Topology Error Estimation for Electric Power System State Accuracy
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Solution Overview
Problem
The complexity of electric power systems in regulated market environments makes it challenging to accurately manage and control generation and transmission resources, as errors in network topology models lead to inaccuracies in state estimations, affecting the optimization and reliability of power system operations.
Innovation Solution
The method involves generating a first network topology model, performing state estimation, and then generating a topology error estimation using binary variables corresponding to telemetered or non-telemetered switching devices, which allows for the creation of a second network topology model and state estimation, enabling optimized power generation schedules and transmission line configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a first network topology model is generated for state estimation, then the power system can be managed and controlled, but topology errors in the model lead to inaccuracies in state estimation
Solution Approach 1:
The patent implements feedback by generating topology error estimations based on the first state estimation results. The energy management system continuously monitors the accuracy of the topology model by comparing expected versus actual system states, and uses this feedback to generate corrections that improve subsequent state estimations.
Solution Approach 2:
The patent applies preliminary action by generating topology error estimations before final state estimation corrections are applied. The system proactively identifies potential topology errors and prepares correction data in advance, which is then used to refine the network topology model before performing optimized power generation scheduling and transmission line configuration.
2Measurement precision
If topology error estimation is performed using binary variables for switching devices, then state estimation accuracy is improved, but the computational complexity increases
Solution Approach 1:
The patent changes parameters by introducing binary variables to represent switching device states (open/closed) in the topology error estimation process. This parameter transformation allows the system to model discrete switching states mathematically, enabling more precise state estimation through binary optimization techniques while maintaining computational tractability.
3Productivity
If a second network topology model is generated based on topology error estimation, then optimization of power generation and transmission is improved, but the system requires more processing steps
Solution Approach 1:
The patent applies preliminary action by generating the second network topology model with corrected topology errors before performing optimized power generation scheduling and transmission line configuration. This preliminary correction ensures that subsequent optimization operations are based on accurate system state data, improving overall operational efficiency.
Solution Approach 2:
The system uses feedback from the first state estimation to identify topology errors and generate corrections for the second topology model. This feedback loop ensures that the additional processing step of generating a second model is justified by the improvement in estimation accuracy, which directly enhances power system operation efficiency.
Data Source
AI summary
An electric power system includes an energy management system configured to control a generated power output level of one or more electric generator resources, and a configuration of two or more high-voltage transmission lines, for efficient operation based, at least in part, on a topology error estimation using binary values corresponding to switch statuses. Increased accuracy of network topology estimates facilitates improved state estimation, which in turn enables production of more highly optimized control of electric generator resources and configuration of high-voltage transmission lines.