Distributionally robust optimization configuration method for island microgrid considering extreme scenarios  

作　　者：Qingzhu Zhang Yunfei Mu Hongjie Jia Xiaodan Yu Kai Hou 

机构地区：[1]Key Laboratory of Smart Grid of Ministry of Education,Tianjin University,Tianjin,300072,China [2]Key Laboratory of Smart Energy&Information Technology of Tianjin Municipality,Tianjin University,Tianjin,300072,China

出　　处：《Energy and AI》2024年第3期179-194,共16页能源与人工智能（英文）

基　　金：funded by the National Natural Science Foundation of China(Grant/Award Numbers:52177107 and 52222704);Science and Technology Project of Tianjin Municipality,China(22JCZDJC00780).

摘　　要：The marine climate conditions are intricate and variable. In scenarios characterized by high proportions of wind and solar energy access, the uncertainty regarding the energy sources for island microgrid is significantly exacerbated, presenting challenges to both the economic viability and reliability of the capacity configuration for island microgrids. To address this issue, this paper proposes a distributionally robust optimization (DRO) method for island microgrids, considering extreme scenarios of wind and solar conditions. Firstly, to address the challenge of determining the probability distribution functions of wind and solar in complex island climates, a conditional generative adversarial network (CGAN) is employed to generate a scenario set for wind and solar conditions. Then, by combining k-means clustering with an extreme scenario selection method, typical scenarios and extreme scenarios are selected from the generated scenario set, forming the scenario set for the DRO model of island microgrids. On this basis, a DRO model based on multiple discrete scenarios is constructed with the objective of minimizing the sum of investment costs, operation and maintenance costs, fuel purchase costs, penalty costs of wind and solar curtailment, and penalty costs of load loss. The model is subjected to equipment operation and power balance constraints, and solved using the columns and constraints generation (CCG) algorithm. Finally, through typical examples, the effectiveness of this paper’s method in balancing the economic viability and robustness of the configuration scheme for the island microgrid, as well as reducing wind and solar curtailment and load loss, is verified.

关 键 词：Island microgrid Extreme scenario Distributionally robust optimization Conditi onal generative adversarial network 

分 类 号：TM727[电气工程—电力系统及自动化]