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Title: Evaluation of Residential HVAC Control Strategies for Demand Response Programs (SYMPOSIUM PAPERS - CH-06-7 Demand Response Strategies for Building Systems)

Abstract

This paper describes the methodology used to develop the simulation model and the application of the simulation model to study the economic benefits and impacts on distribution feeder load shapes when applying different control strategies to the heating, ventilation and air conditioning (HVAC) systems.

Authors:
;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
883205
Report Number(s):
PNNL-SA-45954
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: ASHRAE Transactions, 112(1):535 (1-12)
Country of Publication:
United States
Language:
English

Citation Formats

Katipamula, Srinivas, and Lu, Ning. Evaluation of Residential HVAC Control Strategies for Demand Response Programs (SYMPOSIUM PAPERS - CH-06-7 Demand Response Strategies for Building Systems). United States: N. p., 2006. Web.
Katipamula, Srinivas, & Lu, Ning. Evaluation of Residential HVAC Control Strategies for Demand Response Programs (SYMPOSIUM PAPERS - CH-06-7 Demand Response Strategies for Building Systems). United States.
Katipamula, Srinivas, and Lu, Ning. Fri . "Evaluation of Residential HVAC Control Strategies for Demand Response Programs (SYMPOSIUM PAPERS - CH-06-7 Demand Response Strategies for Building Systems)". United States. doi:.
@article{osti_883205,
title = {Evaluation of Residential HVAC Control Strategies for Demand Response Programs (SYMPOSIUM PAPERS - CH-06-7 Demand Response Strategies for Building Systems)},
author = {Katipamula, Srinivas and Lu, Ning},
abstractNote = {This paper describes the methodology used to develop the simulation model and the application of the simulation model to study the economic benefits and impacts on distribution feeder load shapes when applying different control strategies to the heating, ventilation and air conditioning (HVAC) systems.},
doi = {},
journal = {ASHRAE Transactions, 112(1):535 (1-12)},
number = ,
volume = ,
place = {United States},
year = {Fri Feb 03 00:00:00 EST 2006},
month = {Fri Feb 03 00:00:00 EST 2006}
}
  • A chronological overview of the advanced control strategies for HVAC&R is presented. The overview focuses on hard-computing or control techniques, such as proportional-integral-derivative, optimal, nonlinear, adaptive, and robust; soft-computing or control techniques, such as neural networks, fuzzy logic, genetic algorithms; and the fusion or hybrid of hard and soft control techniques. Part I focused on hardcontrol strategies; Part II focuses on soft and fusion control and some future directions in HVA&R research. This overview is not intended to be an exhaustive survey on this topic, and any omissions of other works is purely unintentional.
  • Many industrial facilities utilize pressure control gradients to prevent migration of hazardous species from containment areas to occupied zones, often using Proportional-Integral-Derivative (PID) control. Within these facilities, PID control is often inadequate to maintain desired performance due to changing operating conditions. As the goal of the Heating, Ventilation and Air-Conditioning (HVAC) control system is to optimize the pressure gradients and associated flows for the plant, Linear Quadratic Tracking (LQT) provides a time-based approach to guiding plant interactions. However, LQT methods are susceptible to modeling and measurement errors, and therefore a hybrid design using the integration of soft control methods withmore » hard control methods is developed and demonstrated to account for these errors and nonlinearities.« less
  • Abstract- Demand response is playing an increasingly important role in smart grid research today. Technologies that control building equipment and appliances using signals such as real-time prices are making their way into our lives. But the behavior of load both affects and is affected by load control strategies that are designed to support the electric grid. This paper explores the natural behavior of electric load, how it is affected by various load control strategies and what the implications are for concepts such as using load control to support the integration of renewable energy resources.
  • There are 3 appendices listed: (A) DR strategies for HVAC systems; (B) Summary of DR strategies; and (C) Case study of advanced demand response.