Simulation and analysis of load shifting and energy saving potential of CO2-based demand-controlled ventilation in a sports training center

Hamidreza Heidar Esfehani,Jakob Schäuble ,Elena Paul,Dirk Bohne

doi:10.1088/1757-899x/609/5/052042

Abstract

This paper aims to evaluate and characterize the impact of optimizing the operation of the HVAC system through maintaining dynamic CO2-based Demand-Controlled ventilation (DCV) on the electricity load profile and energy consumption of the sports training center of Leibniz University Hannover. The actual ventilation control scheme, in which the operation of the HVAC system is operated with a two-stage volume flow controller based on indoor CO2 concentration is improved through two steps to avoid overventilation and reduce power consumption. For this purpose, a detailed multi-zone model of the sports center and energy supply system has been developed in TRNSYS. In the first step, a multi-stage control scenario is implemented considering the occupancy schedules and indoor CO2 concentration measurement data. In the second step, based on an indoor CO2 concentration model, a predictive control scenario is developed and applied. Aiming at characterizing the influence of these operation scenarios on the power consumption of the building, the annual electricity load profiles of the simulation cases will be analyzed and compared with the actual load profile of the building based on the technical planning documents and data provided by building management system (BMS). Simulation results show that utilizing predictive CO2-based DCV leads to a reduction of the peak load electricity by almost 2 kW and the base load by 5 kW as well as decreasing the annual energy consumption by 40 %.

Highlights

Heating, Ventilation, and Air-conditioning (HVAC) systems account for a significant part of the energy consumption in none-residential buildings
The actual ventilation control scheme, in which the operation of the HVAC system is operated with a two-stage volume flow controller based on indoor CO2 concentration is improved through two steps to avoid overventilation and reduce power consumption
The overall electrical load profile of the ventilation system for the first week of November 2017 is illustrated in Figure 5; It can be observed that operating the ventilation system under scenario 1 results in the highest electrical load level compared with other control schemes, as it is expected from the ventilation rates, using multi-stage ventilation control in the second scenario reduces the power consumption at low occupant periods while integrating the third ventilation scenario leads to the further reduction of power consumption during the periods with no occupancy deviation as well as over-occupied periods

Summary

Introduction

Ventilation, and Air-conditioning (HVAC) systems account for a significant part of the energy consumption in none-residential buildings. Due to the large air-handling systems in none-residential buildings with high occupancy levels, a considerable part of the power consumption in HVAC systems dedicates to the mechanical ventilation. Maintaining indoor air quality (IAQ) through demand-controlled ventilation (DCV) in these buildings is a well-known approach that offers significant energy saving potential through avoiding overventilation. By this method, efficient ventilation rates are supplied based on standard occupancy schedules in each zone. Since the schedules deviations can result in overventilation and increasing power consumption of the air-handling units, DCV strategy should be optimized in terms of accuracy and energy efficiency.

Objectives

Results

Conclusion