Appliance Load Scheduling for Solar-Aligned Energy Use

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Solution Overview

Problem

The periods of electricity consumption of appliances in installations connected to renewable energy sources do not coincide with solar energy production, leading to underutilization and inefficiency in the use of available solar energy.

Innovation Solution

A method involving disaggregation of overall electricity consumption to predict individual appliance consumption profiles, adapting these profiles based on renewable energy production forecasts, and controlling appliances to maximize renewable energy use through a management system that includes fuzzy logic and machine learning algorithms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If appliances operate according to their traditional consumption patterns, then user convenience and appliance functionality are maintained, but renewable energy utilization is suboptimal and energy costs increase

Engineering Contradiction:

Improverenewable energy utilizationVSAvoiduser convenience

Core Design Contradiction:

Use of energy by moving objectVSEase of operation

Solution Approach 1:

The system performs preliminary actions by predicting appliance consumption profiles and renewable energy production in advance, then pre-scheduling appliance operations to coincide with periods of high renewable energy availability. This allows the system to optimize energy utilization without requiring real-time user intervention, maintaining convenience while improving renewable energy usage.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by continuously monitoring actual consumption patterns, comparing them with predictions, and adjusting future scheduling decisions. User preferences and constraints are incorporated as feedback to ensure that optimization does not compromise convenience, creating a closed-loop system that adapts to changing conditions.

Inventive Principle:

Principle #23Feedback

2Loss of energy

If appliance consumption is shifted to maximize renewable energy use, then energy costs are reduced and sustainability is improved, but system complexity and control requirements increase

Engineering Contradiction:

Improveenergy waste reductionVSAvoidcontrol system complexity

Core Design Contradiction:

Loss of energyVSDevice complexity

Solution Approach 1:

The system enables appliances to effectively serve themselves by automatically adjusting their operation schedules based on predicted renewable energy production and consumption patterns. The intelligent agent autonomously makes scheduling decisions without requiring complex user configuration or manual control, reducing the perceived complexity for users while achieving energy optimization goals.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system optimizes energy utilization by dynamically changing operational parameters such as timing, duration, and power levels of appliance operations. By adjusting these parameters based on renewable energy predictions and consumption patterns, the system reduces energy waste without requiring fundamental changes to appliance hardware or complex control infrastructure.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If detailed prediction and optimization of each appliance profile is implemented, then renewable energy utilization is maximized, but computational requirements and data processing needs increase

Engineering Contradiction:

Improveenergy optimization efficiencyVSAvoiddata processing overhead

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system segments the overall energy optimization problem into individual appliance-level predictions and optimizations. By analyzing and scheduling each appliance separately based on its specific consumption patterns and flexibility, the system achieves high optimization efficiency without overwhelming computational requirements, as each segment can be processed independently and efficiently.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20260024997A1Optimising the use of renewable energy

Publication Date: 2026.01.22 SAGEMCOM ENERGY & TELECOM SAS

AI summary

A method for optimising the consumption of an installation includes, carried out before a specified period, implementing a disaggregation method, so as to predict, for each appliance, an expected individual consumption profile, predicting an expected renewable production profile by the renewable energy source, defining first optimised individual consumption profiles for the appliances, making it possible to maximise a use of renewable electrical energy, and the second step of controlling the appliances during the specified period, by using the first optimised individual consumption profiles.