Reactive Resource Switching for Multi-Interval Grid Voltage Control
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Solution Overview
Problem
Existing power grid systems struggle to maintain voltage at key points within acceptable limits, especially with the integration of renewable energy sources that provide less controllable reactive power support, leading to inefficiencies and reliability issues.
Innovation Solution
A computer-implemented method using mixed integer linear programming (MILP) optimization and a fallback rule-based approach to determine optimal reactive resource switching in the power grid, coupled with real-time monitoring and decision-making processes to maintain voltage within limits, even when MILP optimization fails.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If renewable power sources (wind and solar) are introduced to reduce carbon emission, then environmental sustainability is improved, but voltage control capability deteriorates because renewable power provides less controllable reactive power support
Solution Approach 1:
The patent introduces a computer-based control system with MILP optimization as an intermediary between renewable power sources and the power grid. This mediator coordinates reactive resource switching to compensate for the lack of reactive power support from renewables, maintaining voltage control capability while preserving the benefit of reduced carbon emissions.
Solution Approach 2:
The system dynamically changes the switching state parameters of reactive resources (capacitors, reactors, SVCs, STATCOMs) based on real-time voltage conditions and predictive analytics. By adjusting these binary switching parameters optimally across multiple time intervals, the system compensates for the variable reactive power output from renewable sources.
2Reliability
If reactive resources are switched frequently to maintain voltage within acceptable limits, then voltage stability is improved, but system complexity and operational cost increase
Solution Approach 1:
The system performs preliminary action by predicting future voltage conditions and determining optimal reactive resource switching schedules in advance using MILP optimization. By planning switching actions for multiple future time intervals beforehand, the system avoids frequent ad-hoc switching operations, reducing operational complexity while maintaining voltage stability.
Solution Approach 2:
The system implements feedback through iterative re-optimization where actual voltage measurements and system responses are fed back into the MILP model. This closed-loop feedback mechanism adjusts future switching schedules based on actual system behavior, optimizing voltage control while minimizing unnecessary switching operations.
Data Source
AI summary
A computer method and system determine the reactive resources to be switched to keep voltage at key points in a power grid within their allowed high and low limits. The method periodically runs power flow for each of plural time intervals from a current time interval to a future time interval. Asynchronously and in concert with running the power flow, the method periodically formulates and solves a representative mixed integer linear programming (MILP) optimization problem for maintaining voltage within limits of interest, resulting in an optimal reactive resource switching solution. Based on the optimal reactive resource switching solution, the method provides at least one output toward switching in/out reactive resources of a subject power grid. The method and system achieve real-time, multi-interval optimal reactive power dispatching.