Microgrid Control Platform Integrating Real and Simulated Data
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Solution Overview
Problem
Existing microgrid control systems and simulation methods lack the integration of real and virtual data to effectively predict and adapt to future network behavior, leading to suboptimal operation and potential implementation of non-viable solutions due to differences between simulated and actual operations.
Innovation Solution
A hybrid platform that integrates software and hardware components to simulate microgrid operations, incorporating real and simulated elements, allowing for data-driven scheduling and validation of results through emulation and fault signalization, ensuring realistic interaction with external facilities and networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If microgrid control systems use predefined algorithms to manage electrical network operation, then the system can regulate network behavior according to predefined parameters, but the system cannot effectively predict and adapt to future network behavior
Solution Approach 1:
The system performs preliminary simulation of future network scenarios using computational models before actual operation occurs. By pre-calculating optimal control strategies for various future conditions, the system can adapt to changing network behavior without requiring complex real-time decision-making algorithms.
Solution Approach 2:
The invention creates virtual copies of the microgrid system through computational modeling and simulation. These digital twins replicate the physical system's behavior, allowing the control system to test and optimize strategies in the virtual environment before applying them to the real system, thereby improving adaptability without proportionally increasing physical system complexity.
2Reliability
If simulation systems are used to model and predict microgrid behavior, then operator intervention can regulate the microgrid in later phases, but the simulated solutions may not be viable when implemented in the real network
Solution Approach 1:
The system establishes continuous feedback loops between the simulation model and the physical microgrid. Sensor data from the real system feeds into the simulation model, which then compares simulated outcomes with actual measurements. This feedback mechanism allows the system to identify and correct discrepancies between simulation and reality, ensuring that simulated solutions remain viable when implemented.
Solution Approach 2:
The simulation model is designed to be dynamic and adaptive, continuously updating its parameters based on real-time data from the physical system. This dynamic adjustment allows the simulation to accurately reflect changing conditions in the real microgrid, improving the reliability of simulated solutions while managing complexity through adaptive rather than static modeling approaches.
3Productivity
If real sensors and computational models are integrated to maximize an objective function, then the microgrid operation can be optimized, but the system requires scheduling and coordination of multiple resources
Solution Approach 1:
The control system segments the microgrid into distinct functional components (generation elements, consumption elements, storage means) and applies separate computational models to each segment. This modular approach allows the system to optimize each component independently while coordinating them through the objective function maximization, thereby achieving overall optimization without requiring monolithic complex scheduling of all resources simultaneously.
Data Source
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AI summary
The present invention belongs to the field of electrical microgrids optimization and management, which include consuming and generation units, and possibly local generators and equipment suitable for energy storage. The present invention consists therefore on a method for the control of electrical microgrids, which, integrating real data from connected equipment - such as energy generation elements (1) and energy consumption elements (3) - associates that real data with data from simulated elements stored in database (12), aiming at optimizing the microgrid operation, through calculation in computational means (9), scheduling the available resources by actuation means (10). The present invention further comprises, in another innovative facet, the ability of emulating the simulation data results, through means for emulation of load and generation of electrical energy (11). It is also a part of the present invention a system that implements the referred method, in its diverse variants.