Cooperative Game Theory Voltage Control for Power Systems
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Solution Overview
Problem
The existing security and economy coordinated automatic voltage control methods face challenges in solving large-scale optimization models efficiently, often resulting in no feasible solution due to strict post-contingency security constraints, making real-time online control difficult and inflexible in expanding security constraints.
Innovation Solution
A new method based on cooperative game theory is introduced, which establishes a multi-objective reactive voltage optimizing model, relaxing constraints to solve an economy model and a security model separately, allowing for a coordinated tradeoff between economy and security, and enabling flexible expansion of security constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a static security constrained optimal power flow (SCOPF) model is constructed with strict post-contingency security constraints, then the security requirement is satisfied, but the model scale becomes huge and difficult to solve in real-time online control
Solution Approach 1:
The patent divides the large-scale SCOPF model into multiple smaller sub-models corresponding to different contingencies. Each sub-model handles a specific contingency scenario, allowing independent optimization and solution. This segmentation reduces the computational complexity of each individual model while collectively satisfying all security requirements across multiple contingencies.
Solution Approach 2:
The patent introduces dynamic adjustment mechanisms for control variables based on different contingency scenarios. The control strategy adapts dynamically to specific contingency conditions, allowing the system to optimize reactive power output and transformer tap positions differently for each contingency type, thereby reducing overall model complexity while maintaining security.
2Reliability
If strict post-contingency security constraints are applied, then the security margin is improved, but the feasible region of the optimization model becomes void and no feasible solution can be obtained
Solution Approach 1:
The patent adjusts optimization parameters and constraint boundaries based on different contingency scenarios. By dynamically modifying parameter settings such as reactive power limits, transformer tap ranges, and security margin requirements according to specific contingency conditions, the system maintains feasible solution spaces while still achieving adequate security margins for each scenario.
Solution Approach 2:
The patent applies partial security constraints selectively to different contingencies rather than uniformly applying strict constraints to all scenarios. For contingencies with lower risk or where full constraints would eliminate feasibility, relaxed constraints are applied, allowing feasible solutions to exist while still providing adequate security for critical scenarios.
3Reliability
If the SCOPF model is solved to obtain automatic voltage control instructions, then the security and economy coordination is achieved, but the calculation time exceeds the requirement for online conducting
Solution Approach 1:
The patent segments the optimization problem into independent contingency-specific sub-problems that can be solved in parallel or sequentially with reduced computational burden. Each sub-model focuses on a specific contingency scenario, allowing faster solution times compared to solving one large comprehensive model, while still achieving security-economy coordination for all scenarios.
Solution Approach 2:
The patent performs preliminary classification and prioritization of contingencies before optimization. High-risk contingencies are identified and handled with full security constraints, while lower-risk scenarios use simplified models or relaxed constraints. This preliminary action allows the system to focus computational resources on critical scenarios, reducing overall calculation time while maintaining security-economy coordination for essential cases.
Data Source
AI summary
A security and economy coordinated automatic voltage control method based on a cooperative game theory is provided. The method includes: establishing a multi-objective reactive voltage optimizing model of a power system; resolving the multi-objective reactive voltage optimizing model into an economy model and a security model; solving the economy model and the security model based on the cooperative game theory to obtain the automatic voltage control instruction; and performing an automatic voltage control for the power system according to the automatic voltage control instruction.