Ludger Leenders

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Leenders

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Ludger

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0000-0002-2578-4257

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Publications 1 - 10 of 21

Flexibility from industrial demand-side management in net-zero sector-coupled national energy systems
Bardow, André; Mayer, Patricia; Heer, Mario; et al. (2024)
Frontiers in Energy Research
National energy systems require flexibility to accommodate increasing amounts of variable renewable energy. This flexibility can be provided by demand-side management (DSM) from industry. However, the flexibility potential depends on the characteristics of each industrial process. The enormous diversity of industrial processes makes it challenging to evaluate the total flexibility provision from industry to sector-coupled energy systems. In this work, we quantify the maximum cost reductions due to industrial DSM in the net-zero sector-coupled Swiss energy system, and the relationship between cost reductions and various industrial process characteristics. We analyze the flexibility of industrial processes using a generic, process-agnostic model. Our results show that industrial DSM can reduce total energy system costs by up to 4.4%, corresponding to 20% of industry-related energy costs. The value of flexibility from industrial DSM depends not only on the process characteristics but also on the system’s flexibility alternatives, particularly for flexibility over seasonal time horizons. As one specific option for industrial DSM, we find that thermal energy storage (TES) technologies available today could realize between 28% and 61% of the maximum cost reductions from industrial DSM, making TES a promising DSM solution and showing that industrial DSM is an accessible and cost-effective flexibility option.
Bilevel optimization of energy system transition pathways considering competition in markets
Shu, David Yang; Reinert, Christiane; Mannhardt, Jacob; et al. (2024)
The energy system transition towards net-zero greenhouse gas emissions involves multiple decision makers. While greenhouse gas mitigation targets must be jointly achieved, the decision makers are primarily interested in minimizing their individual cost of energy supply. The competing interest of decision makers are commonly neglected in optimization models of the energy system transition. To overcome this shortcoming, we model the energy system transition as a multi-leader-single-follower game: In our model, individual decision makers develop investment strategies in shared electricity and carbon markets. We formulate the game as a bilevel optimization problem that reflects the multi-level nature of the decision-making process. We find an equilibrium solution to the multi-leader-single-follower game by applying the Gauss-Seidel method. Our case study of the European electricity system shows that the bilevel optimization problem results in a transition pathway with higher capacity expansion compared to a centralized approach. Further, the average market clearing price and the spread of locational market clearing prices are lower. As a result, overall costs are reduced when considering trading and carbon allowance costs on top of the investment and operating costs. Hence, considering competition and market behavior is vital in modeling the energy system transition.
Where to market flexibility? Integrating continuous intraday trading into multi-market participation of industrial multi-energy systems
Nolzen, Niklas; Ganter, Alissa; Baumgärtner, Nils; et al. (2025)
Computers & Chemical Engineering
The rising share of volatile renewable electricity generation increases the demand for flexibility. Flexibility can be offered by industrial multi-energy systems and marketed either on the continuous intraday, day-ahead, or balancing-power markets. Thus, industrial multi-energy systems face the question where to market their flexibility. We propose a two-step method to integrate trading on the continuous intraday market into a multi-market optimization for flexible industrial multi-energy systems. First, we estimate revenues from continuous trading in the intraday market, employing option-price theory. Second, a multi-stage stochastic optimization allocates the flexibility to the three markets. The case study of an industrial multi-energy system demonstrates that coordinated bidding in all three markets reduces costs the most. A sensitivity analysis reveals that the optimal split between the different markets strongly depends on the intraday market volatility. Overall, the proposed method provides a practical decision-support tool for multi-energy systems participating in short-term electricity and balancing-power markets.
The role of carbon capture & storage to achieve net-zero energy systems: Trade-offs between economics and the environment
Shu, David Yang; Deutz, Sarah; Hartmann, Jan; et al. (2023)
Monetizing Flexibility in Day-Ahead and Continuous Intraday Electricity Markets
Nolzen, Niklas; Ganter, Alissa; Baumgärtner, Nils; et al. (2022)
Computer Aided Chemical Engineering ~ 14th International Symposium on Process Systems Engineering
The rising share of renewable energies increases supply uncertainty in the energy system. To make short-term adjustments more cost-efficient, the continuous intraday market was introduced. The continuous intraday market allows flexible capacity to exploit the price volatilities by asset-backed trading. In asset-backed trading, flexible capacity is continuously traded depending on the real-time electricity price and the marginal cost for electricity production. However, the flexibility for the continuous intraday market needs already be considered during the commitment on the day-ahead market. Hence, this paper proposes an optimal joint bidding strategy for day-ahead and continuous intraday market participation. For this purpose, we employ option-price theory and stochastic optimization. A case study for a flexible multi-energy system shows savings of 11 % by participating in both markets compared to only the day-ahead market. Thus, the bidding strategy provides efficient decision support in short-term electricity markets.
Scenario-Based Threshold Control of Energy Storage Systems for Peak Shaving
Kaiser, Katharina; Kreft, Markus; Leenders, Ludger; et al. (2025)
2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)
Power flows in distribution grids are increasing due to the electrification of transportation and heating, and a growing share of distributed generation. Battery energy storage systems (BESSs) can reduce the stress on the grid and defer grid upgrades by shaving local power peaks. In this context, this work develops, implements, and validates a peak shaving algorithm for a real-world utility-owned BESS. First, it proposes and compares a robust and a stochastic formulation for computing the peak-shaving threshold in simulations. The results indicate that the robust formulation with five scenarios performs best for the given transformer station. In the subsequent real-world experiment, the approach achieves 55.6% of the ideal daily reduction with perfect foresight, demonstrating that the approach effectively shaves power peaks in practice.
Insights from Life-Cycle Assessment of the Carbon Capture and Storage Supply Chain from the DMX™ Demonstration in Dunkirk (3D) Project
Shu, David Yang; Bewi Komesse, Helen; Beauchet, Sandra; et al. (2022)
SSRN Electronic Journal ~ Proceedings of the 16th Greenhouse Gas Control Technologies Conference (GHGT-16)
The formation of carbon dioxide (CO2) in industrial processes such as cement or steel production is hard to avoid. To prevent the release to the environment, CO2 can be separated from industrial point sources to be permanently stored in geological storage. However, the required carbon capture and storage (CCS) supply chain entails substantial material and energy demands over the life cycle. To quantify the effectiveness of CCS supply chains in reducing greenhouse gas (GHG) emissions, life-cycle assessment (LCA) considers the environmental impacts over the full life cycle. Furthermore, environmental impact categories beyond climate change can be analyzed to predict potential environmental hot spots in the CCS supply chain. Due to a lack of primary data, LCA studies rely on literature data, proxies, and simulations to predict the environmental impacts of CCS supply chains. However, recent full-scale CCS projects offer the opportunity to increase the accuracy and confidence in the results of LCAs using real-world data from engineering studies. In this paper, we conduct an LCA of a megaton-scale CCS supply chain designed within the Horizon 2020 project DMX™ Demonstration in Dunkirk (3D). The LCA is based on engineering studies for a CCS supply chain for a steel production plant in Northern France. We evaluate the environmental performance of the supply chain for the local energy supply at the steel plant. A life-cycle CCS efficiency of 93 % can be achieved for storing 1 Mt of CO2 annually, which corresponds to a reduction of the GHG emissions of the steel plant by 6.0 %. In addition, environmental impacts in categories other than climate change increase by less than 1.8 % in most impact categories except for ionizing radiation, where an increase of 18.4 % is observed due to the high share of nuclear power in the French electricity grid. Transportation based on ships emerges as the main contributor to several impact categories due to continued reliance on natural gas as fuel. Even in a worst-case scenario, assuming an all-fossil energy supply, a life-cycle CCS efficiency of 64 % can be achieved. Hence, the proposed CCS supply chain can effectively reduce the GHG emissions of steel production already today. Our study underlines the importance of the energy supply in climate change and other impact categories and points towards transportation as a potential future environmental hot spot. To improve the tradeoff between climate change mitigation and environmental impacts shifting to other categories, the development of CCS projects needs to ensure a low-impact energy supply for all steps of the CCS supply chain, including transportation.
Flexibility-expansion planning for enhanced balancing-power market participation of decentralized energy systems
Nolzen, Niklas; Leenders, Ludger; Bardow, André (2021)
Computer Aided Chemical Engineering ~ 31st European Symposium on Computer Aided Process Engineering
The rising share of renewable energy sources in power supply and the shut-down of conventional power plants lead to a need for new providers of balancing power. Balancing-power could be newly provided by the flexibilization of decentralized energy systems. In this contribution, we propose flexibility-expansion planning for decentralized energy systems to account for investments in additional units for flexibilization. Flexibility-expansion planning leads to a stochastic optimization model for optimal investment decisions towards increased operational flexibility. The stochastic optimization model consists of a design optimization and a two-stage stochastic program. In a case study, the method is applied to a decentralized energy system participating in the German tertiary balancing-power market. Savings of up to 5.9 % can be achieved with additional investments in heat storage. Thus, flexibility-expansion planning allows operators of decentralized energy systems to optimally invest in flexible technologies for improved balancing-power market participation.
Concurrent deficit and surplus situations in the future renewable Swiss and European electricity system
Lienhard, Nadine; Mutschler, Robin; Leenders, Ludger; et al. (2023)
Energy Strategy Reviews
European countries aim to achieve net zero CO2 emissions by mid-century. Consequently, the European energy system and particularly the electricity system must undergo major changes. An increasing electrification of the mobility and heating sector is required for decarbonisation, which reserves electricity a central role on the path towards net zero CO2 emissions. However, to meet emission targets, the electricity supply must originate from low emission generation sources. According to the TYNDP 2018 scenarios, the electricity supply in Europe is expected to predominantly originate from renewable energy converters, introducing new challenges to energy systems. Due to the seasonality of renewable energy sources, most European countries, including Switzerland, are expected to face seasonal imbalances of supply and demand in the electricity system. According to national energy strategies of countries with deficits in electricity, the resulting shortages in supply should be covered with imports from their neighbouring countries. This study assesses concurrent deficit and surplus situations among different balancing zones and highly renewable energy systems. Thereby, possible infeasible energy balances are identified by analysing the case of Switzerland and its neighbouring countries Austria, Germany, France and Italy based on published scenarios. The results show, that there are concurrent deficit situations in Switzerland and its neighbouring countries in particular during winter. Hence, the results of this analysis challenge the current energy strategies and the aim to reach net zero CO2 emissions in Switzerland and Europe.
Bilevel optimization for joint scheduling of production and energy systems
Leenders, Ludger; Hagedorn, Dörthe Franzisca; Djelassi, Hatim; et al. (2022)
Optimization and Engineering
Energy-intensive production sites are often supplied with energy by on-site energy systems. Commonly, the scheduling of the systems is performed sequentially, starting with the scheduling of the production system. Often, the on-site energy system is operated by a different company than the production system. In consequence, the production and the energy system schedule their operation towards misaligned objectives leading in general to suboptimal schedules for both systems. To reflect the independent optimization with misaligned objectives, the scheduling problem of the production system can be formulated as a bilevel problem. We formulate the bilevel problem with mixed-integer decision variables in the upper and the lower level, and propose an algorithm to solve this bilevel problem based on the deterministic and global algorithm by Djelassi, Glass and Mitsos (J Glob Optim 75:341–392, 2019. https://doi.org/10.1007/s10898-019-00764-3) for bilevel problems with coupling equality constraints. The algorithm works by discretizing the independent lower-level variables. In the scheduling problem considered herein, the only coupling equality constraints are energy balances in the lower level. Since an intuitive distinction is missing between dependent and independent variables, we specialize the algorithm and add a procedure to identify independent variables to be discretized. Thereby, we preserve convergence guarantees. The performance of the algorithm is demonstrated in two case studies. In the case studies, the production system favors different technologies for the energy supply than the energy system. By solving the bilevel problem, the production system identifies an energy demand, which leads to minimal cost. Additionally, we demonstrate the benefits of solving the bilevel problem instead of solving the common integrated or sequential problem.

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