Description

Advanced control techniques such as Model Predictive Control have been investigated in individual buildings and previous research has shown potentialfor energy saving and comfort improvement compared to conventional control techniques currently implemented in buildings. These advanced controlmethods have the potential to play a keyrole in the development of more sustainable cities. To support this development, the potential of such techniquesneeds to be evaluated at large scale, accounting for the diverse thermal characteristics of buildings rather than focusing on specific cases; to date, replicablemethodologies and flexible tools are lacking to estimate this potential. The current paper falls within this framework. It describes a comprehensive tool toestimate the potential for thermal load management at urban scale, while accounting for the passive storage capacity in buildings. Rather than applying alimited number of predefined scenarios, the tool includes building models and relies on predictive optimization (MPC) to find the best (or near-best)heating schedules for an user-defined objective. The tool considers various energy vectors and can deal automatically with different optimization objectivesacross varying building population sizes. The paper describes an application of the tool using a case study of ten buildings with various thermal propertiesrepresentative of different urban construction characteristics. The aim of the case study is to minimize space heating demand over two months during theheating period. Over the building configurations investigated, the work shows that the median heating demand reduction ranges between 10 and 15%compared to baseline energy management approach; for the same case study, the median discomfort duration reduction ranges between 23 and 100%. Thework also shows the impact of setback temperature on the MPC strategy for the ten buildings considered: with a 3°C (5.4°F) setback, between 7 and16% of space heating energy can be saved compared to a flat setpoint strategy. The quantification of the potential for energy saving resulting from advancedthermal load control is of interest to various stakeholders, including occupants willing to reduce their energy bills or cities investigating how to reachsustainability targets. The impact of the setback temperature on energy saving and comfort for advanced control techniques provides technical backgroundto develop new standards or guidelines.

 

Citation: 2017 Annual Conference, Long Beach, CA, Conference Papers

Product Details

Published:

2017

Number of Pages:

8

Units of Measure:

Dual

File Size:

1 file , 820 KB

Product Code(s):

D-LB-17-C050