Central Plant Optimization via Streamlined Data Linkage
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Solution Overview
Problem
Central plants face challenges in optimally designing and operating energy distribution across subplants due to data sharing difficulties between design and operational tools, leading to inefficiencies and increased costs.
Innovation Solution
A central plant optimization system that includes a planning tool for generating a model of the central plant, a central plant controller for combining this model with timeseries data, and an optimization platform to determine optimal energy load allocation across equipment at each time step, facilitating seamless data linkage and operational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is shared between design and operational tools, then operational efficiency is improved, but data integration complexity increases
Solution Approach 1:
The patent implements a data exchange interface that serves as an intermediary between design tools and operational control systems. This interface uses standardized data formats and protocols to enable seamless data sharing without requiring complex custom integration, thus improving operational efficiency while maintaining manageable integration complexity.
Solution Approach 2:
The system employs a universal data model that can represent both design specifications and operational parameters within a single framework. This multi-functional data structure allows the same data infrastructure to serve multiple purposes throughout the asset lifecycle, from design through operation, reducing the need for separate data systems and their associated integration complexities.
2Adaptability or versatility
If data re-formatting is performed when moving between tools, then data compatibility is improved, but time and cost increase
Solution Approach 1:
The patent implements a standardized data parameter framework that automatically adjusts data representation based on the receiving system's requirements. Rather than manual re-formatting, the system dynamically transforms data parameters (such as units, precision, and structure) according to pre-defined compatibility rules, ensuring data compatibility while minimizing processing time and costs.
3Productivity
If optimal energy load allocation is achieved, then operational costs are reduced, but computational complexity increases
Solution Approach 1:
The system performs preliminary computational analysis during the design phase to pre-determine optimal operational strategies and parameters. By conducting optimization calculations in advance when full system data is available, the complex computational work is completed beforehand, allowing real-time operational decisions to be made with simpler, pre-calculated guidance, thus reducing operational costs without excessive real-time computational burden.
Data Source
AI summary
A central plant optimization system for designing and operating a central plant includes a planning tool, a central plant controller, and an optimization platform. The planning tool is configured to generate a model of the central plant. The central plant controller is configured to receive the model of the central plant from the planning tool and combine the model of the central plant with timeseries data including a timeseries of predicted energy loads to be served by equipment of the central plant. The optimization platform is configured to receive the model of the central plant combined with the timeseries data, construct an optimization problem using the model of the central plant and the timeseries data, solve the optimization problem to determine an optimal allocation of the energy loads across the equipment of the central plant, and provide optimization results to the central plant controller. The central plant controller is configured to use the optimization results to operate the equipment of the central plant to achieve the optimal allocation of the predicted energy loads.