Real-time emissions monitoring
Introduction
Energy Management Software (Energy Management Software - EMS) is a general term and category that refers to a variety of energy-related software applications[1] that can provide utility bill tracking, real-time metering, building lighting and HVAC control systems, building simulation and modeling, carbon and sustainability reporting, IT equipment management, demand response), and/or energy audits. Energy management may require a systems approach. systems.[2].
Energy management software often provides tools to reduce energy costs and consumption in buildings or communities. The EMS collects energy data and uses it for three main purposes: reporting, monitoring and engagement. Reports may include verifying energy consumption data, benchmarking, and setting high-level energy use reduction targets. Monitoring may include trend analysis and energy consumption tracking to identify cost-saving opportunities. Engagement may mean real-time responses (automated or manual), or initiating a dialogue between occupants and building managers to promote energy conservation. An engagement method that has recently gained popularity is the real-time energy consumption display available in web applications or an on-site dashboard/screen.
Data collection
Energy management software uses historical and/or real-time interval data, with intervals ranging from quarterly statements to minute-by-minute smart meter readings. Data is collected from interval meters, Building Automation Systems (BAS), directly from utilities, directly from sensors on electrical circuits,[3] or other sources. Past bills can be used to provide a comparison between pre- and post-EMS energy consumption.
Energy Data Analytics
Through data analysis (Energy Data Analytics), the EMS helps users in composing mathematical formulas to analyze, forecast and track energy conservation measures to quantify the success of the measure, once implemented. Energy analytics[4] help managers combine energy and non-energy data to create key performance indicators, calculate carbon footprint, greenhouse gases, renewable heat incentives") and energy efficiency certifications to comply with local climate change policies, directives, regulations and certifications. Energy analytics also include intelligent algorithms such as classification and machine learning to analyze the energy consumption of buildings and/or their equipment that build a memory of energy usage patterns, learn behaviors good and bad power consumption and notify in case of abnormal power usage.