Reliable energy forecasting helps managers to prepare future budgets for their buildings. Therefore, a simple, easier, less time consuming and reliable forecasting model which could be used for different types of buildings is desired. In this paper, we have presented a forecasting model based on five years of real data sets for one dependent variable (the daily electricity consumption) and six explanatory variables (ambient temperature, solar radiation, relative humidity, wind speed, weekday index and building type). A single mathematical equation for forecasting daily electricity usage of university buildings has been developed using the Multiple Regression (MR) technique. Data of two such buildings, located at the Southwark Campus of London South Bank University in London, have been used for this study. The predicted test results of MR model are examined and judged against real electricity consumption data of both buildings for year 2011. The results demonstrate that out of six explanatory variables, three variables; surrounding temperature, weekday index and building type have significant influence on buildings energy consumption. The results of this model are associated with a Normalized Root Mean Square Error (NRMSE) of 12% for the administrative building and 13% for the academic building. Finally, some limitations of this study have also been discussed.

This paper presents the integrated performance of a solar-assisted desiccant dehumidifier along with Maisotsenko cycle (M-cycle) counter flow heat and mass exchanger. This system handles latent load and sensible load separately. The hybrid configuration of solar thermal collectors was analyzed for efficiency of solar collectors and solar fraction. High consumption of fossil fuels, which are already present in a limited amount, is also associated with environmental problems and climate change issues, as these increase the chances of global warming. These issues demand of us to shift towards renewable energy resources. Increase in world energy use results in a number of environmental problems, such as climate change, in addition to global warming and ozone depletion. In building services, HVAC systems are major concerns. To overcome the requirement, conventional air conditioning and vapor compression systems are mainly used for air conditioning, although these also have some environmental problems. Solar thermal applications in combination with other renewable-energy-dependent cooling practices have generated a huge interest towards sustainable solutions, keeping in view several techno-economical, environmental, and climatic advantages. The experimental investigation reveals that the maximum outlet temperature and efficiency of solar thermal collectors was 87°C and 56% respectively. The maximum cooling capacity of the system is evaluated at 4.6 kW.

The current study presents a numerical and real-time performance analysis of a parabolic trough collector (PTC) system designed for solar air-conditioning applications. Initially, a thermodynamic model of PTC is developed using engineering equation solver (EES) having a capacity of around 3 kW. Then, an experimental PTC system setup is established with a concentration ratio of 9.93 using evacuated tube receivers. The experimental study is conducted under the climate of Taxila, Pakistan in accordance with ASHRAE 93-1986 standard. Furthermore, PTC system is integrated with a solid desiccant dehumidifier (SDD) to study the effect of various operating parameters such as direct solar radiation and inlet fluid temperature and its impact on dehumidification share. The experimental maximum temperature gain is around 5.2°C, with the peak efficiency of 62% on a sunny day. Similarly, maximum thermal energy gain on sunny and cloudy days is 3.07 kW and 2.33 kW, respectively. Afterwards, same comprehensive EES model of PTC with some modifications is used for annual transient analysis in TRNSYS for five different climates of Pakistan. Quetta revealed peak solar insolation of 656 W/m² and peak thermal energy 1139 MJ with 46% efficiency. The comparison shows good agreement between simulated and experimental results with root mean square error of around 9%.

Energy Usage Intensity (EUI, kWh/m²/year) of a building category helps energy managers and building owners in evaluating the energy performance of their buildings. Banks are energy-intensive buildings but there is limited research published in this highly energy-intensive building category. In this paper, the energy consumption of 98 bank buildings located in different cities of the AJK region of Pakistan has been critically analyzed and their EUI value has been established. Data were collected through site visits, interviews, and questionnaires. Electricity consumption of each bank branch was normalized using Cooling Degree Days method and respective annual normalized EUIs were calculated. It was found through analysis that three major factors that drive electricity consumption in bank buildings in Pakistan are; building's area, the number of workstations and the number of Automatic Teller Machines. The EUI of banks in Pakistan has been found to be 222kWh/m²/yr which is comparable with the same of eight other countries.