Predictive Load Control for Renewable Energy Self-Consumption
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Solution Overview
Problem
Renewable energy sources like photovoltaic systems face inefficiencies due to inconsistent energy production linked to meteorological conditions, leading to excess energy being transferred to the grid rather than self-consumed, resulting in increased costs and unnecessary load on distribution networks.
Innovation Solution
A modular system comprising a control logic unit with prediction modules for energy production and consumption, along with a network of actuators for selective energy distribution and diagnostic verification, enabling automated management of electrical loads to maximize self-consumption and reduce grid reliance, integrated with sensors and maintenance tools for predictive diagnostics and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If photovoltaic systems transfer excess energy to the electricity grid, then the distribution network load is reduced, but the system energy self-consumption efficiency deteriorates
Solution Approach 1:
The system performs preliminary actions by predicting energy production and consumption patterns in advance, then proactively scheduling and activating electrical loads before excess energy is generated. This allows the system to consume self-generated energy locally rather than exporting to the grid, thereby improving energy self-consumption efficiency without requiring complex real-time control infrastructure
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring actual energy production from photovoltaic panels, comparing it with predicted consumption patterns, and adjusting load activation schedules accordingly. This closed-loop control enables dynamic optimization of self-consumption while maintaining manageable system complexity through automated decision-making algorithms
2Productivity
If electrical loads are activated during daytime hours to match photovoltaic production, then energy self-consumption is maximized, but the flexibility of load operation deteriorates
Solution Approach 1:
The system applies dynamics by creating flexible, adjustable load schedules that can adapt to varying photovoltaic production conditions. Instead of rigid fixed-time activation, the system dynamically determines optimal load operation windows based on real-time and predicted energy availability, thereby maintaining both high self-consumption rates and operational flexibility through programmable control parameters
Solution Approach 2:
The system utilizes parameter changes by allowing load activation times, durations, and intensities to be adjusted as variable parameters rather than fixed constants. This enables the system to optimize self-consumption by modifying operational parameters according to weather conditions, production forecasts, and consumption patterns, thereby achieving high productivity without sacrificing adaptability
3Quantity of substance
If photovoltaic production is used to meet daytime energy needs, then additional energy source costs are reduced, but the system reliability during low-production periods deteriorates
Solution Approach 1:
The system performs preliminary actions by storing excess energy in accumulators during high-production periods, making it available for later use during low-production periods. This advance energy storage ensures continuous reliable supply while maximizing the utilization of free renewable energy, thereby reducing external energy purchases without compromising reliability
Solution Approach 2:
The system introduces accumulators as intermediary energy storage devices between the photovoltaic production system and the electrical loads. These accumulators act as buffers that decouple production from consumption, allowing the system to maintain reliability during low-production periods by drawing from stored energy while still prioritizing self-consumption of freshly generated energy
Data Source
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AI summary
The present invention concerns a system (S) that can be connected to a production plant (I) equipped with passive energy consumption elements (L) and local energy production devices (D) suitable for producing renewable energy, said system (S) comprising a network of actuators (5), each of which is operationally connected to the passive elements (L) and to a control logic unit (U) capable of controlling the energy consumption of said plant (I) on the basis of a forecast estimate of the energy produced from the local devices (D), said control logic unit (U) comprising a first prediction module (1) of the daily production capable of estimating said renewable energy produced, a second prediction module (2) of the daily consumption capable of predicting the energy consumed by the local devices (D) and/or by said one or more passive elements (L), a predictive diagnostic verification module (3) suitable for verifying malfunctions of the local devices (D), and a planning module (4) capable of activating the loads (L) in a selective manner, wherein said network of actuators (5) is capable of selectively supplying said renewable energy produced by said one or more local devices (D) to said one or more passive elements (L ), and said planning module (4) is configured to plan the selective opening of the loads (L) by sending a signal to said network of actuators (5), in such a way as to selectively open or close said loads (L ) at a predetermined instant in time in such a way as to control the energy consumption of said plant (I) on the basis of said prediction of daily production and consumption.