Central Plant Asset Allocation Override for Real-Time Energy Pricing
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Solution Overview
Problem
Central plants face challenges in optimally allocating energy loads across various subplants due to real-time pricing from utilities, making it difficult to determine the optimal time for producing and consuming resources to minimize costs.
Innovation Solution
A controller with a processing circuit that performs optimization subject to override constraints to determine resource production amounts, allowing users to override certain production levels while presenting cost impacts, thereby optimizing total cost or resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the central plant optimizes resource production timing to minimize costs under real-time pricing, then economic efficiency is improved, but the complexity of determining optimal allocation increases
Solution Approach 1:
The system performs preliminary optimization calculations to determine the optimal allocation of energy loads across subplants before real-time operation. By pre-calculating the optimal production timing and resource allocation based on forecasted pricing and load patterns, the system reduces real-time decision complexity while maintaining economic efficiency.
Solution Approach 2:
The patent introduces an asset allocator as an intermediary component that mediates between the complex optimization problem and the control system. This intermediary translates complex optimization calculations into actionable allocation decisions, simplifying the overall system architecture while enabling sophisticated cost optimization.
2Adaptability or versatility
If the system allows user override of optimization outputs, then operational flexibility is improved, but the automated optimization effectiveness may be reduced
Solution Approach 1:
The system dynamically adjusts between automated optimization and user override modes. The override mechanism allows users to modify optimization outputs when operational considerations require deviation from purely cost-based decisions, while the system remains primarily automated. This dynamic adaptability resolves the contradiction by allowing both high automation and user flexibility.
Data Source
AI summary
A controller for building equipment that operate to produce or consume resources for a building or campus. The controller performs an optimization of an objective function subject to an override constraint to determine values for a plurality of decision variables indicating amounts of resources to be produced or consumed by the building equipment. The override constraint defines one or more of the values for a subset of the plurality of decision variables by specifying an override amount of a first resource of the resources to be produced or consumed by a first subset of the building equipment and the optimization determines a remainder of the values for a remainder of the plurality of decision variables. The controller controls the building equipment to produce or consume the amounts of the resources determined by performing the optimization subject to the override constraint.