Solar-Storage Power Plant Assessment Using Daily Schedule Optimization
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Solution Overview
Problem
There is a need for an improved solution to assess the performance of power plants comprising a solar field system and a storage system, as existing methods lack efficiency and objectivity in evaluating performance indicators such as power quality and CO2 emissions.
Innovation Solution
A computer-implemented method that provides a systematic approach to assess the performance of power plants by optimizing schedules for each architecture, computing daily and yearly indicators, and determining the operability of different architectures based on these indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a comprehensive performance assessment method is implemented for power plants, then the objectivity and determinism of performance evaluation is improved, but the computational complexity and time required for assessment increases
Solution Approach 1:
The performance assessment is divided into separate modular components: a solar field system module, a storage system module, and a combined performance assessment module. Each module independently processes specific aspects of power plant operation, allowing complex calculations to be broken down into manageable segments that can be executed systematically without overwhelming computational burden.
Solution Approach 2:
The system pre-defines multiple architecture configurations and performance indicator frameworks before actual assessment begins. By preparing assessment templates, indicator structures, and calculation methodologies in advance, the system eliminates the need for complex real-time decision-making during execution, thereby reducing computational complexity while maintaining assessment objectivity.
2Measurement precision
If detailed daily optimization and indicator computation is performed for each day, then the accuracy of yearly performance indicators is improved, but the computational time and processing requirements increase
Solution Approach 1:
The yearly assessment period is segmented into individual daily optimization problems. Each day is processed independently with its own optimization schedule and indicator computation, allowing parallel processing and efficient resource utilization. This segmentation enables accurate daily tracking that aggregates to precise yearly indicators without requiring monolithic computational processing.
Solution Approach 2:
The system performs optimization and indicator computation periodically for each day rather than continuously throughout the year. By establishing regular daily assessment cycles with standardized procedures, the system achieves comprehensive yearly accuracy through consistent periodic measurements rather than requiring constant computational intervention.
3Reliability
If multiple architecture configurations are assessed iteratively to determine operability, then the reliability of power plant design evaluation is improved, but the number of computations and resources required increases
Solution Approach 1:
The assessment system is designed with universal applicability across multiple architecture configurations. A single standardized assessment framework and indicator set can evaluate different solar field systems, storage systems, and their combinations without requiring configuration-specific customization. This multi-functionality allows reliable comparison of various designs using the same proven methodology, maintaining reliability while improving efficiency through standardized processes.
Solution Approach 2:
The system uses representative sample architectures and typical operational scenarios as templates for broader assessment. By evaluating standardized model configurations that capture essential design variations, the system can reliably infer performance characteristics for similar architectures without exhaustively analyzing every possible configuration, thereby maintaining evaluation reliability while reducing computational burden.
Data Source
AI summary
The disclosure notably relates to a computer-implemented method for assessing performance of a power plant. The power plant comprises a solar field system and a storage system. The method comprises providing one or more sets of inputs. Each set of inputs represents a respective architecture of the power plant. The method further comprises computing, for each set of inputs, by a computer system and based on the set of inputs, output data including one or more yearly indicators. For each set of inputs, the computing comprises, for each day of a set of days, optimizing a schedule for the power plant and computing daily indicators for the day. The computing further comprises, for each set of inputs, determining the one or more yearly indicators based on the computed daily indicators. The method forms an improved solution for assessing performance of a power plant.