Accurate system state information under various
operation conditions is a prerequisite for power grid monitoring
and efficient control. To achieve that goal, a new multi-scale
state estimation framework is proposed, paving the way for
the development of next generation of energy management
system (EMS). The developed framework consists of three key
components, namely the static state estimation (SSE) module,
the dynamic state estimation (DSE) module, the interfaces and
switching logics between the two modules. Specifically, the
singular spectrum analysis (SSA)-based change point detection
approach is developed to monitor the system continuously. If no
event is detected by the SSA, the robust SSE using both SCADA
and PMU measurements is executed. Otherwise, the event is
declared and the results from SSE are used to derive the initial
condition for DSE. During the transient process, only PMU-based
DSE is executed for system monitoring and it will be terminated
when SSA does not detect any change point of the system.
After that, the DSE results are forwarded for SSE initialization
and bus voltage magnitude and angle estimations. Simulation
results carried out on the IEEE 39-bus system demonstrate the
effectiveness and benefits of the proposed framework.
Revised: March 16, 2020 |
Published: August 4, 2019
Citation
Zhao J., S. Wang, N. Zhou, R. Huang, L. Mili, and Z. Huang. 2019.A New Multi-Scale State Estimation Framework for the Next Generation of Power Grid EMS. In IEEE Power & Energy Society General Meeting (PESGM 2019), August 4-8, 2019. Piscataway, New Jersey:IEEE.PNNL-SA-139400.doi:10.1109/PESGM40551.2019.8973858