Integrated Demand Response System for Facility Energy Optimization
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Solution Overview
Problem
Large-scale facilities inefficiently manage energy consumption, leading to suboptimal use of resources and peak demand issues that overload power grids, resulting in economic and environmental consequences.
Innovation Solution
An integrated demand response system that uses artificial intelligence to optimize power allocation and generation across facility systems by determining marginal costs and adjusting energy consumption based on sensor data, weather forecasts, and scheduling, allowing for holistic energy management and peak demand reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual and independent control of facility systems is used, then operational simplicity is maintained, but energy resource utilization becomes suboptimal
Solution Approach 1:
The patent combines multiple independent facility systems (HVAC, lighting, security, etc.) into a single integrated demand response system that centrally manages energy allocation. This merging allows the system to optimize energy distribution across all systems simultaneously, resolving the contradiction by achieving both centralized optimization and maintaining individual system operational independence through modular architecture.
Solution Approach 2:
The integrated demand response system serves multiple functions: it manages energy allocation, monitors system performance, responds to utility signals, and coordinates load management across diverse facility systems. This multi-functionality allows a single system to improve energy utilization efficiency while maintaining ease of operation through unified control interfaces.
2Reliability
If peak demand is met by building additional power plants, then power supply reliability is improved, but infrastructure cost efficiency deteriorates
Solution Approach 1:
The system performs preliminary action by proactively reducing load during peak demand periods through automated demand response strategies. By anticipating peak periods and pre-cooling facilities or pre-positioning energy storage, the system reduces peak demand without requiring additional power plants, thus maintaining reliability while avoiding the high costs of peak-only infrastructure.
Solution Approach 2:
The system implements continuous feedback loops that monitor utility pricing signals, load conditions, and system performance. This feedback enables dynamic adjustment of energy consumption patterns, allowing the facility to respond to real-time conditions and optimize energy usage, thereby reducing the need for expensive peak infrastructure while maintaining reliable power supply.
3Object-affected harmful factors
If energy consumption is reduced during peak periods, then power grid overload is prevented, but facility operational flexibility is reduced
Solution Approach 1:
The system dynamically adjusts energy allocation based on real-time conditions, utility signals, and facility needs. Rather than imposing static load reductions, the system continuously adapts its control strategies, allowing flexible response to changing conditions while maintaining operational requirements. This dynamic approach prevents grid overload while preserving facility operational flexibility.
Solution Approach 2:
The system changes operational parameters of facility systems (temperature setpoints, lighting schedules, equipment operation times) to reduce peak demand. By adjusting these parameters dynamically based on utility pricing and load conditions, the system reduces power consumption during critical periods while maintaining acceptable operational performance and flexibility.
Data Source
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AI summary
A method for managing power consumption within a facility includes receiving a request to reduce a total level of power consumption within the facility by a predetermined measure (S23). A plurality of operating parameters indicative of how much power is being consumed by each of a plurality of facility systems is received (S21). A corresponding cost associated with a marginal power reduction is determined for each of the plurality of facility systems using the received plurality of operating parameters (S24). A power allocation to the facility system of the plurality of facility systems that is determined to have a lowest marginal cost of power reduction is incrementally reduced (S25). The steps of determining a corresponding cost and incrementally reducing power are repeated until the total level of power consumption within the facility has been reduced by the predetermined measure.