Real-Time Data and Analytics on Building Management System to Control Energy Consumption

This paper is on the realm of Real-Time Data and Analytics in the context of Building Management Systems for Energy Consumption Control. Given the escalating household electricity consumption and the integration of decentralized energy sources, the optimization of electricity procurement costs assumes paramount significance. An effective solution in this regard is the introduction of a Home Energy Management System (HEMS). HEMS operates autonomously, efficiently adapting to fluctuations in electricity rates and household energy consumption patterns. This paper delves into the architecture and efficiency-driven scheduling algorithms employed by HEMS. Additionally, it explores the integration of HEMS within the broader spectrum of cutting-edge technologies, encompassing smart grids, demand response mechanisms, intelligent home systems, innovative energy generation methods, advanced energy storage solutions, and their interconnections. The framework is built upon an Advanced Metering Infrastructure (AMI) and utilizes localized information management terminals for data storage and optimized scheduling. The objective here is to scrutinize the benefits and potential risks associated with Real-Time Data and Analytics in Building Management Systems for Energy Consumption Control, with the aim of cost reduction, risk mitigation, and the elimination of operational inefficiencies.