PhD Defence by Yufei Xi
24.11.2021 kl. 13.00 - 16.00
Yufei Xi, AAU Energy, will defend the thesis "Optimal Management of Flexible Resources in Multi-Energy Systems"
Optimal Management of Flexible Resources in Multi-Energy Systems
Professor Zhe Chen
Professor Henrik Lund
Associate Professor Mads Pagh Nielsen
Associate Professor Mads Pagh Nielsen, Aalborg University, Denmark (Chairman)
Olav Bjarte Fosso, Norwegian University of Science and Technology
Zita Maria Almeida do Vale, Polytechnic of Porto
Climate change and fossil resource depletion promote the deployment of fluctuating renewable energy sources, where the energy market is experiencing a profound transition. Accordingly, flexibility has been especially prized in the multi-energy system (MES) with higher penetration of renewable energy (e.g., solar and wind). In recent years, several measures have been implemented to increase flexibility in supply and demand such as storage installation and energy integration. Meanwhile, the optimal management issues of flexible resources (FRs) should be discussed and addressed.
From technical and economic perspectives, considering the interaction between system operation and market procedures is the key to research. On the one hand, the integration of energy networks brings broader development potential for FRs, as well as uncertainty and complexity in integrated operations. On the other hand, the liberalization of the market enables the market outcome closely related to the system operation, which means that the factors such as energy prices must be considered in the decision-making for the optimal management of FRs. Therefore, this Ph.D. project focuses on rationally utilizing and dispatching various FRs, as well as discusses solutions to provide the operation of the MES in an efficient and economical way.
Firstly, various FRs in MESs have been identified and studied including the investigation of their characteristics and mathematical models. They have been appropriately combined and used in the integrated gas, electricity and district heating system. This part lays the foundation for the subsequent optimization of the operation and management of FRs.
Secondly, this thesis has contributed to the aspect of quantifying FRs. A multi-objective optimization model for coordinating the operation of FRs has been proposed. The model allows the MES to intelligently select and use FRs based on price signals of the day-ahead market. An illustrative case has been analyzed to show the potential of the proposed approach in increasing social welfare and reducing the curtailment of renewable energy.
In terms of market design, the mutual influence of the real-time market and system operation has been further considered. Throughout the project, two solutions to optimize the MES with FRs according to the different market modes have been proposed:
• In the case of centralized operation and management of the MES, a bi-level programming model for integrating flexible demand has been developed. In this model, an integrated gas, electricity and district heating system with aggregated smart buildings is described. These smart buildings use photovoltaic power generation, electric vehicles with storage, electric heating and other technologies, and they are managed and operated by the aggregator considering real-time energy prices.
• Taking into account the limited communication with existing energy operators, an equilibrium model for optimally scheduling the MES with FRs has been developed. In this model, each energy subsystem has an independent operator to pursues its maximum benefits and coordinates with each other until a satisfying equilibrium.
The validity of the models has been verified in their corresponding illustrative cases. Meanwhile, the proposed models can optimally allocate the resources and reflect the price and quantity of the energy transaction in the MES.
Furthermore, the impact of the coordination and optimization of FRs on the MES, specifically the demand response (DR) participation level, is also analyzed in this project. The simulation results show that: 1) With the increase of coordinated FRs, the social welfare and wind power curtailment of the MES are significantly improved; 2) The Bi-directional feedback between the consumption of power systems and the real-time electricity prices of the market achieved by DR management has positive impacts on both system and market, such as improving abnormal peak-prices and reducing the investment for the storage capacity.