Optimal Energy Scheduling of Grid-connected Microgrids with Battery Energy Storage
Licentiate thesis, 2020
This thesis contributes to the solution of the above-mentioned issues with an energy management model developed for a grid-connected microgrid that uses battery energy storage as a flexible energy resource. The performance of the model was evaluated in different test cases (simulations and demonstrations) in which the model optimized the schedule of the microgrid resources and the energy exchange with the connected main grid, while satisfying the constraints and operational objectives of the microgrid. Coordination with the distribution system operator was proposed to ensure that the microgrid energy scheduling solution would not violate the constraints of the main grid.
Two radial distribution grids were used in simulation studies: the 12-kV electrical distribution grid of the Chalmers University of Technology campus and a 12.6-kV 33-bus test system. Results of the Chalmers’ test case assuming the operation of two grid-connected microgrids with battery energy storage of 100-200 kWh showed that the microgrids’ economic optimization could reduce the cost for the distribution system operator by up to 2%. Coordination with the distribution system operator could achieve an even higher reduction, although it would lead to sub-optimal solutions for the microgrids. Application of decentralized coordination showed the effectiveness of utilizing microgrids as flexible entities, while preserving the privacy of the microgrid data, in the simulations performed with the 33-bus test system.
The developed microgrid energy management model was also applied for a building microgrid, where the battery energy storage was modeled considering both degradation and real-life operation characteristics derived from measurements conducted at real residential buildings equipped with stationary battery energy storages. Simulation results of a building microgrid with a 7.2 kWh battery energy storage showed that the annual building energy and battery degradation cost could be reduced by up to 3% compared to when the impact of battery degradation was neglected in the energy scheduling. To demonstrate the model’s practical use, it was integrated in an energy management system of the real buildings, where the buildings’ battery energy storages and, by extent, their energy exchange with the main grid, were dispatched based on the model’s decisions in several test cases.
The test cases’ results showed that the model can reduce the energy cost of the microgrid both in short-term and in long-term. Moreover, with the help of this model, the microgrid can be employed as a flexible resource and reduce the operation cost of the main distribution grid.
Battery energy storage
Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components
K.E. Antoniadou–Plytaria, D. Steen, L.A. Tuan, O. Carlson, and M. A. F. Ghazvini, “Market-based energy management model of a building microgrid considering battery degradation,” submitted for second-round review on Transactions on Smart Grid, Aug. 2020.
Energy Scheduling Strategies for Grid-connected Microgrids: A Case Study on Chalmers Campus
2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe),; (2019)
Paper in proceedings
Chalmers Campus as a Testbed for Intelligent Grids and Local Energy Systems
IEEE International Conference on Smart Energy Systems and Technologies (SEST),; (2019)
Paper in proceedings
From micro towards Mega GRID: Interaction of micro grids in Active Distribution Network (m2M-GRID)
Swedish Energy Agency, 2017-02-01 -- 2020-03-31.
Areas of Advance
Other Electrical Engineering, Electronic Engineering, Information Engineering
Chalmers University of Technology
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Opponent: Senior Researcher Henrik W. Bindner, Head of Research Group at Center for Electrical Power and Energy at DTU Electrical Engineering, Kgs. Lyngby, Denmark