Energy Aggregator Response Profile Construction
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Solution Overview
Problem
Energy distribution networks face challenges such as unpredictable responses from energy facilities to control signals, leading to issues like increased energy consumption after reduction commands, congestion on transmission lines, frequency and voltage deviations, and the need for optimizing energy management to prevent safety problems and maximize revenue.
Innovation Solution
An automatic method that disaggregates energy demand by constructing response profiles for each energy facility based on instantaneous and historical energy state variations, technical constraints, and previous response profiles, and sends control signals for energy production, consumption, or storage to satisfy predefined objectives, such as correcting safety issues or maximizing revenue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If control signals are sent to energy facilities to reduce energy consumption, then energy consumption is reduced, but energy consumption increases again shortly after the command is received
Solution Approach 1:
The system performs preliminary actions by sending control signals in advance and using historical response data to predict future behavior. The aggregator constructs response profiles beforehand that account for rebound effects, allowing it to pre-compensate for expected consumption increases and maintain reliable energy management despite unpredictable facility responses.
2Productivity
If the aggregator sends control signals to energy facilities, then energy demand can be satisfied, but the response of energy facilities is not known and depends on facility behavior or client goodwill
Solution Approach 1:
The system implements feedback by collecting historical response data from energy facilities and clients, analyzing actual responses to previous control signals, and using this information to construct more accurate response profiles. This feedback loop transforms uncertain facility behavior into predictable patterns, enabling the aggregator to reliably satisfy energy demand while accounting for individual facility and client characteristics.
3Productivity
If energy distribution networks operate at high capacity, then energy supply meets demand, but congestion occurs on transmission lines
Solution Approach 1:
The aggregator performs preliminary actions by predicting energy production and consumption patterns using constructed response profiles, and by proactively adjusting control signals to prevent transmission congestion before it occurs. This allows the system to maintain high energy supply capacity while avoiding harmful congestion effects on transmission lines through advance planning and coordination.
4Ease of operation
If the aggregator manually manages energy facilities, then control can be exercised over production and consumption, but automatic and effective action cannot be issued to correct safety problems
Solution Approach 1:
The system enables self-service by implementing automatic construction of response profiles and generation of control signals based on historical data and predefined objectives. The aggregator automatically issues safety-critical commands to energy facilities without manual intervention, while the system learns from past responses to improve its automated decision-making, combining the benefits of automation with adaptive intelligence.
Data Source
AI summary
A method of managing energy supply in which an aggregator receives an energy demand from at least one operator of an energy distribution network and sends instructions to a plurality of energy facilities suitable for providing energy in order to satisfy the demand, the method being characterized by the following steps:each energy facility transmits to the aggregator a description of instantaneous variations of the energy state and technical constraints linked to its operation in order to satisfy the demand; andthe aggregator defines in automatic manner for each energy facility a response profile for the demand as a function of the description by taking into account non-linear responses and energy state history data from each energy facility, and transmits the response profile of the energy distribution network to the operator, and transmits a set of control signals to each energy facility in order to satisfy the demand.