Hybrid Power Plant Sizing Using Subminute Renewable Profiles
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Solution Overview
Problem
There is a need for an improved solution to optimize the sizing of hybrid power plants, which integrate renewable energy sources and storage technologies, to meet varying electricity, heat, and hydrogen demands effectively.
Innovation Solution
A computer-implemented method that provides renewable power generation profiles, selects hybrid power production and storage technologies based on demand and profiles, and determines the optimal sizing of the hybrid power plant through simulations and dynamic transient analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sizing methods are used for hybrid power plants, then the design process is simpler, but the accuracy and reliability of the sizing optimization is insufficient
Solution Approach 1:
The sizing optimization process is segmented into multiple independent simulation modules: renewable power generation perturbation simulation, component trip simulation, and dynamic transient analysis. Each module focuses on specific aspects of plant behavior under different conditions, allowing comprehensive analysis while maintaining manageable complexity through modular design
Solution Approach 2:
The method performs preliminary simulations of various perturbation scenarios (renewable generation variations, component trips) before finalizing the sizing optimization. By pre-analyzing how the plant responds to different disturbances, the optimization process can identify critical sizing parameters in advance, improving accuracy without proportionally increasing overall complexity
2Measurement precision
If subminute profiles are incorporated into the optimization, then the temporal resolution and accuracy of renewable power generation analysis is improved, but the computational complexity increases
Solution Approach 1:
The optimization methodology transitions from static sizing analysis to dynamic analysis by incorporating subminute temporal resolution profiles. The system dynamically adjusts sizing recommendations based on rapidly varying renewable generation patterns, capturing transient behaviors that static methods miss, thereby improving temporal accuracy while managing computational demands through efficient simulation algorithms
3Reliability
If simulations of renewable power generation perturbations and component trips are performed, then the reliability assessment of the hybrid power plant is improved, but the time and computational resources required increase
Solution Approach 1:
The method performs preliminary simulations of critical failure modes and perturbation scenarios during the sizing optimization phase. By pre-characterizing the plant's response to component trips and renewable generation variations, the system establishes reliability thresholds and sizing requirements before detailed design, improving reliability assessment efficiency
Solution Approach 2:
Rather than simulating all possible failure scenarios exhaustively, the methodology focuses on simulating the most critical perturbations and component trips that have the greatest impact on plant reliability. This targeted simulation approach provides sufficient reliability assessment accuracy while significantly reducing computational time and resources compared to comprehensive scenario analysis
Data Source
AI summary
The disclosure concerns a computer-implemented method for optimizing the sizing of a hybrid power plant. The method comprises providing one or more renewable power generation profiles. The one or more profiles include one or more subminute profiles. The method comprises providing a power demand that includes a demand for electricity. The method further comprises selecting a hybrid power production technology. The selection of the hybrid power production technology is based on the provided one or more profiles and on the power demand. The method further comprises selecting a power storage technology. The selection of the power storage technology is based on the selected hybrid power production technology. The method further comprises determining an optimal sizing of the hybrid power plant. The determination of the optimal sizing is based on the provided one or more profiles, on the power demand, on the selected hybrid power production and storage technology.