Central Plant EMPC Control for Real-Time Energy Cost Allocation
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Solution Overview
Problem
Optimally allocating energy loads across the assets of a central plant is challenging, especially with real-time pricing from utilities, as existing methods struggle to efficiently manage resource production and consumption to minimize economic costs.
Innovation Solution
An economic model predictive control (EMPC) tool is implemented, which includes configuration tools for user input, a data model extender, a high-level EMPC algorithm, and an asset allocator to generate and solve optimization problems, determining optimal control decisions for resource production and consumption across subplants, storage, and sinks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional control methods are used to manage central plant operations, then system simplicity is maintained, but economic costs cannot be minimized due to inability to optimally allocate energy loads across assets
Solution Approach 1:
The control system is segmented into modular components: configuration tools for system setup, data model extender for adaptive modeling, high-level EMPC algorithm for optimization strategy, and asset allocator for execution. This segmentation allows complex optimization functionality to be implemented while maintaining manageable system architecture and enabling incremental deployment.
Solution Approach 2:
The EMPC tool acts as an intermediary layer between utility pricing signals and central plant assets. It receives real-time pricing data, processes it through optimization algorithms, and generates control decisions that allocate energy loads across chiller subplant, heater subplant, and storage assets, thereby minimizing economic costs without requiring direct complex interactions between all plant components.
2Productivity
If real-time pricing optimization is implemented to minimize economic costs, then energy allocation efficiency improves, but system complexity and difficulty of operation increase
Solution Approach 1:
The EMPC tool implements self-service through automated configuration import from existing plant documentation, automatic data model extension based on detected new entities, and autonomous optimization execution. The system automatically adapts to plant changes and generates control decisions without requiring manual reconfiguration or expert intervention, thereby maintaining ease of operation while achieving sophisticated energy allocation.
Solution Approach 2:
The configuration tools perform preliminary actions by importing plant data and establishing the initial data model structure before optimization begins. The data model extender proactively identifies and defines new entities and relationships in advance, preparing the system for subsequent optimization operations without requiring manual setup during runtime.
3Adaptability or versatility
If existing control methods are used, then implementation simplicity is maintained, but adaptability to new entities and relationships in plant data models is limited
Solution Approach 1:
The data model is implemented as a dynamic structure that automatically extends to accommodate new entities and relationships. The data model extender continuously monitors plant configuration data and adapts the model structure in real-time, allowing the system to evolve with plant changes without requiring manual model updates or reimplementation.
Solution Approach 2:
The EMPC tool provides universal functionality by handling diverse plant configurations through a unified data model framework. The same core optimization algorithm can process different plant types (chiller plants, heater plants, combined systems) and various data structures, making the system broadly adaptable while maintaining consistent implementation procedures.
Data Source
AI summary
Systems and methods for implementing an economic strategy such as a model predictive control (EMPC) strategy. An EMPC tool is configured to present to receive sinks and connections between central plant equipment. The EMPC tool also includes a data model extender configured to extend a data model to define new entities and/or relationships. The EMPC tool also includes a high level EMPC algorithm configured to generate an optimization problem and an asset allocator configured to solve the resource optimization problem in order to determine optimal control decisions used to operate the central plant.