Cascade Hydropower Scheduling With Relative Target Proximity
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Solution Overview
Problem
Multi-objective optimal operation of cascade hydropower plants is complex due to high-dimensional, strongly coupled, non-linear optimization problems, and existing methods heavily rely on subjective factors, failing to fully reflect decision-making benefits from multiple objectives.
Innovation Solution
A method based on relative target proximity and marginal analysis principle, transforming multi-objective optimization into a single-objective problem using genetic algorithms and economic marginal analysis to determine optimal solutions under different weight coefficients, reducing subjective inference in decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-objective optimization algorithm is used to obtain Pareto solution set, then the physical meaning of the multi-objective problem is preserved and non-inferior solution set is obtained, but the final decision still depends on subjective orientation or target preference of dispatcher
Solution Approach 1:
The patent transforms the multi-objective optimization problem into a single-objective problem by changing the parameter representation from multiple objective functions to a unified objective function based on relative target proximity. This is achieved by normalizing multiple objectives to a common scale and combining them with weight coefficients, thereby eliminating the need for subjective decision-making while preserving the essential characteristics of the original multi-objective problem
Solution Approach 2:
The patent introduces an intermediary mechanism - the relative target proximity metric - that mediates between multiple objectives and provides an objective basis for decision-making. This intermediary transforms the complex multi-objective evaluation into a single measurable quantity that reflects the综合 benefit of multiple objectives without requiring subjective judgment
2Ease of manufacture
If objective weight method is used to transform multi-objective problem into single-objective problem, then the solution procedure is simple and easy to implement, but the solution heavily depends on subjective factors such as determination of objective weight coefficient
Solution Approach 1:
The patent changes the parameter determination method from subjective weight assignment to objective weight derivation based on relative target proximity. The weight coefficients are determined through normalization of objectives and mathematical transformation rather than subjective judgment, maintaining simplicity while reducing subjective influence
Solution Approach 2:
The optimization system determines its own weight coefficients through the relative target proximity method without requiring external subjective input. The system self-adjusts the weights based on the normalized objectives and their relative importance, making the decision-making process autonomous and objective
3Reliability
If multi-objective optimal operation is performed under highly coupled constraints of temporal-spatial, then comprehensive utilization requirements are met, but efficient solution techniques are required to take account of computational efficiency and accuracy
Solution Approach 1:
The patent transforms the complex multi-objective optimization problem with temporal-spatial constraints into a single-objective problem with changed parameters. By normalizing multiple objectives and combining them into a unified objective function, the computational complexity is reduced while still meeting comprehensive utilization requirements
Solution Approach 2:
The patent segments the complex optimization problem into manageable components: (1) normalization of individual objectives, (2) calculation of relative target proximity, (3) optimization with weight coefficients, and (4) extraction of optimal solutions. This segmentation makes the problem tractable while maintaining comprehensive utilization requirements
Data Source
AI summary
The invention relates to the field of hydropower scheduling, and relates to a method for multi-objective optimal operations of cascade hydropower plants based on relative target proximity and marginal analysis principle. The invention constructs an optimization model with relative target proximity by introducing positive and negative ideal points of objectives so that a multi-objective optimization is efficiently handled. A strategy for processing complex operation constraints is proposed and coupled with genetic algorithm to solve the model. Thus, optimal solution sets under different weight coefficients of objectives can be determined. Following this, marginal benefit and marginal cost are introduced to represent a relationship between multiple objective values and corresponding weight coefficients. According to principle of profit maximization in economics, a marginal analysis of objective weight coefficient is finally made to determine benefit-dominant area, cost-dominant area and equilibrium area, and there by obtaining a basis of multi-objective decision-making.