Energy Management Modeling for Distributed Facilities
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Solution Overview
Problem
Creating effective energy management models for distributed facilities is complicated due to varying climate conditions, functional usage, time zones, and diverse policies, making it difficult to optimize energy consumption and emissions.
Innovation Solution
A system and method that involves obtaining customer facility information, generating a baseline knowledge base, creating an energy operational model, mapping energy sources to asset systems, and optimizing the energy operational model using cost, energy consumption, and emission objective functions to provide operational parameters and thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a detailed spatial model and energy model are created for distributed facilities, then energy management precision is improved, but model creation complexity and time increase
Solution Approach 1:
The patent segments the distributed facility into multiple spatial units or zones, each with its own energy model. This allows the overall complex model to be broken down into manageable components that can be created and managed independently, reducing the complexity burden while maintaining comprehensive energy management precision across the entire facility.
Solution Approach 2:
The patent employs preliminary action by pre-defining standard energy models, spatial templates, and configuration frameworks that can be reused across different facilities. This preliminary preparation significantly reduces the time and complexity of creating detailed models, as the framework is already established before site-specific customization begins.
2Adaptability or versatility
If customized energy models are created for each distributed facility, then energy management adaptability is improved, but model creation difficulty increases
Solution Approach 1:
The patent creates a universal energy management platform that can adapt to different distributed facilities through configurable parameters and modular components. The same base platform serves multiple facilities with different characteristics by adjusting configurations rather than creating entirely custom models, thus improving adaptability while reducing creation difficulty.
Solution Approach 2:
The patent applies local quality by allowing site-specific customizations within the standardized framework. Each facility can have localized adjustments for climate conditions, functional usage, and policies while maintaining the overall structure and benefits of the universal model, achieving adaptability without proportional increase in creation difficulty.
3Manufacturing precision
If comprehensive facility information and historical operational data are collected, then optimization accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent introduces an intermediary layer of data processing architecture that includes data normalization modules, standardized data schemas, and intermediate calculation layers. This intermediary structure organizes and pre-processes comprehensive facility information and historical data in a systematic way, enabling high optimization accuracy while managing data processing complexity through structured intermediate steps.
4Productivity
If multiple objective functions (cost, energy consumption, emission) are optimized simultaneously, then overall energy management effectiveness is improved, but computational complexity increases
Solution Approach 1:
The patent implements periodic action by optimizing different objective functions at different time intervals or hierarchical levels. Instead of simultaneously optimizing all three objectives (cost, energy consumption, emission) at every decision point, the system uses a hierarchical approach where higher-level strategic decisions consider all objectives, while lower-level operational decisions focus on specific objectives, reducing computational complexity while maintaining overall effectiveness.
Data Source
AI summary
Energy modeling of target infrastructure for energy management in distributed-facilities. In one embodiment, an energy management modeling method including obtaining customer facility information and a customer business type; obtaining energy management industry standard information related to the customer business type; generating a baseline customer knowledge base, based on the obtained energy management industry standard information; obtaining facility historical operational information and operational policy information; generating a first energy operational model using the customer facility information, the baseline customer knowledge base, the facility historical operational information, and the operational policy information; generating a mapping of energy sources to asset systems, using the first energy operational model; generating an optimized energy operational model using the mapping of the energy sources to asset systems, wherein the optimized energy operational model utilizes an objective function of cost, energy consumption, and emission; and providing the optimized energy operational model.