PRICES include / exclude VAT
Homepage>ISO Standards>ISO/IEC 15067-3-51:2024-Information technology — Home Electronic System (HES) application model-Part 3-51: Framework of a narrow AI engine for a premises energy management system using energy management agents
Sponsored link
download between 0-24 hoursReleased: 2024
ISO/IEC 15067-3-51:2024-Information technology — Home Electronic System (HES) application model-Part 3-51: Framework of a narrow AI engine for a premises energy management system using energy management agents

ISO/IEC 15067-3-51:2024

ISO/IEC 15067-3-51:2024-Information technology — Home Electronic System (HES) application model-Part 3-51: Framework of a narrow AI engine for a premises energy management system using energy management agents

Format
Availability
Price and currency
English PDF
Immediate download
155.00 EUR
English Hardcopy
In stock
155.00 EUR
Standard´s number:ISO/IEC 15067-3-51:2024
Pages:22
Edition:1
Released:2024
Language:English
DESCRIPTION

ISO/IEC 15067-3-51:2024


This document specifies a Narrow AI Engine Framework including requirements for the Energy Management Agent (EMA) specified in ISO/IEC 15067-3. This standard includes specifications for an AI infrastructure to be embedded in an EMA serving a single structure (home or building) or community housing such as an apartment complex. The Narrow AI Engine specified in this standard for EMAs enables demand response functionality to be located in each EMA instead of an external energy management system. Thus, energy management can be adapted to local and customer needs. The Narrow AI Engine includes operational principles such as prediction, decision–making, and control. This standard builds upon the EMA functions of ISO/IEC 15067-3 and ISO/IEC 15067-3-3. The AI functions specified in this standard support complex decisions about energy management for devices attached to home and buildings networks. These AI specifications enable the EMA to allocate power from public sources (including conventional and nonconventional sources) and local sources (wind, solar, and storage) according to price, availability, appliance and electric vehicle demands, customer preferences, and the customer’s budget.