Occupancy driven supervisory control of indoor environment systems to minimise energy consumption of airport terminal building

A very economical way of reducing the operational energy consumed by large commercial buildings such as an airport terminal is the automatic control of its active energy systems. Such control can adjust the indoor environment systems setpoints to satisfy comfort during occupancy or when unoccupied, initiate energy conservation setpoints and if necessary, shut down part of the building systems. Adjusting energy control setpoints manually in large commercial buildings can be a nightmare for facility managers. Incidentally for such buildings, occupancy based control strategies are not achieved through the use of conventional controllers alone. This research, therefore, investigated the potential of using a high-level control system in airport terminal building. The study presents the evolution of a novel fuzzy rule-based supervisory controller, which intelligently establishes comfort setpoints based on flow of passenger through the airport as well as variable external environmental conditions. The inputs to the supervisory controller include: the time schedule of the arriving and departing passenger planes; the expected number of passengers; zone daylight illuminance levels; and external temperature. The outputs from the supervisory controller are the low-level controllers internal setpoint profile for thermal comfort, visual comfort and indoor air quality. Specifically, this thesis makes contribution to knowledge in the following ways: It utilised artificial intelligence to develop a novel fuzzy rule-based, energy-saving supervisory controller that is able to establish acceptable indoor environmental quality for airport terminals based on occupancy schedules and ambient conditions. It presents a unique methodology of designing a supervisory controller using expert knowledge of an airport s indoor environment systems through MATLAB/Simulink platform with the controller s performance evaluated in both MATLAB and EnergyPlus simulation engine. Using energy conservation strategies (setbacks and switch-offs), the pro-posed supervisory control system was shown to be capable of reducing the energy consumed in the Manchester Airport terminal building by up to 40-50% in winter and by 21-27% in summer. It demonstrates that if a 45 minutes passenger processing time is aimed for instead of the 60 minutes standard time suggested by ICAO, energy consumption is significantly reduced (with less carbon emission) in winter particularly. The potential of the fuzzy rule-based supervisory controller to optimise comfort with minimal energy based on variation in occupancy and external conditions was demonstrated through this research. The systematic approach adopted, including the use of artificial intelligence to design supervisory controllers, can be extended to other large buildings which have variable but predictable occupancy patterns

Evaluation of indoor environment system performance for airport buildings

Airport terminals are energy intensive buildings. They are mostly thought to operate on a 24/7 scale and so indoor environment systems run on full schedules and do not have fine control based on detailed passenger flow information. While this assumption of round-the-clock operation may be true for the public areas of the airport building and so opportunity for complete shut-down of HVAC and lighting systems are limited especially in a busy airport terminals, there are many passenger exclusive area within the airport in which occupancy varies strictly with flight schedules. This paper presents the results of indoor environment measurement and flight schedules to identify such opportunities and to implement energy conservation measure in the passenger exclusive areas of the airport building. It also uses building simulation to assess the benefits of such energy saving interventions in terms of comfort, energy and carbon emission savings

Fuzzy supervisory control strategies to minimize energy use of airport terminal buildings

Airport terminal buildings are among energy most consuming buildings and this presents huge opportunities for implementing energy saving strategies. Achieving satisfactory control of these buildings using classical controllers alone is difficult because they contain components that are complex, nonlinear but dynamically related. Therefore, this paper presents and appraises fuzzy control strategies for reducing energy consumptions while simultaneously providing comfort for passengers in an airport terminal building. The inputs into this fuzzy supervisory controller are the time schedule for arrival and departure of passenger planes as well as the expected number of passengers during each flight, zone illuminance and external temperature. The controller outputs optimised temperature, airflow rates and lighting setpoints for the conventional controllers. Simulation studies in MATLAB/SIMULINK confirmed the capacity of this control strategy to provide comfort setpoints for the passengers at reduced energy

Designing an occupancy flow-based controller for airport terminals

One of the most cost-effective ways to save energy in commercial buildings is through designing a dedicated controller for adjusting environmental set-points according occupancy flow. This paper presents the design of a fuzzy rule-based supervisory controller for reducing energy consumptions while simultaneously providing comfort for passengers in a large airport terminal building. The inputs to the controller are the time schedule of the arrival and departure of passenger planes as well as the expected number of passengers, zone global illuminance (daylight) and external temperature. The outputs from the controller are optimised temperature, airflow and lighting set-point profiles for the building. The supervisory controller was designed based on expert knowledge in MATLAB/Simulink, and then validated using simulation studies. The simulation results demonstrate significant potential for energy savings in the controller's ability to maintain comfort by adjusting set-points according to the flow of passengers. Practical application : The systematic approach adopted here, including the use of artificial intelligence to design supervisory controllers, can be extended to other large buildings which have variable but predictable occupancy patterns like the restricted area of the airport terminal building

Investigating the performance of a combined solar system with heat pump for houses

The UK government has committed to generate 20% of the country's energy from renewable sources by 2020. This paper investigates energy reduction in houses by using an innovative solar thermal collector combined with a heat pump system. The dynamic lumped parameter model for a small house is derived and the combined heating system is used to provide the typical hot water and heating requirement. The goal is to maintain thermal comfort inside the house and reduce the amount of electricity consumption used for heating and hot water. This is achieved by reducing the electricity costs through optimising the operation of the heat pump, integrating the available solar energy, and by shifting electricity consumption to the cheaper night time tariff. Models of conventional controller on–off and a multi-variable model predictive control (MPC) are developed and used for several different climatic conditions. The results showed that the model predictive controller performed best by providing better comfort, consuming less electric energy and better use of cheap night time electricity by load shifting and storing heat energy in the heating tank