Device for optimising the use of renewable energy available
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Solution Overview
Problem
Current solutions for optimizing self-consumption of excess photovoltaic energy with non-modular power loads, such as thermodynamic water heaters, fail to capture the full potential due to lack of anticipation in surplus energy and operating time, leading to suboptimal energy usage and efficiency penalties.
Innovation Solution
An electrical power supply system that integrates a control unit using simulation models, meteorological forecasts, and self-learning algorithms to dynamically calculate activation criteria for thermodynamic water heaters, optimizing energy absorption and minimizing network withdrawal by predicting renewable energy production and consumption patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time surplus data is used to control load activation, then the system responds quickly to available energy, but the lack of anticipation prevents optimal placement of energy absorption
Solution Approach 1:
The system performs preliminary actions by forecasting photovoltaic production and load consumption patterns in advance using simulation models and meteorological data. This allows the control algorithm to determine optimal activation times for the water heater before the actual energy surplus occurs, enabling proactive rather than reactive energy absorption scheduling.
2Productivity
If the load is activated to absorb excess energy, then self-consumption increases, but frequent switching causes anti-short cycle violations and equipment deterioration
Solution Approach 1:
The control algorithm dynamically adjusts the water heater activation strategy by incorporating minimum on/off time constraints and forecasting future energy availability. This dynamic approach allows the system to maintain high self-consumption rates while respecting equipment operational constraints, avoiding frequent switching cycles that would cause deterioration.
3Productivity
If programming is done during the day to synchronize with solar resource, then daytime energy absorption increases, but the load may not coincide with maximum surplus and network withdrawal occurs
Solution Approach 1:
The system uses feedback from forecasted photovoltaic production data and actual consumption patterns to continuously optimize the water heater activation schedule. This feedback mechanism allows the algorithm to adjust programming times to precisely coincide with maximum energy surplus periods, maximizing daytime absorption while minimizing network withdrawal.
4Productivity
If reminders are used to absorb temporary excess energy, then short-term self-consumption improves, but multiple heating penalizes overall system efficiency
Solution Approach 1:
The control algorithm ensures continuous and optimized useful action by scheduling water heater operation to absorb energy in sustained periods rather than multiple fragmented reminders. This continuous operation approach maximizes the utilization of energy surplus while maintaining high overall system efficiency, avoiding the penalties associated with frequent start-stop cycles.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for the optimal activation of thermodynamic water heaters, maximizing self-consumption of photovoltaic energy while minimizing energy withdrawal from the network, thus enhancing the overall efficiency and effectiveness of renewable energy utilization.
Implementation Method 1
at least one local source of renewable energy, in particular formed of at least one photovoltaic panel
Implementation Method 2
thermodynamic water heater
Data Source
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AI summary
The invention relates to a device for optimizing the use of available renewable energy, particularly for optimizing the self-consumption of surplus electricity production from renewable energy sources, characterized in that it comprises means adapted to implement the following steps: 1) Performing an estimation, over a determined time horizon, of renewable electricity production, for example photovoltaic, using a simulation model of the renewable electricity production installation, for example photovoltaic, on the one hand, and weather forecasts on the other hand; 2) Performing an estimation, over a determined time horizon, of off-load consumption driven by self-learning from a rolling consumption history.3) Estimating the operating time of the controlled load based on a rolling history of electricity consumption and forecasts of the outside temperature over a determined time horizon, and where applicable, a model of the thermal power produced by the condenser of the thermodynamic water heater; 4) Dynamically calculating the load activation criteria to minimize the draw on the electrical supply network and maximize the self-consumption of photovoltaic energy.