Aizaz Samuel

Development of an adaptive window-opening algorithm to predict the thermal comfort, energy use and overheating in buildings

This investigation of the window-opening data from extensive field surveys in UK office buildings demonstrates: (1) how people control the indoor environment by opening windows; (2) the cooling potential of opening windows; and (3) the use of an ‘adaptive algorithm’ for predicting window-opening behaviour for thermal simulation in ESP-r. It was found that when the window was open the mean indoor and outdoor temperatures were higher than when closed, but it was shown that nonetheless there was a useful cooling effect from opening a window. The adaptive algorithm for window-opening behaviour was then used in thermal simulation studies for some typical office designs. The thermal simulation results were in general agreement with the findings of the field surveys. The adaptive algorithm is shown to provide insights not available using non adaptive simulation methods and can assist in achieving more comfortable, lower energy buildings while avoiding overheating.

Considering the impact of situation-specific motivations and constraints in the design of naturally ventilated and hybrid buildings

A simple logical model of the interaction between a building and its occupants is presented based on the principle that if free to do so, people will adjust their clothing or available building controls with the aim of achieving or restoring comfort and reducing discomfort. These adjustments are related to building design in two ways: first, the freedom to adjust depends on the availability and ease of use of control options; second, the use of controls affects building comfort and energy performance. The values of constraints are quantified for a range of existing buildings in Europe and Pakistan. The integration of the model within a design flow is proposed and the impact of different levels of constraints demonstrated. It is proposed that to minimize energy use and maximize comfort in naturally ventilated and hybrid buildings the designer should take the following steps: (i) provide unconstrained low-energy adaptive control options where possible, (ii) avoid problems with indoor air quality which provide motivations for excessive ventilation rates, (iii) incorporate situation-specific adaptive behaviour of occupants in design simulations, (iv) analyse the robustness of designs against variations in patterns of use and climate and (v) incorporate appropriate comfort standards into the operational building controls.

An integrated approach to indoor contaminant modelling

Good indoor air quality is essential to ensure adequate internal environmental conditions, avoiding possible problems related to health, productivity, and comfort of individuals inhabiting a building. In order to appraise internal contaminant levels, taking into account sources, sinks, and transport of pollutants from the outside and throughout a building, an indoor contaminant behavior prediction method was developed using coupled thermal and mass flow simulation. The developed approach was validated against analytical, inter-model, and empirical results. It was shown that an integrated approach within a building performance simulation environment was necessary because situations exist in which assessment of just one domain does not give an accurate depiction of reality. This paper describes why it is important to take a global look at contaminant behavior. It was found that significant errors could occur if spatial and temporal temperature variations are not included in the prediction of contaminant levels.

Performance of actively controlled domestic heat storage devices in a smart grid

Distributed, small-scale energy storage has been identified as a means of improving load factors for intermittent renewable generation and displacing the need for fossil-based backup. Domestic electric storage heaters operating within a smart grid offer high density, controllable energy storage at low cost, allowing the network operator to shift demand by charging heaters to dispose of excess supply. This paper reports monitoring outcomes and simulation studies on the first field trials of such a system, in which heaters are capable of responding to instructions from the grid to vary charging level at 15-min intervals, as well as to occupant-set controls on power output. Monitoring found significant unexpected out-of-schedule power draw and under-utilisation of storage capacity. Alternative approaches to scheduling were tested using simulations, and evaluated using metrics to quantify schedule following as well as other aspects of performance to give a balanced view of system performance to the network operator. Modern insulated storage heaters are capable of supporting load shifting for up to 48 h with minimal impact on room temperatures or demand, and with high confidence that charging schedules will be followed. However, where device controllers compete with centrally generated charge scheduling, the network will experience significant out-of-schedule power draw while occupants will experience either lower temperatures or increased cost.