[1]CHEN Shiming,MA Fei,GAO Yanli.Robust optimization design of an electrical cyber-physical system based on constrained cost[J].CAAI Transactions on Intelligent Systems,2020,15(3):623-632.[doi:10.11992/tis.201812034]
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Robust optimization design of an electrical cyber-physical system based on constrained cost
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
15
Number of periods:
2020 3
Page number:
623-632
Column:
吴文俊人工智能科学技术奖论坛
Public date:
2020-05-05
- Title:
- Robust optimization design of an electrical cyber-physical system based on constrained cost
- Keywords:
- complex network theory; electrical cyber-physical system; interdependent network; node configuration optimization; power-load optimization; robustness; constraints cost
- CLC:
- TM73
- DOI:
- 10.11992/tis.201812034
- Abstract:
- In view of the complexity of networks and considering the practical problems, such as power network expansion, encountered by networks, this study proposes procedures on how to set up additional stations to optimize load distribution and improve the robustness of a power system under cost constraints. First, the topological structure data of a province in the Central China power grid is used to build a sectional one-to-one coupled interdependent network model of power grid and cyber network. Then, the nonlinear load–volume model is used as the cascading failure model of the system. Given the actual situation of planning the installation of new substations in the power grid, four possible node addition strategies for the newly added power node and its cyber equipment are proposed. Moreover, simulation and analysis of the power cyber-physical system of a province in the Central China power grid and the IEEE 118 Bus System were conducted on the basis of the four strategies in terms of network robustness and power–load optimization. The simulation results show that, when taking the new node connected to the maximum and minimum power–load nodes in the existing network as the reference, the required robust optimization can be achieved with only a few configured nodes. The test results have certain guiding significance for the optimal allocation of limited resources in the construction and planning of a power system.
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1900-01-01