Smart Switching Device for Decentralized Energy Integration
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Solution Overview
Problem
Existing switching devices for energy connections to energy networks are inefficient in integrating decentralized renewable energy producers and do not effectively manage energy storage options, leading to suboptimal energy feeding and consumption processes.
Innovation Solution
A switching device with an intelligent electricity meter that connects consumers to energy networks, records energy consumption and production, and uses communication modules to automatically compare energy offers from different intermediaries for purchasing, selling, or exchanging energy, incorporating features like self-learning AI, weather forecasts, and market observations to optimize energy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional switching devices are used for energy connections, then basic energy measurement is possible, but integration of decentralized renewable energy producers is inefficient
Solution Approach 1:
The switching device is designed to perform multiple functions: it acts as a smart meter for energy measurement, a switching agency for provider selection, a communication hub for market data exchange, and a control unit for energy flow management. This multi-functionality enables efficient integration of decentralized renewable energy producers while maintaining basic measurement capabilities.
Solution Approach 2:
The device incorporates communication modules that continuously exchange market data, energy prices, and consumption information with external systems. This feedback mechanism enables real-time optimization of energy feeding and consumption processes, allowing the system to adapt to changing market conditions and improve integration efficiency.
2Adaptability or versatility
If basic metering is used, then energy consumption recording is possible, but energy storage management is suboptimal
Solution Approach 1:
The switching device predicts future energy production and consumption based on weather forecasts, market observations, and self-learning AI algorithms. By performing preliminary actions such as pre-charging energy storage systems when electricity prices are low or renewable generation is high, the device optimizes energy storage utilization before actual consumption needs arise.
Solution Approach 2:
The device dynamically adjusts energy storage management strategies based on real-time conditions including weather forecasts, market prices, and consumption patterns. This dynamic adaptation allows the system to optimize energy storage utilization efficiency by switching between different operational modes such as charging, discharging, or idle states.
3Ease of operation
If manual energy provider selection is used, then consumer choice is possible, but energy trading efficiency is reduced
Solution Approach 1:
The switching device autonomously performs energy provider selection and switching without requiring manual consumer intervention. It automatically queries market data, compares energy offers from different intermediaries, and executes switching decisions based on predefined criteria such as price, renewable energy content, or consumption patterns. This self-service capability dramatically improves energy trading efficiency while maintaining consumer choice through configurable selection criteria.
Solution Approach 2:
The device introduces intelligent software agents as intermediaries between consumers and energy providers. These agents automatically negotiate energy contracts, compare offers from multiple intermediaries, and execute transactions on behalf of consumers, thereby improving energy trading efficiency without eliminating consumer autonomy.
4Loss of information
If simple energy counting is used, then basic consumption tracking is possible, but real-time optimization is not achieved
Solution Approach 1:
The switching device integrates multiple data sources including market data from energy exchanges, weather forecasts for renewable generation prediction, and consumption patterns from smart meters. This multi-functional data integration capability enables real-time optimization of energy management by considering a comprehensive set of parameters beyond simple energy counting.
Solution Approach 2:
The device continuously receives feedback from various sources including real-time energy prices, weather conditions, consumption patterns, and grid status. This feedback is processed by self-learning AI algorithms that continuously optimize energy management strategies, enabling real-time adaptation and improvement of energy trading and storage decisions.
Data Source
AI summary
The present invention relates to a switching device for connecting a consumer to an energy network, comprising at least one meter for recording energy consumption and/or energy feed-in to the energy network.To improve the integration of the increasing number of decentralized renewable energy producers, the switching facility has a communication module for data exchange with communication modules of other switching facilities, whereby the exchanged data includes information on the quantity and/or price and/or period and/or energy type of available and/or required energy; a purchasing module that compares sales offers from various switching facilities for the procurement of energy and automatically makes a purchase decision; and/or a sales module that compares purchase offers from various switching facilities for the disposal of energy and automatically makes a sales decision; and/or an exchange module that compares exchange offers from various switching facilities for the exchange of energy and automatically makes an exchange decision.In secondary aspects, the present invention provides a charging station with an interface for charging electric or hybrid cars and with such a switching device, as well as a switching system with several such switching devices.