Flexible Constraint Optimization for Electric Power Systems
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Solution Overview
Problem
Modern electric power systems face challenges in optimizing economic efficiency, safety, and reliability due to rigid constraints that are not flexible enough, making it difficult to find the optimal operation point, especially with the integration of renewable energy sources and complex grid structures.
Innovation Solution
A method for optimizing flexible constraints in electric power systems is introduced, which includes expressing the total power generation cost as a sum of quadratic functions, selecting a multi-dimensional flexible optimization model, and performing load flow calculations to achieve comprehensive optimization of economic efficiency, safety, and reliability, with the option to switch to an optimal load curtailment model if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional rigid constraints are used to guarantee safety and reliability, then system reliability is improved, but system adaptability deteriorates due to conservative boundary settings
Solution Approach 1:
The patent transforms rigid constraints into dynamic flexible constraints by introducing flexibility indices (δf, δLk, δGi, δVk, δFl) that allow constraint boundaries to adapt dynamically. The optimization model adjusts constraint tightness based on system state and operational requirements, enabling the system to maintain reliability while adapting to varying conditions through programmable, adjustable constraint parameters.
Solution Approach 2:
The patent changes the parameter representation of constraints from fixed values to flexible ranges defined by flexibility indices. By parameterizing constraints with adjustable flexibility factors (e.g., PGi ≤ PGimax(1+δGi)), the system can modify constraint characteristics without structural changes, resolving the contradiction between reliable operation and adaptive response to different scenarios.
2Productivity
If comprehensive optimization of economic efficiency, safety, and reliability is pursued, then system economic efficiency is improved, but optimization complexity increases
Solution Approach 1:
The patent segments the comprehensive optimization problem into distinct flexible constraint modules (power generation cost flexibility, load flexibility, generator output flexibility, voltage flexibility, load flow flexibility). Each module handles a specific aspect with its own flexibility index, making the complex multi-objective optimization manageable through structured decomposition while maintaining comprehensive optimization capability.
Solution Approach 2:
The patent creates a universal flexible optimization framework that simultaneously addresses economic efficiency, safety, and reliability through a single multi-dimensional model. The unified formulation with flexibility indices serves multiple optimization objectives at once, reducing overall system complexity compared to separate specialized models while achieving comprehensive optimization.
3Adaptability or versatility
If flexible optimization models are implemented, then constraint adaptability is improved, but computational burden increases
Solution Approach 1:
The patent implements flexible constraints selectively through flexibility indices that can be adjusted based on computational resource availability and system priorities. Not all flexibility dimensions need to be fully activated simultaneously - the system can apply partial flexibility to critical constraints while maintaining rigid constraints elsewhere, reducing computational burden while preserving necessary adaptability.
Data Source
AI summary
A method for optimizing the flexible constraints of an electric power system includes a step S1 of expressing the total power generation cost of the electric power system by using the sum of quadratic functions of active power outputs of all generator sets in the system and constructing an objective function, a step S2 of selecting a multi-dimensional flexible optimization model or a flexible power generation cost optimization model according to the practical situation of the electric power system and the practical purpose of optimization, a step S3 of determining the operating conditions of the electric power system, and a step S4 of carrying out load flow calculation.


