Building HVAC Set-Point Scheduling to Reduce Peak Electrical Demand

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Solution Overview

Problem

Commercial and institutional facilities face high peak demand charges that can exceed half of their electrical power bills, necessitating strategies to reduce peak electrical demand without requiring direct control over HVAC systems, which often requires specialized expertise.

Innovation Solution

A method is developed to generate a policy that temporarily changes temperature set points of HVAC systems during pre-cooling, drift, and curtailment periods, allowing building owners to manage peak demand without complex control over equipment, using a baseline electrical demand profile and reference peak values to define sub-periods for reducing peak electrical demand.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Power

If direct control over HVAC compressors and equipment is implemented to reduce peak demand, then peak electrical demand can be reduced, but device complexity and operational difficulty increase significantly

Engineering Contradiction:
Improvepeak electrical demandVSAvoidcontrol system complexity
Core Design Contradiction:
PowerVSDevice complexity

Solution Approach 1:

The patent introduces a building automation system as an intermediary layer between the utility company and the HVAC equipment. This intermediary receives pre-cooling policies from the utility and translates them into automated temperature set-point adjustments, eliminating the need for building operators to directly control complex HVAC equipment while still achieving peak demand reduction

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The HVAC system is enabled to self-regulate its operation based on automated temperature set-points provided by the building automation system. The system automatically adjusts cooling levels during pre-cooling periods without requiring manual intervention or specialized expertise from building operators

Inventive Principle:
Principle #25Self-service

2Loss of energy

If pre-cooling policies are implemented to reduce peak demand, then utility costs can be reduced, but energy consumption during pre-cooling periods increases

Engineering Contradiction:
Improvepeak demand chargeVSAvoidenergy consumption during pre-cooling
Core Design Contradiction:
Loss of energyVSUse of energy by moving object

Solution Approach 1:

The system performs pre-cooling action in advance of the peak demand period by lowering temperature set-points before the utility's pre-cooling window begins. This preliminary action allows the building to benefit from reduced peak demand charges while the actual intensive cooling occurs during off-peak hours when energy rates are lower

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent implements periodic temperature set-point adjustments that align with utility pre-cooling policy windows. The building automation system cycles through different temperature set-points during pre-cooling, drift, and curtailment periods, creating a periodic pattern that reduces overall energy consumption while maintaining comfort during occupied periods

Inventive Principle:
Principle #19Periodic action

Data Source

PatentUS11371737B2Optimization engine for energy sustainability
Publication Date: 2022.06.28 TARGET BRANDS INC
  • US11371737B2 patent drawing
  • US11371737B2 patent drawing
  • US11371737B2 patent drawing

AI summary

A method for reducing peak electrical demand of a building includes generating a baseline electrical demand profile over a target time period from a model. The baseline electrical demand profile can be used to define a policy including a peak management period having at least a first sub-period and a subsequent second sub-period, the first sub-period having a first temperature set point for at least one air handling system of the building that is different from a normal operating temperature set point, the second sub-period having a second temperature set point different from both the normal operating temperature set point and the first temperature set point, and implementing the policy. The model can be generated from one or more of historical electrical data for the building, weather forecast data, building and equipment operating schedules, sales data, and data based on information received from a video camera located in the building.