Dynamic Energy Management System for Predictive Load Control
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Solution Overview
Problem
Current energy management systems lack the ability to actively predict and control energy use based on future trends, relying on static billing systems and inefficient energy distribution, which hinders optimal utilization of limited energy resources.
Innovation Solution
An energy management apparatus and method that collects data on energy use, estimates future energy consumption and costs using sensors and smart meters, and adjusts energy supply by controlling appliances based on estimated charges and user-defined schedules, integrating with smart grid technology for real-time monitoring and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a flat rate billing system is used, then simplicity of billing is maintained, but energy resources are not used efficiently
Solution Approach 1:
The billing system transitions from a static flat rate structure to a dynamic differential rate structure that changes based on time slots and energy consumption levels. The system divides the billing period into multiple time slots with different rates, allowing energy pricing to adapt dynamically to grid conditions and consumption patterns, thereby improving energy efficiency while maintaining operational simplicity through automated calculations.
Solution Approach 2:
The billing parameters are changed from a single fixed rate to multiple variable rates based on time of day, day of week, and energy consumption thresholds. By changing the pricing parameters dynamically, the system encourages off-peak usage and reduces peak demand, improving overall energy efficiency without complicating the user experience through automated rate selection.
2Productivity
If real-time energy monitoring is implemented, then energy management capability is improved, but system complexity increases
Solution Approach 1:
The energy management system is designed to perform multiple functions through a single integrated platform: real-time monitoring, data collection from multiple sources, predictive analytics, billing calculation, and user notification. By consolidating these functions into one universal system rather than separate components, the patent reduces overall system complexity while maintaining comprehensive energy management capabilities.
Solution Approach 2:
The system automatically collects energy consumption data from sensors and smart meters, performs predictive analytics using stored algorithms, calculates billing amounts based on differential rates, and sends notifications to users without requiring manual intervention. This self-service approach reduces operational complexity while enhancing energy management productivity through automated processes.
3Measurement precision
If future energy use prediction is performed, then energy planning accuracy is improved, but computational requirements increase
Solution Approach 1:
The system performs preliminary actions by collecting and storing energy consumption data in advance during normal operation. Historical data is accumulated and pre-processed, creating a foundation for future predictions. This preliminary data preparation reduces the computational burden during prediction operations, as the raw data collection and initial processing have already been completed during routine monitoring periods.
Solution Approach 2:
The prediction system uses a simplified modeling approach that focuses on key consumption patterns and trends rather than attempting to model every variable. By applying partial action—concentrating computational resources on the most significant prediction factors—the system achieves sufficient accuracy for energy planning purposes without requiring excessive computational power for exhaustive analysis of all possible variables.
Data Source
AI summary
Provided are an apparatus and a method for energy management. The energy management apparatus includes: a receiving block configured to receive energy use information from at least one sensor; and an estimating block configured to calculate a sum and change of energy use per predetermined time slot from the received energy use information and estimate energy use or energy charge after a certain time based on the calculation of the sum and the change. The method includes: receiving energy use information from at least one sensor; and calculating a sum and change of energy use per hour from the received energy use information and estimating energy use or energy charge after a certain time slot based on the calculation of the sum and the charge.