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Optimierung des Energiemanagements durch Aggregatoren
Citation Link: https://doi.org/10.15480/882.16018
Publikationstyp
Doctoral Thesis
Date Issued
2025
Sprache
German
Author(s)
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2025-08-28
TORE-DOI
Citation
Technische Universität Hamburg (2025)
In this work, a mixed-integer linear optimization model is developed to depict the decision-making problem of energy aggregators (EAs), which includes the deployment planning of various types of flexible energy resources and the trading of energy on different markets for a set of households assigned to the EA. The central research contribution compared to previous works in the development of the EA model (EAM) is that, on the one hand, it represents a holistic approach, as different types of energy resources and energy markets are integrated into the aggregated energy management of a community of households, and on the other hand, it features a high level of detail in the modeling of the technical restrictions of energy resources, in particular power-to-heat systems with heat pumps. In a case study with two seasonal scenarios, each consisting of 62 days, the EAM is verified and validated for day-ahead planning for up to 111 households. The results show that the participating households can achieve clear economic added value through the EA and that this added value is based on complex synergies between the system components, which can only be exploited through holistic and differentiated modeling. Further analyses consider an additional improvement in the efficiency of EA energy management through the foresighted use of energy storage systems. Standardized strategies are identified that contribute to an increase in household trading surpluses for different constellations of days. In addition, a fairness analysis is carried out, which shows that the internal trading between households depicted in the EAM is problematic in terms of fairness, as the flexibility provided to the community is not sufficiently rewarded. An ex-post redistribution of the realized community surpluses is proposed as an approach to improve fairness between households.
Furthermore, the EAM is considered in the context of local energy markets. For this purpose, a model of a local market is developed that is integrated into a higher-level day-ahead process together with the EAM, thereby iteratively depicting local energy trading between EAs. Application in a case study shows that the composition of EAs' households has a strong influence on the resulting trading relationships. For example, specialization of EAs in specific types of households, resulting in heterogeneity among EAs, is advantageous in terms of local market efficiency compared to a set of unspecialized and thus homogeneous EAs, which, on the other hand, results in more internal energy exchange between the households of the respective EAs. In the case of a heterogeneous composition of EAs, a further study analyzes the possibility of targeted market interventions to reduce line congestion. A comparison of four different approaches, each with nine variants, leads to the conclusion that such a market-based approach can contribute positively to reducing line congestion, but that the potential is limited and the approaches presented should therefore be considered as supporting other congestion management tools.
In conclusion, it is clear that EAs can play an important role in future energy systems by providing economically efficient energy management for households. The EAM developed in this thesis represents a basic model for depicting the decision-making problems of such energy management. There are many configuration options and influencing factors that must be taken into account for the successful application of the concept and the realization of the potential of EAs.
Furthermore, the EAM is considered in the context of local energy markets. For this purpose, a model of a local market is developed that is integrated into a higher-level day-ahead process together with the EAM, thereby iteratively depicting local energy trading between EAs. Application in a case study shows that the composition of EAs' households has a strong influence on the resulting trading relationships. For example, specialization of EAs in specific types of households, resulting in heterogeneity among EAs, is advantageous in terms of local market efficiency compared to a set of unspecialized and thus homogeneous EAs, which, on the other hand, results in more internal energy exchange between the households of the respective EAs. In the case of a heterogeneous composition of EAs, a further study analyzes the possibility of targeted market interventions to reduce line congestion. A comparison of four different approaches, each with nine variants, leads to the conclusion that such a market-based approach can contribute positively to reducing line congestion, but that the potential is limited and the approaches presented should therefore be considered as supporting other congestion management tools.
In conclusion, it is clear that EAs can play an important role in future energy systems by providing economically efficient energy management for households. The EAM developed in this thesis represents a basic model for depicting the decision-making problems of such energy management. There are many configuration options and influencing factors that must be taken into account for the successful application of the concept and the realization of the potential of EAs.
Subjects
aggregators
energy management
smart grids
mixed integer linear programming
heat pumps
energy trading
DDC Class
330: Economics
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Hoth_Kai_Optimierung des Energiemanagements durch Aggregatoren.pdf
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