Smart Building Energy Management System for Energy Efficiency and Demand Response

Abstract

Buildings account for a significant share of total energy use throughout the world. Religious facilities, which account for a substantial portion of overall floor space and energy use in the commercial sector, have rarely been the subject of energy efficiency and management studies. Religious buildings have distinct patterns of occupancy and energy consumption. For example, over five million mosques are thought to exist around the world. Mosques are religious facilities whose usage patterns vary daily in all seasons. Mosques are distinguishable from other types of buildings by their distinct function. A changing operation schedule from one day to another characterizes their function. These buildings are open for occupancy five times daily: at dawn, noon, afternoon, sunset, and evening. The earth's rotation around the sun governs these times; therefore, they vary chronologically over the year according to the season, yet they are eternal. Since mosques are one-story buildings, their rooftops are larger than any multi-story buildings with similar footprints. Because of their larger rooftops and widespread use in many countries, mosques are ideal candidates for solar photovoltaic (PV) installations. However, due to their unique designs and usages in terms of energy consumption and thermal comfort, they need to be assessed differently from residential and commercial buildings. At the same time, due to their presence in temperate climates and unique occupancy patterns, these buildings are often found to be inefficient users of energy.

To date mosque buildings, and other buildings of worship, have gotten insufficient attention in the literature when it comes to their energy use and efficiency. These buildings offer distinct opportunities for investigation in terms of building energy use and indoor comfort due to their unique operation and building properties. Furthermore, within the broad idea of grid modernization, the focus is now on data analytics applications to assure the electric grid's efficient, stable, and resilient operation. Hence, architects are challenged to create innovative designs that make mosques greener and energy efficient while offering a healthier indoor environment. The mosque energy management system's (MEMS) optimal operation is crucial to its security, performance, and efficiency. Challenges posed by the PV system output volatility and geographical dispersion, it is essential to have reliable and effective energy management and control systems in mosque buildings.

This research provides a simulation-based optimization model explicitly tailored for MEMS with the operation under a demand response (DR) program. The proposed MEMS incorporates a solar PV generation system and battery energy storage system (BESS) and optimizes energy usage while maintaining indoor thermal comfort. The mosque building's operational efficiency and reliability can be improved using the developed MEMS. The developed MEMS can be used to optimize other types of buildings with minor customizations based on the needs of each type.

The newly established MEMS has three major functionalities: forecasting, optimized scheduling, and load reduction potentials. Firstly, machine learning applications are used to derive a novel data-driven short-term predictive strategy to forecast the future values of solar radiation and PV power output. It allows for precise forecasts of thermal comfort requirements and electrical grid service availability. Secondly, the coordinated scheduling of MEMS is used to reduce energy usage while maintaining healthier indoor thermal comfort. The third functionality investigates how HVAC setpoint changes impact energy savings and demand reduction potentials in mosque buildings.

A representative sample of five different sizes of mosques in three geographically various locations in Saudi Arabia was selected to demonstrate the effectiveness of the developed framework. For each building, four simulation days were used as study cases as follows: a typical summer day, a typical summer Friday, a typical Ramadhan day, and a typical winter day. Only one winter day type is chosen because there is no air conditioning load during the winter, which is the major load. Each simulation day exhibits different occupancy patterns. The model's simulation findings revealed that the synergetic optimized dispatch may increase the system performance without impacting indoor comfort feeling.