In traditional distributed state estimation, a subarea does not consider the network model and operating state of its neighboring subnet when making its own estimation independently while making up for the previously neglected information only during coordination. To remedy such a situation, a new distributed state estimation based on decomposition and coordination equivalent to external network concentration is presented according to the multi-agent theory. The large-scale power system is decomposed into a number of overlapping subsystems to build a 2-dimensional federated multi-agent framework suitable for distributed state estimation. By establishing the external network concentration equivalent model all subsystems are enabled to consider their neighbors influence. Thus the estimate solution in each subarea can satisfy definite precision requirements even without outside coordination. A heuristic coordination and correction mechanism based on the blackboard model is founded and the information fusion rate accelerated. And the adjacent systems are subjected to the effect from non-boundary nodes. In addition, outer iteration is performed according to the analysis of the injected powers sensitivity by the quantity of the node states to avoid repeated estimate. Test results on IEEE 14-bus, 30-bus and 118-bus system each show the correctness and effectiveness of the algorithm proposed.
Distribution Network Restoration Decision Considering Risk of State Estimation Error in Restoration Process
Time-varying Virtual Inertia and State Estimation of Grid-following Converter Based on Maximum Correntropy Criterion and Polynomial Chaos Kalman Filter
Related Author
YANG Lijun
LIU Jianchao
CAO Liangjing
LU Zhigang
ZHU Kaiyu
LIN Jikeng
HAO Lili
KAN Yizhou
Related Institution
Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province,Yanshan University
Langfang Power Supply Company
College of Electronics and Information Engineering, Tongji University
College of Electrical Engineering & Control Science, Nanjing Tech University
State Grid Electric Power Research Institute (NARI Group Corporation)