability of energy-only electricity markets with only intermittent renewable energy sources and grid-scale storage}, series = {Energy economics}, volume = {145}, journal = {Energy economics}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1873-6181}, doi = {10.1016/j.eneco.2025.108439}, pages = {1 -- 28}, abstract = {What happens to the merit order of electricity markets when all electricity is supplied by intermittent renewable energy sources coupled with large-scale electricity storage? With near-zero marginal cost of production, will there still be a role for an energy-only electricity market? We answer these questions both analytically and empirically for electricity markets in Texas and Germany. What emerges in market equilibrium is the 'new merit order'. Curtailment at zero prices is a necessary feature of the new merit order, complementing peak prices to cover fixed costs of storage. Storage cannot 'solve' curtailment, because curtailment provides essential zero-price periods. Our work demonstrates that as long as free entry and competition ensure effective price setting, an efficient new merit order emerges in electricity markets even when the grid is completely powered by intermittent sources with near-zero marginal costs. We find that energy-only markets remain viable and functional.}, language = {en} } @misc{AntweilerMuesgens, author = {Antweiler, Werner and M{\"u}sgens, Felix}, title = {The new merit order : the viability of energy-only electricity markets with only intermittent renewable energy sources and grid-scale storage}, series = {USAEE working paper}, volume = {24-614}, journal = {USAEE working paper}, doi = {10.2139/ssrn.4702939}, pages = {1 -- 49}, abstract = {What happens to the merit order of electricity markets when all electricity is supplied by intermittent renewable energy sources coupled with large-scale electricity storage? With near-zero marginal cost of production, will there still be a role for an energy-only electricity market? We answer these questions both analytically and empirically for electricity markets in Texas and Germany. What emerges in market equilibrium is the 'new merit order'. Our work demonstrates that as long as free entry and competition ensure effective price setting, an efficient new merit order emerges in electricity markets even when the grid is completely powered by intermittent sources with near-zero marginal costs. We find that energy only markets remain viable and functional.}, language = {en} } @misc{BenAmorSgarciuBatzLineiroetal., author = {Ben Amor, Souhir and Sgarciu, Smaranda and Batz Lineiro, Taimyra BatzLineiro and M{\"u}sgens, Felix}, title = {Advanced models for hourly marginal CO2 emission factor estimation : a synergy between fundamental and statistical approaches}, series = {Applied energy}, volume = {397}, journal = {Applied energy}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1872-9118}, doi = {10.1016/j.apenergy.2025.126265}, pages = {1 -- 25}, abstract = {Global warming is caused by increasing concentrations of greenhouse gases, particularly carbon dioxide (CO2). The reduction of carbon dioxide emissions is thus an energy policy priority. A metric to quantify the change in CO2 emissions is the marginal emission factor. Marginal emission factors are needed for various purposes, for example to analyze the emission impact of electric vehicle charging. This paper presents two methodologies to estimate the marginal emission factor in electricity systems with high temporal resolution. The first is an energy systems model that incrementally calculates the marginal emission factors. This calculation is computationally intensive when the time resolution is high, but is very accurate because it considers relevant market factors on both the supply and demand sides and emulates the electricity market dynamics. The second is a Markov Switching Dynamic Regression model, a statistical model designed to estimate marginal emission factors faster, and it is benchmarked against the dynamic linear regression model widely used in the marginal emission factor estimation literature. For the German electricity market, we estimate the marginal emission factor time series both historically (2019, 2020) using Agora Energiewende and for the future (2025, 2030, and 2040) using estimated energy system data. The results indicate that the Markov Switching Dynamic Regression model outperforms benchmark models. Hence, the Markov Switching Dynamic Regression model is a simpler alternative to the computationally intensive incremental marginal emission factor, especially when short-term marginal emission factor estimation is needed. The results of the marginal emission factor estimation are applied to an exemplary low-emission vehicle charging scenario to estimate CO2 savings by shifting the charge hours to those corresponding to the lower marginal emission factor. We implemented the emission-minimized charging approach using both marginal emission factors. Over a 5-year period, the Markov Switching Dynamic Regression model appears to save 47.9 \% of emissions on average, compared to 6.5 \% real-world saving. The maximal value possible with incremental MEFs would be 37.6 \%.}, language = {en} } @misc{MuhammadHoffmannMuesgens, author = {Muhammad, Sulaman and Hoffmann, Christin and M{\"u}sgens, Felix}, title = {Assessing energy security risks : implications for household electricity prices in the EU}, series = {Energy}, volume = {327}, journal = {Energy}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1873-6785}, doi = {10.1016/j.energy.2025.136201}, pages = {1 -- 11}, abstract = {Energy security has emerged as a critical issue, especially for Europe, driven by escalating geopolitical tensions and the transition toward sustainable energy sources. Beyond affecting national energy supply, energy security also significantly influences the affordability of electricity for consumers. We examine the impact of energy security on household electricity prices, focusing on three key indicators: energy dependency, energy diversity, and geopolitical risk. Using panel data of 27 EU countries from 2007 to 2022, the analysis reveals that both energy diversity and dependency contribute to lowering electricity prices, while geopolitical risk shows no significant direct effect. However, the interaction between energy dependency and geopolitical risk reveals that during times of heightened geopolitical risks, a heavy reliance on foreign energy can lead to significantly higher electricity prices. Further 2SLS estimation and additional analysis with extended controls confirm the robustness of these findings. These findings offer valuable insights for policymakers focused on enhancing energy security.}, language = {en} } @misc{GengeNeuwirthAlDabbasetal., author = {Genge, Lucien and Neuwirth, Marius and Al-Dabbas, Khaled and Fleiter, Tobias and M{\"u}sgens, Felix}, title = {Optimising green value chains for the chemical industry in Europe}, series = {International journal of hydrogen energy}, volume = {199}, journal = {International journal of hydrogen energy}, publisher = {Elsevier BV}, address = {Amsterdam}, issn = {1879-3487}, doi = {10.1016/j.ijhydene.2025.152689}, pages = {1 -- 3}, abstract = {Transforming Europe's basic chemical industries for climate neutrality necessitates strategic decisions about sourcing green ammonia and methanol. Using a spatially detailed, techno-economic optimisation model for 72 industrial sites, we compare three distinct value chain setups: domestic production, hydrogen imports, and direct commodity imports. Direct commodity imports consistently emerge as the most cost-effective strategy for most countries, with average savings of 14 \% for ammonia and 18 \% for methanol in 2040. However, the picture is more diverse across the individual countries. Domestic ammonia production remains competitive in regions with abundant renewables like Southern Europe and Norway, while hydrogen imports offer strategic value for the largest industrial sites in Germany, the Netherlands, and hubs near the MENA region. On average, a fully domestic production of green ammonia would result in 15 \% higher costs at European level equal to about 1.4 billion €/year - compared to commodity imports. At site level, the cost premium ranges between -13 \% (domestic production is cheaper than imports) and +38 \%. Our findings provide policymakers with a foundation to develop industrial transition strategies that balance cost efficiency and sovereignty in the ammonia/fertiliser and methanol/chemicals value chains. They underline the importance of European cooperation by deploying best wind and solar potentials and establishing European energy transport infrastructure as backbone of a competitive net-zero industry.}, language = {en} } @misc{RadkeMuesgens, author = {Radke, Silvian M. and M{\"u}sgens, Felix}, title = {Mitigating negative electricity prices - batteries or flexibility in wind and solar?}, series = {2025 21st International Conference on the European Energy Market (EEM)}, journal = {2025 21st International Conference on the European Energy Market (EEM)}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {979-8-3315-1278-1}, issn = {2165-4093}, doi = {10.1109/EEM64765.2025.11050208}, pages = {1 -- 6}, abstract = {This paper analyses the influence of battery storage systems and high shares of price-inelastic generation on electricity prices. Within the last years, negative wholesale electricity prices have become a relevant topic in many electricity systems around the world. We develop a linear cost minimization model to analyze the relationship between price-inelastic generation and battery storage. We parameterize the model with three different scenarios which describe the German electricity market in the year 2030. Our model shows that both additional storage capacities and more flexible renewable generation are necessary to avoid high volatility in electricity prices and thereby reduce the number of hours with negative electricity prices.}, language = {en} }