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.

India, Pakistan, and Bangladesh (IPB) are the largest South Asian countries in terms of land area, gross domestic product (GDP), and population. The growth in these countries is impacted by inadequate renewable energy policy and implementation over the years, resulting in slow progress towards human development and economic sustainability. These developing countries are blessed with huge potential for renewable energy resources; however, they still heavily rely on fossil fuels (93%). IPB is a major contributor to the total energy consumption of the world and its most energy-intensive building sector (India 47%, Pakistan 55% and Bangladesh 55%) displays inadequate energy performance. This paper comprehensively reviews the energy mix and consumption in IPB with special emphasis on current policies and its impact on economic and human development. The main performance indicators have been critically analyzed for the period 1970–2017. The strength of this paper is a broad overview on energy and development of energy integration in major South Asian countries. Furthermore, it presents a broad deepening on the main sector of energy consumption, i.e., the building sector. The paper also particularly analyzes the existing buildings energy efficiency codes and policies, with specific long-term recommendations to improve average energy consumption per person. The study also examines the technical and regulatory barriers and recommends specific measures to adapt renewable technologies, with special attention to policies affecting energy consumption. The analysis and results are general and can be applied to other developing countries of the world.

The building sector consumes about 40% of the world’s primary energy. Seasonal climatic conditions have a significant effect on the energy consumption in buildings. One of the famous methods used for decoding this seasonal variation in buildings energy consumption is the “Degree Days Method”. Data has been widely published for the heating and cooling degree days of different countries. Unfortunately, there is very limited and outdated published data for the heating and cooling degree-days of Pakistan. In this study, yearly average heating and cooling degree-days for different regions of Pakistan are established by using 30 year long-term measured data for different base temperatures. The data is presented in tables and figures whereas heating and cooling degree-day maps of Pakistan have been developed.

In Pakistan, data for household electricity consumption are available in the form of monthly electricity bills only, and, therefore, are not helpful in establishing appliance-wise consumption. Further, it does not help in establishing the relationship among the household electricity consumption and various driving factors. This study aimed to unlock the household electricity consumption in Pakistan by analyzing electricity bills and investigating the impact of various socioeconomic, demographic, and dwelling parameters and usage of different appliances. The methodology adopted in this study was survey-based data collection of the residential sector. For this purpose, data were collected from 523 dwellings through surveys and interviews in Mirpur city. The results of the data analysis revealed that the average household electricity consumption is 2469 kWh/year with an average family size of seven and an average floor area of 78.91 m². Based on possession of various appliances, the households were categorized into four types and their consumption patterns were established and compared. Air Conditioned (AC) houses consume 44% more electricity compared to the non-AC houses, whereas an Uninterrupted Power Supply (UPS) consumes electricity equivalent to an AC. The research findings are useful for policy makers and building designers and are discussed in the conclusion section.

Universities in the United Kingdom that have installed Combined Heat and Power (CHP) technology are making good moves towards achieving their CO₂ reduction targets. However, CHP may not always be an economical option for a university campus due to numerous factors. Identification of such factors is highly important before making an investment decision. A detailed technical, economic, and environmental feasibility of CHP is, therefore, indispensable. This study aims to undertake a detailed assessment of CHP for a typical university campus and attempts to highlight the significance of such factors. Necessary data and information were collected through site visits, whereas the CHP sizing was performed using the London South Bank University (LSBU) CHP model. The results suggest that there is a strong opportunity of installing a 230 kW CHP that will offset grid electricity and boilers thermal supply by 47% and 75%, respectively, and will generate financial and environmental yearly savings of £51k and 395 t/CO₂, respectively. A wider spark gap decreases the payback period of the project and vice versa. The capital cost of the project could affect the project’s economics due to factors, such as unavailability of space for CHP, complex existing infrastructure, and unavailability of a gas connection.

Rising temperatures, increase in population, and dense urban morphology have resulted in increased cooling energy demands. The conventional degree-days method to calculate cooling energy demand considers only the sensible heat load of air and neglects the latent component. This study aims to estimate the cooling degree days based on the heat index (by considering both the sensible and latent loads) for the current and future years (2050 and 2080). Further, the ventilation load index for each of these cities has been established to unlock the impact of ventilation on the building’s total energy consumption for current and future years. The results show that heat index-based degree days have a stronger relationship with the buildings’ cooling energy consumption and, therefore, can predict the cooling energy demand of buildings with 20% higher accuracy than conventional temperature-based degree days. Analysis shows that cooling degree-days and frequency of temperature above the comfort range continue to increase in Pakistan, highlighting increased degree-days in the range from 11.0 to 41.6% by 2050 and from 28.4 to 126.5% by 2080. Prompt actions are essential to enhance the resilience of Pakistan’s national grid to meet these future cooling energy demands.