Renewable Asset Dispatch Co-Optimization for Accurate Output Simulation
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Solution Overview
Problem
Predictions of renewable energy system output are often inaccurate and inefficient due to separate modeling of different asset types, neglecting synergies and real-world power delivery considerations, leading to sub-optimal dispatch and design of renewable energy systems.
Innovation Solution
A computing system that co-optimizes the dispatch of multiple renewable energy assets, including PV arrays, wind turbines, and energy storage devices, to simulate and predict their combined output, taking into account environmental factors and power delivery shapes, thereby optimizing dispatch and design for efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If separate modeling of different asset types is used, then device complexity is reduced, but measurement precision of renewable energy system output deteriorates
Solution Approach 1:
The patent combines separate models of different renewable energy asset types (PV arrays, wind turbines, energy storage devices) into a unified co-optimized dispatch model. This integration allows the system to capture synergies between assets and account for real-world power delivery considerations, thereby improving output prediction accuracy without proportionally increasing complexity.
Solution Approach 2:
The patent creates a multi-functional modeling framework that simultaneously handles multiple asset types and optimization objectives. The unified model serves multiple purposes: predicting output, optimizing dispatch, and evaluating system design, thereby improving measurement precision while managing complexity through a versatile modeling approach.
2Ease of operation
If separate modeling of different asset types is used, then ease of operation is improved, but productivity of renewable energy system deteriorates
Solution Approach 1:
By merging separate asset models into a co-optimized dispatch framework, the system captures synergies between different renewable energy assets. This integration enables more efficient system operation and higher productivity, as the unified model can coordinate assets to maximize overall performance rather than optimizing each asset in isolation.
3Device complexity
If separate modeling of different asset types is used, then device complexity is reduced, but reliability of renewable energy system deteriorates
Solution Approach 1:
The unified co-optimized dispatch model integrates multiple asset types to capture system-wide synergies and interdependencies. This holistic approach improves reliability by accounting for real-world power delivery considerations and enabling coordinated operation, which separate models cannot achieve.
Solution Approach 2:
The patent implements feedback mechanisms within the co-optimized dispatch model, where the system continuously evaluates performance and adjusts dispatch decisions. This feedback loop enhances reliability by enabling real-time optimization and adaptation to changing conditions, ensuring the system meets target outputs consistently.
Data Source
AI summary
A method may include receiving first parameters of a first renewable energy asset of a first type to be simulated, wherein the first parameters include a first set of parameters within a first predetermined range, receiving second parameters of a second renewable energy asset of a second type to be simulated, wherein the second parameters include a second set of parameters within a second predetermined range, correlating the sets of parameters into a plurality of simulated REPPs, for each simulated REPP of the plurality of simulated REPPs, calculating output parameters by co-optimizing dispatch of the first renewable energy asset and the second renewable energy asset, and displaying a graph including a visual representation of one or more output parameters of the output parameters of each simulated REPP of the plurality of simulated REPPs.