Genetic Algorithm Energy Management for nZEB

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Solution Overview

Problem

Existing energy management systems for nearly zero energy buildings (nZEBs) fail to optimally balance energy saving, resident comfort, and maximum exploitation of renewable energy sources, often increasing grid energy absorption and electricity bills while compromising comfort.

Innovation Solution

A genetic algorithm-based energy management system (EMS) that schedules programmable appliances, regulates controllable loads, and optimizes battery storage system operations, considering real-time electricity prices, weather forecasts, and user preferences to minimize grid energy consumption and maximize renewable energy utilization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If the energy management system considers only the comfort level of the residents, then the electric energy absorbed by the grid may be increased, but the energy autonomy level of the nZEB decreases and electricity bills increase

Engineering Contradiction:

Improveresident comfortVSAvoidgrid energy absorption

Core Design Contradiction:

Ease of operationVSUse of energy by moving object

Solution Approach 1:

The energy management system dynamically adjusts the operation of programmable appliances and controllable loads based on real-time conditions including renewable energy generation, grid pricing, and resident comfort preferences. The system transitions between different operational modes (e.g., comfort mode, economy mode, empty house mode) to balance comfort and energy absorption dynamically rather than using fixed schedules.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system continuously monitors multiple parameters including state-of-charge of battery storage, real-time electricity prices, weather forecasts, and actual energy generation from renewable sources. This feedback loop enables the system to adjust appliance scheduling and load control strategies in real-time, optimizing the balance between resident comfort and grid energy absorption based on current conditions.

Inventive Principle:

Principle #23Feedback

2Use of energy by moving object

If the energy management system aims only the reduction of the electric energy absorbed by the grid, then the residents' comfort may be adversely affected

Engineering Contradiction:

Improvegrid energy absorptionVSAvoidresident comfort

Core Design Contradiction:

Use of energy by moving objectVSEase of operation

Solution Approach 1:

The system performs preliminary actions by pre-cooling or pre-heating spaces and pre-charging battery storage during periods of high renewable energy generation or low grid pricing, before the actual need arises. This allows the system to reduce grid energy absorption during peak demand periods while maintaining comfort levels, as the thermal mass and battery are already prepared to meet the load.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes operational parameters of controllable loads such as temperature setpoints, operating schedules, and power levels to optimize energy usage. By adjusting these parameters dynamically based on renewable generation availability and grid pricing, the system can reduce grid absorption while maintaining acceptable comfort ranges rather than fixed comfort levels.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If the energy management system does not utilize a control method with an optimal cost function, then the balance between building performance and residents' comfort cannot be optimized

Engineering Contradiction:

Improvebuilding performanceVSAvoidcontrol system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system replaces complex manual control mechanisms with an automated genetic algorithm-based optimization engine. This computational approach substitutes iterative manual tuning and complex rule-based control systems with a unified optimization framework that automatically finds optimal solutions by evaluating multiple objectives simultaneously, reducing the need for complex manual intervention while achieving optimal balance.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentEP3696765B1Method for improving the performance of the energy management in a nearly zero energy building and system therefor

Publication Date: 2026.03.18 ARISTOTLE UNIVERSITY OF THESSALONIKI RESEARCH COMMITTEE ELKE

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AI summary

There is provided an optimal energy management method for a nearly zero energy building (nZEB) based on a genetic algorithm technique (GAT) providing an optimal balance between the targets of energy saving, comfort of the building residents and maximum exploitation of the generated electric energy by the renewable energy sources (RES) through a proper utilization of a battery storage system (BSS). This is achieved by minimizing a cost function (J) that considers the generated/consumed electric energy by each device, the user preferences, the state-of-charge and the energy price of the battery storage system (BSS), the weather forecast. This invention also provides a system implementing the optimal energy management method, which comprises energy and temperature sensors (17), controllable power switches (13), a battery storage system (10) and a controller with human machine interface (16). The outcomes of the energy management system are control signals that regulate the operation of the power switches and the inverter (9) of the battery storage system (BSS).