System and methods for predictive modeling of energy using machine-learning models

A computer system for energy optimization and identifying an energy efficiency program for a property, comprising:

• one or more processors of a computing system in communication with one or more data sources;
• and
• at least one non-transitory computer readable medium storing instructions which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving input data associated with the property from one or more sensors, wherein the input data includes attributes, and wherein the attributes include historical energy usage data, real-time energy consumption data, and location-specific attributes of the property;
• analyzing the input data to determine a property profile including integrating the input data into a unified framework and normalizing the input data for compatibility across a plurality of data formats;
• inputting the property profile and data from the one or more data sources for one or more energy efficiency programs into a machine-learning model;
• in response to the inputting, processing, utilizing the machine-learning model, the input data to (i) classify one or more energy usage patterns of the property, and (ii) predict one or more energy savings inefficiencies for the property;
• adjusting one or more weights of the machine-learning model in response to a deviation between a set of predicted savings and a set of actual energy savings;
• matching, utilizing the machine-learning model with the one or more adjusted weights, at least one energy efficiency program from the one or more energy efficiency programs to the property based upon the input data and the predicted one or more energy savings inefficiencies;
• generating an energy assessment of the property and a cost analysis based upon the predicted one or more energy savings inefficiencies and the at least one energy efficiency program;
• and
• generating an interactive visualization of the energy assessment and the at least one energy efficiency program in a graphical user interface of a device, wherein the visualization dynamically updates based upon real-time data received from the one or more sensors corresponding to energy usage, and wherein the dynamically updated interactive visualization displays (i) one or more energy consumption patterns over time, (ii) one or more projected impacts of applying one or more selected energy efficiency programs, and (ii) one or more highlighted inefficiencies and trends.

A non-transitory computer readable medium for energy optimization and identifying an energy efficiency program for a property, the non-transitory computer readable medium storing instructions which, when executed by one or more processors of a computing system in communication with one or more data sources, cause the one or more processors to perform operations comprising:

• receiving input data associated with the property from one or more sensors, wherein the input data includes attributes, and wherein the attributes include historical energy usage data, real-time energy consumption data, and location-specific attributes of the property;
• analyzing the input data to determine a property profile including integrating the input data into a unified framework and normalizing the input data for compatibility across a plurality of data formats;
• inputting the property profile and data from the one or more data sources for one or more energy efficiency programs into a machine-learning model;
• in response to the inputting, processing, utilizing the machine-learning model, the input data to (i) classify one or more energy usage patterns of the property, and (ii) predict one or more energy savings inefficiencies for the property;
• adjusting one or more weights of the machine-learning model in response to a deviation between a set of predicted savings and a set of actual energy savings;
• matching, utilizing the machine-learning model with the one or more adjusted weights, at least one energy efficiency program from the one or more energy efficiency programs to the property based upon the input data and the predicted one or more energy savings inefficiencies;
• generating an energy assessment of the property and a cost analysis based upon the predicted one or more energy savings inefficiencies and the at least one energy efficiency program;
• and
• generating an interactive visualization of the energy assessment and the at least one energy efficiency program in a graphical user interface of a device, wherein the visualization dynamically updates based upon real-time data received from the one or more sensors corresponding to energy usage, and wherein the dynamically updated interactive visualization displays (i) one or more energy consumption patterns over time, (ii) one or more projected impacts of applying one or more selected energy efficiency programs, and (ii) one or more highlighted inefficiencies and trends.