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Electric Power Construction

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Research on Multi-Objective Bi-Level Optimization of Network-Storage Considering Transient Stability

FANG Chaoxiong1, WU Xiaosheng2, JIANG Yuewen2   

  1. 1. Economic Research Institute, State Grid Fujian Electric Power Co., Ltd, Fuzhou 350012, China; 2. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
  • Online:2020-07-01
  • Supported by:
    This work is supported by Science and Technology Project of State Grid Fujian Electric Power Co., Ltd.(No.SGTYHT/18-JS-206).

Abstract: With the continuous development of wind power and load demands, new challenges are brought to power grid planning by the issues including transmission congestion, wind curtailment, and operation safety and so on. Due to the fast response, flexible configuration and wide application, energy storage systems play an important role in wind power accommodation, transmission congestion, and system safe operation. In order to improve the transmission capacity and anti-disturbance capability of a power grid, the power transmission capacity, wind curtailment level and transient stability are comprehensively considered at the planning and operation level by involving the transient operation characteristics after faults. A two-layer network-storage joint planning model is established in multi-objective form with the system construction-operation indicator and system stability indicator. The outer-layer model is a multi-objective model considering the locating and sizing of the energy storage systems. The inner-layer model is a transmission network expansion planning model considering the unit commitment problem. In order to improve the solution efficiency, the power flow constraint of the expanded line, the charge and discharge model of the energy storage system and the generation cost curve are linearized. By solving the proposed model using NSGA-Ⅱ algorithm combined with GUROBI and developing the case study in the improved Garver 6-bus system, the validity and rationality of this model are verified in different scenarios.

Key words: wind power integration, transmission network expansion planning, energy storage system, multi-objective optimization, unit commitment

CLC Number: