Institut für Interoganizational Management & Performance

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Browsing Institut für Interoganizational Management & Performance by Subject "Bioeconomy"

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    Modelle und Lösungsverfahren zur langfristigen Planung der Stromproduktion einer flexiblen Biogasanlage unter Berücksichtigung von Verschleiß
    (2021) Butemann, Hendrik; Schimmelpfeng, Katja
    One of the most important measures against climate change is the shift from fossil to renewable energies. Many countries have therefore made it their goal to increase the share of renewable energies for electricity generation. In Germany, the share in 2019 was 40.2%, of which biomass accounted for 20.6%. This category includes biogas plants, which, unlike other sources of renewable energy, have the advantage of not being dependent on certain weather conditions. They are considered a flexible option for electricity generation because they can produce electricity when neither the sun is shining nor the wind is blowing. When the first biogas plants were put into operation, revenues from electricity production could be maximized by having the combined heat and power unit (CHP) associated with the biogas plant generate electricity continuously. To take advantage of the flexibility of biogas plants, German legislators introduced premiums that contained incentives to produce electricity during periods of low supply from other renewable energy sources. Since then, biogas plant operators have been able to maximize their revenues when the CHP produces electricity on demand, i.e., in start-stop mode. However, a large number of starts and stops of the CHP causes altered wear and tear and must be taken into account in the long-term planning of the electricity production of a biogas plant. The aim of this dissertation is therefore to use operations research methods to develop cyclical electricity production plans for biogas plants that take into account the wear and tear of the CHP and the timing and costs of maintenance activities in order to support biogas plant operators in maximizing their revenues. For this purpose, first a classification of electricity production planning of biogas plants into the planning tasks along the biomass-based supply chain is given. Subsequently, the basics of biogas plants are explained, which include their relevance in Germany, their way of operation, service and maintenance as well as the legal framework for their operation. The research gap, which is filled by this dissertation, results from the literature review on quantitative approaches for the operation of biogas plants. It shows that there is still no research work that sufficiently addresses the wear and tear of CHP in flexible operation and the planning of maintenance activities in connection with electricity production. Therefore, a conceptual optimization model is developed that accurately replicates the non-linear wear that occurs in reality and thus enables simultaneous planning of electricity production and maintenance activities. For better applicability with standard solvers, the model is additionally linearized. A case study based on real-world data reveals that a flexible biogas plant achieves higher total revenues than a continuously operated biogas plant under the conditions prevailing in Germany, even when maintenance costs are taken into account. The conceptual optimization model is then extended to produce a cyclical plan that biogas plant operators can apply on a weekly basis. In the following chapter, a greedy heuristic for generating a starting solution as well as a genetic algorithm and a tabu search are developed with the goal of reducing the computation time when solving the extended model. For this purpose, the basics of the individual solution methods are first explained and the input data are adapted to the problem with the help of parameter tuning. An extensive numerical study, in which the input parameters electricity prices, costs for maintenance activities, wear and tear of the CHP and biogas storage capacity are varied, compares the performance of the methods with that of the extended optimization model. In all scenarios, the tabu search determines the best result in low runtime. A summary and an outlook on further research opportunities conclude the dissertation.
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    Strategic network planning in biomass-based supply chains
    (2021) Fichtner, Stephan; Meyr, Herbert
    Fossil resources are limited and will run short. Moreover, the extensive usage of fossil resources is discussed as a key driver for climate change which means that a changeover in basic economic and ecological thinking is necessary. Especially for energy production, there has to be a movement away from the usage of fossil resources and towards renewable resources like wind, water, sun, or biomass. Within the first part of this work a structured review of recent literature on the long-term, strategic planning of biomass-based supply chains is provided. Therefore, in the first step, the overall research field “bioeconomy” by means of the various utilization pathways of biomass is structured and the demand-oriented view of supply chain management models and the supply-oriented view of bioeconomy are combined. In the second step, a literature review of operations research models and methods for strategic supply chain planning in biomass-based industries are provided. Thirdly, trends are identified and conclusions about research gaps are drawn. One of the identified research gaps is to make biomass-based supply chains profitable on their own, i.e., without governmental subsidies. Therefore, new optimization models are necessary, which should be as close to reality as possible, by for example considering risks and actual surrounding constraints concerning the legal framework. Within the second part of this work, an approach for strategic optimization of biogas plants considering increased flexibility is developed. Biogas plants can produce their energy flexibly and on-demand if their design is adjusted adequately. In order to achieve a flexibly schedulable biogas plant, the design of this plant has to be adapted to decouple the biogas and electricity production. Therefore, biogas storage possibilities and additional electrical capacity are necessary. The investment decision about the size of the biogas storage and the additional electrical capacity depends on the fluctuation of energy market prices and the availability of governmental subsidies. This work presents an approach supporting investment decisions to increase the flexibility of a biogas plant by installing gas storages and additional electrical capacities under consideration of revenues out of direct marketing at the day-ahead market. In order to support the strategic, long-term investment decisions, an operative plant schedule for the future, considering different plant designs given as investment strategies, using a mixed-integer linear programming (MILP) model in an uncertain environment is optimized. The different designs can be evaluated by calculating the net present value (NPV). Moreover, an analysis concerning current dynamics and uncertainties within spot market prices is executed. Furthermore, the influences concerning the variation of spot market prices compared to the influence of governmental subsidies, in particular, the flexibility premium, are revealed by computational results. Besides, the robustness of the determined solution is analyzed concerning uncertainties. The focus of the third part of the work is to consider variable substrate feeding in the mentioned optimization approach because it is expected that variable substrate feeding and thus a demand-oriented biogas production can influence the optimized plant design. In order to support this extension, an operative plant schedule for the future, considering (non-) linear technical characteristics of the biogas plant and the legal framework is optimized. Therefore, mixed-integer linear programming models with integrated approximation approaches of non-linear parts, representing the biogas production rates, are constructed. Furthermore, the influences of fluctuating spot market prices, governmental subsidies, and biomass feedstock prices on the decisions are analyzed for a fictional case example, which is based on a biogas plant in southern Germany. These numerical experiments show that variable substrate feeding can play a decisive role during the optimization of a biogas plant schedule as part of a long-term design optimization. However, the size of the strategic optimization problem makes the use of a heuristic solution algorithm necessary.