Efficiency-Controlled Energy Flow Management for Photovoltaic Storage
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Solution Overview
Problem
Current photovoltaic storage systems lack efficiency-controlled operational management, failing to account for system inefficiencies and changes in the power grid or market conditions, leading to suboptimal energy flow and increased power losses.
Innovation Solution
A method for efficiency-controlled operational management of photovoltaic storage systems that reads current characteristic data, determines optimal energy flows using a power requirement parameter, and selects the most efficient energy flow to maximize energy efficiency, incorporating energy storage and grid connection to balance supply and demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If standard operating procedures are used without efficiency control, then the system operation is simple, but power losses increase and energy efficiency deteriorates
Solution Approach 1:
The energy management system continuously monitors system inefficiencies and operational parameters, using feedback loops to adjust energy flow decisions dynamically. This allows the system to reduce power losses by adapting to real-time conditions while maintaining manageable complexity through automated control algorithms.
Solution Approach 2:
The patent implements dynamic operational management that adapts to changing system conditions, power grid status, and market prices. The energy management system transitions from static standard procedures to dynamic decision-making that optimizes energy efficiency while handling complexity through structured control methods.
2Productivity
If efficiency-controlled operational management is implemented, then energy efficiency improves and power losses reduce, but system complexity increases
Solution Approach 1:
The energy management system acts as an intermediary layer between the photovoltaic storage system and the power grid, centralizing complex decision-making logic. This mediator handles efficiency optimizations, grid interaction strategies, and market price considerations, allowing the underlying hardware to remain relatively simple while achieving high energy efficiency through intelligent control.
3Adaptability or versatility
If the system adapts to changes in power grid and market conditions, then operational optimality improves, but control complexity increases
Solution Approach 1:
The system adapts to changing grid and market conditions by dynamically adjusting operational parameters such as charge/discharge rates, energy flow directions, and timing decisions. The energy management system monitors external conditions and modifies internal control parameters accordingly, achieving high adaptability through parameter optimization rather than structural complexity.
Data Source
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AI summary
The invention relates to a method (1000) for efficiency-controlled operational management for a storage system (104) for a photovoltaic system (100), wherein the photovoltaic system (100) comprises the following as components: at least one solar generator (102), the storage system (104), an energy management system (116), a household connection (106), and a grid connection (108). The method (1000) comprises a step of reading in (1010) current characteristic data of the photovoltaic system (100), a step of determining (1020) a plurality of possible energy flows (114) between the components of the photovoltaic system (100) for the current time interval by using the current characteristic data and determining a respective expected value for each energy flow of the plurality of possible energy flows by using a power demand parameter and the plurality of possible energy flows (114), and a step of selecting (1030) an energy flow (114) from the plurality of possible energy flows (114) for the current time interval, wherein the expected value is maximal for the current time interval, wherein the energy flow (114) determines the efficiency-controlled operational management. The current characteristic data represent production values and/or consumption values and/or a state of charge (122) of the storage system (104) in a current time interval.