One goal of iSERV project is to provide an automatic tool that enables the user to detect the weaknesses of its HVAC system and to assess potential savings through modelling. The tool is based on some information data provided about the system and the associated building as well as on electrical measurements data taken on the system.
iSERV has collected data from HVAC systems and buildings from 15 Member States of the European Union. This data, collected through continuous electrical monitoring, is then analysed so as to support end-users to improve energy efficiency of their own systems. That aim can be achieved by means of detecting different ECOs (Energy Conservation Opportunities) based on either real data metering or modelling.
A number of ECOs, capable of being addressed in this manner, have been selected and prioritised to offer an efficient financial ratio for the end-user in terms of investment and payback. These ECOs might consider e.g. the modification of regulation to adjust internal setpoints or HVAC system schedule. ECOs based on real metered data or modelling are used depending of the level of data available from the end-user and integrated within the HERO database (the online application tool of iSERV). Mathematical models have been developed and compiled for integration into HERO enabling automatic detection of these modelled ECOs for a specific building system. Approximately 15 ECOs modelled in this manner will be available at the end of the project to prove the concept.
Input requirements for modelled ECOs are mainly based on data available in HERO. For instance, if not available, power needed for lighting and appliances are estimated from activity (e.g. office building). Modelling ECOs are divided into two categories, depending on whether they need a monthly heating and cooling needs calculation. In the latter case, electrical consumption for HVAC system including auxiliaries is derived from heating and cooling needs.
The main Methodology used consists in considering a reference building case, which is pre-computed through the model core based on ISO standard 13690. Then the considered ECO is applied by varying one or more parameters, which allows assessing an estimation of potential savings (e.g. minimum savings, average savings, and maximum savings).
The following example illustrates the implementation of a simple ECO with high priority because of low investment and high payback.
ECO example: Shut off A/C equipment when not needed
Note: this ECO could be derived from the real metered data and/or from modelling depending on the level of data available for the considered HVAC system (i.e. with sub-metering or hourly data or not)
Definition
This ECO mainly aims to reduce energy used for the global AC system by applying an occupancy working schedule.
Action 1:
This reduction may apply by reviewing the operation schedule of the A/C system considering the building’s occupancy schedule. Thus the cold generator could be shut off during the unoccupied period, giving potential savings from:
• Night operation
• Week-end operation
Action 2:
Furthermore, the cooling equipment could be shut off during cold conditions, if it is not currently the case and if applicable (e.g. a data center needs cooling during the whole year).
To which systems does this ECO apply ?
This ECO could apply to any Air Conditioned equipment, including pumps when the cold generator includes pumps.
Tools
Model based on ISO 13790. Fully simulated ECO.
Pre-conditions : check & validation
• This ECO doesn’t apply if real metered data is available for the system. An alternative algorithm will assess the potential savings using the real data in this case
• AC equipment is working during unoccupied periods (night/week-end) and/or cooling is working during winter season
Description
1/ Preconditions check:
• Look at the schedule and occupancy to check whether the AC equipment is used during unoccupied period of the building (night/week-end).
• Check if AC equipment is working during winter season for cooling and check activity
Then, if pre-conditions are validated:
2/ The « ISO 13790 » core of the model is first computed with available data from the HERO database, especially schedules. Then the model is recomputed by reviewing the schedules:
a) Cooling/Heating schedule starts one hour before occupancy schedule and stops at the end of occupancy
b) If activity agrees (e.g. zone served by AC system is not a data centre), and if cooling is applied during winter, then cooling is considered capable of being shut off during the winter season.
Results
Results are expressed as a percentage of simulated energy savings.
Potential of energy savings:
• … % of cooling
• … % of global HVAC consumption
• … % of building consumption
Author: Julien Carton (University of Liège)