Method for improving the performance of the energy management in a nearly zero energy building

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Solution Overview

Problem

Existing energy management systems for nearly-zero energy buildings (nZEBs) fail to balance energy saving, resident comfort, and the optimal exploitation of renewable energy sources and battery storage systems, often increasing utility bills or compromising comfort.

Innovation Solution

An energy management method utilizing a genetic algorithm to optimize the scheduling of programmable electric loads and battery storage systems, considering real-time electricity prices, user preferences, state-of-charge, and weather forecasts, through control signals to power switches and inverters.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If the energy management system prioritizes only the comfort level of residents, then the comfort of building residents is improved, but the electricity utility bills are increased

Engineering Contradiction:

Improvecomfort of building residentsVSAvoidelectricity utility bills

Core Design Contradiction:

Ease of operationVSLoss of energy

Solution Approach 1:

The system dynamically adjusts energy management strategies based on real-time conditions including weather forecasts, real-time electricity prices, and battery state-of-charge levels. The genetic algorithm continuously optimizes control signals for power switches and inverters, allowing the system to adapt between comfort prioritization and cost reduction modes rather than using fixed rules

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates multiple feedback loops including real-time electricity price signals, battery state-of-charge monitoring, weather forecast integration, and consumption pattern analysis. This feedback enables the genetic algorithm to learn from past performance and adjust energy management decisions to balance comfort and cost effectively

Inventive Principle:

Principle #23Feedback

2Loss of energy

If the energy management system prioritizes only the reduction of electricity cost, then the electricity utility bills are reduced, but the comfort of residents is adversely affected

Engineering Contradiction:

Improveelectricity utility billsVSAvoidcomfort of building residents

Core Design Contradiction:

Loss of energyVSEase of operation

Solution Approach 1:

The system uses weather forecasts to predict future energy generation from renewable sources and pre-charges battery storage systems when electricity prices are low or renewable generation is high. This preliminary action ensures energy availability during peak price periods without compromising resident comfort

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The genetic algorithm optimizes multiple parameters including battery charge/discharge rates, power switch timing, inverter control settings, and load scheduling. By dynamically changing these parameters based on real-time conditions, the system achieves cost reduction while maintaining comfort within acceptable ranges

Inventive Principle:

Principle #35Parameter changes

3Object-generated harmful factors

If the energy management system increases the exploitation of renewable energy sources, then the carbon emissions are reduced, but the balance with resident comfort and energy saving objectives becomes difficult to maintain

Engineering Contradiction:

Improvecarbon emissionsVSAvoidbalance between energy saving and comfort

Core Design Contradiction:

Object-generated harmful factorsVSAdaptability or versatility

Solution Approach 1:

The battery storage system acts as an intermediary between renewable energy sources and building loads. It absorbs excess renewable energy when generation exceeds demand and releases energy when renewable generation is insufficient, enabling maximum renewable exploitation while maintaining comfort and energy saving objectives through the genetic algorithm's optimization of charge/discharge cycles

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11971185B2Method for improving the performance of the energy management in a nearly zero energy building

Publication Date: 2024.04.30 ARISTOTLE UNIVERSITY OF THESSALONIKI RESEARCH COMMITTEE ELKE

AI summary

An optimal energy management method and a system that implements the method for a nearly zero energy building (nZEB) based on the genetic algorithm technique that can provide an optimal balance between the objectives of energy saving, comfort of the building residents and maximum exploitation of the generated electric energy by the renewable energy sources through the proper utilization of a battery storage system, is developed in this invention. The above can be attained by minimizing a cost function that considers the real-time electricity price, 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), and the weather forecast. the system that implements the optimal energy management method comprises energy and temperature sensors, controllable power switches, a battery storage system and a controller with human machine interface. The outcomes of the energy management system are control signals that regulate the operation of the power switches and the inverter of the battery storage system.