A TxQoS-aware business transaction framework

In this thesis, we propose a transaction framework to provide comprehensive and flexible transaction support for contract-driven, service-oriented business processes. The research follows the research method outlined below. Initially, a thorough investigation on current state of affairs was made. Afterwards, we carried out a case study, which we utilized to identify the problems that are likely to occur during the execution of business processes. As the result of the solution design, the concepts, scenarios, life cycles, reference architectures, and mechanisms were proposed to address the problems. The design took place on the conceptual level, while the coding/programming and implementation is out of the scope of this thesis. The business-oriented solution design allows for transaction qualities to be specified and guaranteed by a contractual approach named as TxQoS (Transactional Quality of Service). The technology-oriented design enables flexible composition of ATCs (Abstract Transaction Constructs) as a transaction schema to support the execution of complex processes. As the last step of research, we validated the feasibility of our design by a utility study conducted in a large telecom project, which has complex processes that are service-oriented and contract-driven. Finally, we discussed the contributions and limitations of the research. The main contribution of the thesis is the BTF (Business Transaction Framework) that addresses process execution reliability. The TxQoS approach enables the specification of transaction qualities in terms of FIAT (Fluency, Interference, Alternation, Transparency) properties. This businessfriendly approach allows the providers and users to agree on transaction qualities before process execution time. The building blocks of the proposed framework, ATCs, are reusable and configurable templates, and are abstracted and generalized from existing transaction models. The various transaction requirements of sub-processes and process chunks can be represented by corresponding ATCs, which allow for a flexible composition. Integrated, the TxQoS and ATC approaches work together to form a TxQoS-aware business transaction framework

Scheduling of Resources in Renewable Energy Communities

This work presents a detailed study of the scheduling of power and energy resources in renewable energy communities (RECs). The study has been developed starting from the analysis of a single basic unit of the community, i.e., the prosumer and its microgrid, to the scheduling and expansion of the energy community concept with several prosumers through several scenarios. The individual scheduling problem of the prosumer has been studied as a day-ahead deterministic problem and as a multistage stochastic problem to consider uncertainties associated with energy generation and energy consumption. Furthermore, an approach has been formulated to consider the integration of bidirectional charging services of electrical vehicles within a local energy system with the presence of renewable generation. Moreover, this thesis focuses on the scenario in which direct energy transactions between prosumers located within a REC are allowed in addition to the energy transactions with the external energy provider. The day-ahead scheduling problem has been addressed by a centralized approach and by a distributed approach based on the alternating direction method of multipliers (ADMM). The developed approaches provide the scheduling of the available energy resources to limit the balancing action of the external grid and allocate the internal network losses to the corresponding energy transactions. Finally, the thesis presents a coordinated day-ahead and intra-day approach to provide the optimal scheduling of the resources in a REC. In this case, the ADMM-based procedure, which is aimed at minimizing the total energy procurement costs, is adapted to cope with the impact of the fluctuation of both the local energy generation and demand during the day. To achieve this, a day-ahead multistage stochastic optimization approach is combined with an intra-day decision-making procedure, able to adjust the scheduling of the energy resources according to the current operational conditions