Energy Optimizer Sensitivity Analysis for Transparent Site Management
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Solution Overview
Problem
Existing energy management systems for complex sites with multiple energy streams struggle to assess the impact of various conditions and parameters on overall energy management due to their complexity and interplay of entities.
Innovation Solution
A system comprising an energy optimizer and a data variator that determines optimization goals using an optimization algorithm, performs data sensitivity analysis, and allows for informed changes to the optimization algorithm to improve energy management transparency and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an energy management system is used to control power flows in complex energy networks, then energy management capability is improved, but transparency and comprehensibility of parameter impacts deteriorate
Solution Approach 1:
The system implements sensitivity analysis that provides feedback information about how changes in input parameters affect optimization outputs. This feedback mechanism quantifies the impact of individual parameters (e.g., weather conditions, load demands, energy prices) on energy management decisions, thereby restoring transparency without compromising the sophisticated control capabilities of the energy management system.
Solution Approach 2:
The sensitivity analysis module acts as an intermediary between the complex energy management system and decision-makers. It translates the complex interplay of multiple energy streams and parameters into comprehensible sensitivity metrics that reveal which parameters have the most significant impact on optimization outcomes, enabling informed decision-making without requiring understanding of the entire complex system.
2Adaptability or versatility
If the complexity of energy networks with multiple energy streams is increased, then energy management flexibility is improved, but assessability of parameter impacts deteriorates
Solution Approach 1:
The sensitivity analysis provides systematic feedback that quantifies the impact of each parameter on optimization outputs. This feedback mechanism enables assessment of parameter impacts even in highly flexible energy networks with multiple energy streams, by measuring the sensitivity of outputs to changes in individual inputs while accounting for the complex interplay between different energy carriers.
Solution Approach 2:
The system employs parameter sensitivity analysis that systematically varies input parameters (such as weather conditions, load demands, energy prices) to measure their impact on optimization outputs. This approach enables assessability of parameter impacts by observing how changes in specific parameters propagate through the complex energy network and affect management decisions.
Data Source
AI summary
A system for optimizing an energy management of a site, comprising: an energy optimizer, wherein the energy optimizer determines one or more optimization goals based on an optimization algorithm, a data variator adapted to provide at least one first energy data input and at least one second energy data input, different to the first energy data input, to the energy optimizer, wherein the energy optimizer receives the first and second energy data inputs from the data variator, and to determine, based the first and second energy data inputs, respective at least one first and second energy data outputs via the optimization algorithm, wherein a data sensitivity of the energy optimizer is determined with respect to the first and second energy data inputs and the first and second energy data outputs.