Distributed Storage Optimization for Power Availability
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Solution Overview
Problem
Distributed energy storage devices in power supply systems, such as those in photovoltaic systems, face challenges in stability and capacity due to unpredictable energy delivery from renewable sources, leading to inefficiencies and high costs, necessitating effective optimization of their operation.
Innovation Solution
A method is developed to determine and transmit operational control parameters and limits using communications technology to optimize the cost function for distributed storage devices, considering locally available energy and power, and ensuring power availability and extended service life by aggregating and analyzing usage histories and control parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distributed storage devices are deployed to ensure power availability and stability, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent introduces a centralized optimization server as an intermediary that receives data from multiple distributed storage devices, performs complex optimization calculations, and sends back control commands. This mediator handles the computational complexity centrally, allowing individual storage devices to remain simple while achieving system-wide optimization of power availability and reliability.
2Productivity
If multiple applications are served from one storage device, then productivity is improved, but loss of time increases due to optimization requirements
Solution Approach 1:
The system performs preliminary optimization calculations by the centralized server before actual power distribution decisions are needed. The server pre-processes data from multiple storage devices and determines optimal control strategies in advance, so that when multiple applications need to be served simultaneously, the decisions are already made and can be executed immediately without time-consuming real-time calculations.
3Manufacturing precision
If operational control parameters are determined centrally using communications technology, then manufacturing precision is improved for cost function optimization, but loss of information increases due to data transmission
Solution Approach 1:
The patent implements a feedback mechanism where the centralized optimization server receives operational data from distributed storage devices, processes this information to determine optimal control parameters, sends commands back to the devices, and then receives confirmation of execution. This closed-loop feedback system ensures that even if some information is lost during transmission, the system can detect and correct deviations by comparing actual outcomes with expected results, maintaining precise cost function optimization.
Data Source
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AI summary
The invention substantially relates to a method, wherein operational control parameters and/or control limits, which are to be conveyed using communications technology, are determined on the operator side for each of the distributed storage devices in such a way that a specific cost function is minimal for all of the distributed storage devices on the basis of locally measured variables determined at the respective storage device and transmitted to the operator and on the basis of installation-dependent control limits stored locally in each case and which are also transmitted to the operator, and wherein the operational control parameters and/or control limits, which are to be conveyed using communications technology, are transmitted from the operator side to the corresponding distributed storage devices and implemented there. Consideration of the locally limited available energy and power and the boundary conditions resulting from serving multiple applications from one storage device hereby ensures power availability and, by way of example, an optimal overall service life of all distributed storage devices.