Cloud Power Management for Building Load Optimization
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Solution Overview
Problem
Existing power management systems for power distribution networks face challenges such as high costs, inefficiencies in demand reduction, inadequate load forecasting, and reliability issues, particularly during peak demand periods, and often require expensive hardware in each building, while failing to minimize load disturbances across the system.
Innovation Solution
A cloud-based power management system that utilizes thermal storage devices, distributed energy resources, and energy storage devices, along with an interface device and a central load controller, to forecast and optimize power demand, reduce peak loads, and minimize the need for auxiliary generators by preheating or precooling buildings and storing energy before peak periods, using dynamic thermal models and optimized load commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing power management systems are deployed, then power demand can be managed, but expensive hardware components are required in each building
Solution Approach 1:
The patent extracts the complex control hardware from individual buildings and consolidates it into a centralized cloud-based power management system. The system uses existing communication infrastructure to transmit power consumption data from buildings to the centralized controller, which then performs optimization calculations and sends control commands back, eliminating the need for expensive local hardware while maintaining demand management capability
Solution Approach 2:
The patent introduces a cloud-based intermediary system that mediates between power consumption data from multiple buildings and the control commands needed to optimize demand. This centralized intermediary performs thermal modeling and optimization calculations, acting as an intelligent mediator that coordinates load management across the entire building portfolio without requiring complex local hardware at each building site
2Productivity
If existing power management systems are used, then some demand reduction is achieved, but the effect of load disturbance is not minimized throughout the system
Solution Approach 1:
The patent implements a feedback mechanism where the centralized power management system continuously monitors actual power consumption data from multiple buildings, compares it against thermal models and forecasts, and adjusts control commands accordingly. This closed-loop feedback enables the system to minimize load disturbances by making real-time adjustments that maintain comfort while optimizing demand reduction across the entire system
Solution Approach 2:
The patent uses thermal modeling to perform preliminary actions by pre-cooling or pre-heating buildings before peak demand periods. The system forecasts future power consumption and proactively adjusts HVAC operations in advance, storing thermal energy in building thermal mass during off-peak hours. This preliminary action reduces peak demand while minimizing disturbances to building comfort during critical periods
3Power
If traditional power generation capabilities are relied upon, then base power demand is met, but auxiliary generators are required during peak periods
Solution Approach 1:
The patent applies preliminary action by pre-cooling or pre-heating buildings during off-peak hours using HVAC systems, storing thermal energy in building thermal mass. This advance preparation reduces the cooling or heating load during peak demand periods, allowing the system to meet peak power demands with existing infrastructure rather than requiring auxiliary generators
Solution Approach 2:
The patent changes the operational parameters of HVAC systems by adjusting setpoints and operation schedules based on thermal models and forecasts. The system modifies temperature setpoints temporarily during off-peak periods to charge thermal mass, then relies on this stored thermal energy during peak periods, effectively changing the parameter of when heating or cooling is delivered to flatten the power demand curve
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively reduces peak power demand, minimizes energy costs, and enhances reliability by optimizing the use of thermal and energy storage devices, reducing the need for auxiliary generators, and providing cost-effective solutions for power distribution networks.
Implementation Method 1
a thermal storage device structured to receive electric power, convert the electric power to thermal energy, and store the thermal energy
Implementation Method 2
a distributed energy resource structured to receive solar irradiance, to convert the solar irradiance into electric power
Implementation Method 3
a thermal load structured to maintain a building temperature
Data Source
AI summary
Unique systems, methods, techniques and apparatuses for cloud-based control for power distribution systems are disclosed. One exemplary embodiment is a system comprising a microprocessor-based power management system in operative communication with a plurality of buildings located remotely from the power management system and a plurality of communication interface devices provided at corresponding ones of the plurality of buildings. The power management system is structured to perform a plurality of building unit-specific optimizations, evaluate a net power demand on the electrical power grid, reduce the net power demand on the electrical power grid while minimizing disruption to the resident-defined preference parameters, and transmit to each of the plurality of interface devices the one or more additional control commands corresponding to the specific building at which each interface device is provided.