In order to enhance the power supply capability and disaster resistance ability of power systems under extreme natural disasters
a multi-objective planning method of anti-disaster backbone grid is proposed with the guarantee rate of the load requirements
security operation constraints of the power system and connectivity of the network topology satisfied. In the proposed strategy
a multi-objective planning model of anti-disaster backbone grid
in which the reinforce cost of differential planning
the efficiency of power resupply after a disaster and the ability of the backbone grid to resist the disaster are considered comprehensively
is constructed for maximizing economics
resilience and network survivability. The graph repair strategy is utilized in comprehensive learning particle swarm optimization algorithm
which increases the feasible solution space of the algorithm. Then
the mixed strategy Nash equilibrium
which can balance the benefit of each objective function
is adopted to extract the best compromise solution with the optimal equilibrium value from the Pareto fronts obtained by the algorithm. The feasibility of the proposed method is verified by the numerical results of a regional power grid in Guangdong Province.
Coordinated Planning for AC/DC Hybrid Distribution Networks Considering Equilibrium Between Economy and Resilience
Nash Equilibrium Based Optimal Control Method for Hydrogen Production System with Photovoltaic-Storage Coupling
日前电力市场不完全信息条件下的电力供需双边博弈模型
基于动态博弈的配电网单相电力用户用电行为分析
Related Author
CHEN Tiantian
TANG Wei
WANG Zhaoqi
ZHANG Lu
ZHANG Bo
MA Ziyao
LI Jianlin
WANG Lifang
Related Institution
Electric Power Research Institute of State Grid Shanghai Municipal Electric Power Company
College of Information and Electrical Engineering, China Agricultural University
National User-Side Energy Storage Innovation Research and Development Center (North China University of Technology)
University of Chinese Academy of Sciences
Key Laboratory of High Density Electromagnetic Power and Systems (Chinese Academy of Sciences), Institute of Electrical Engineering, Chinese Academy of Sciences