Microgrid Control With Rule-Based Dispatch and Site Optimization
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Solution Overview
Problem
Current microgrid controllers do not yield optimal results, are computationally expensive, and suffer from convergence issues, with limited customizability to specific sites, and do not effectively manage resource consumption, reliability, cost, and carbon emissions.
Innovation Solution
A system that combines rule-based controls with a site-specific optimizer to determine power sources and levels, using a set of rules independent of the site to provide initial power levels, and an optimizer to optimize these levels based on site-specific attributes like resource consumption, reliability, and carbon emissions, ensuring a usable result within a specified time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a microgrid controller uses rule-based controls, then it provides simplicity and fast computation, but it does not yield optimal results and has limited customizability to specific sites
Solution Approach 1:
The control system is segmented into two distinct components: a rule-based controller that provides fast, simple computations, and an optimizer that delivers optimal, customized solutions. Each component operates independently but complements the other, allowing the system to leverage both speed and adaptability without requiring one to sacrifice the other.
2Adaptability or versatility
If a microgrid controller uses an optimizer, then it yields optimal results and can be customized to specific sites, but it is computationally expensive and suffers from convergence issues
Solution Approach 1:
The rule-based controller performs preliminary control actions to maintain stable and reliable microgrid operation. This preliminary control ensures that the system remains within acceptable operating parameters, reducing the burden on the optimizer and allowing it to focus on optimization without causing convergence issues or computational overload.
3Ease of operation
If current microgrid controllers are used, then they provide basic control functionality, but they do not effectively manage resource consumption, reliability, cost, and carbon emissions
Solution Approach 1:
The optimizer continuously receives feedback from the microgrid system regarding resource consumption, reliability metrics, cost parameters, and carbon emissions. Based on this feedback, the optimizer adjusts control parameters to improve these performance metrics while maintaining ease of operation through the rule-based controller's stable baseline operation.
Data Source
AI summary
The system obtains a load required by a power grid and specifications of power sources. The specification indicates an amount of power that the power source can provide. The system obtains rules indicating a first power source based on the load, where the rules indicate a first power level of the first power source. The system provides the first power and level to an optimizer to determine a second power source and level by optimizing operation of the power source. The system obtains a time threshold and, based on the threshold, obtains the second power source and level from the optimizer. The system determines whether the first power source and level or the second power source and level are closer to a desired operation. Based on the determination, the system operates the first power source at the first power level or the second power source at the second power level.