Optimization and extraction of an operation strategy for the distributed energy system of a research station in Antarctica

A distributed energy system (DES) can integrate renewable resources and achieve efficient energy utilization, and it is a common form of energy system for isolated systems. However, a multienergy complementary energy supply scheme makes operating a DES complicated. To ensure the system operates efficiently, it is necessary to study its operation strategy. However, currently, the research on DES operation optimization mostly is in the optimization result itself, hence lacking the transferring of the optimized operation strategy to engineering applications, which is difficult to apply to the actual energy saving operation. Therefore, this paper takes the DES of a scientific research station in Antarctica as an example when it comes to the optimization of its operation strategy, extracting the control logic for engineering applications from the optimized operation strategy. Aiming for the lowest primary energy consumption of the DES across an entire year, a model for optimal operation is presented and formulated as a Mixed Integer Linear Program (MILP), and further solved by the General Algebraic Modeling System (GAMS). The operation strategy of the DES is optimized and the energy saving space is analyzed. Furthermore, through strategy interpretation, the available control logic of the project is extracted from the optimized strategy, and the extraction effect is verified. The results show that the primary energy consumption of the optimized operation strategy can be reduced by 11.8% when compared with the original operation strategy. By using the engineering control logic extracted from the optimized operation strategy to adjust the original operation strategy, the primary energy consumption of the system can be reduced by 9.6%. The current study can provide a scientific and reasonable scheduling strategy for the actual operation of a DES and provide guidance and reference for the optimal operation of an existing DES. (C) 2019 Elsevier Ltd. All rights reserved.