Hybrid Thermal System Controller Allocation Optimization
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Solution Overview
Problem
Hybrid thermal systems face challenges in efficiently distributing thermal energy loads across multiple generators to minimize costs and carbon emissions, especially under dynamic conditions and varying resource availability.
Innovation Solution
A method for controlling a hybrid thermal system that involves predicting thermal energy demand, allocating it between multiple thermal energy generators, and continuously correcting the allocation based on actual conditions to optimize parameters such as carbon emissions and resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If thermal energy demand is allocated between multiple generators to minimize carbon emissions, then environmental performance is improved, but system complexity increases due to dynamic conditions and varying resource availability
Solution Approach 1:
The controller determines an initial allocation of thermal energy demand between multiple generators over a future time period before operation begins. This preliminary allocation optimizes carbon emissions by considering predicted demand and resource availability in advance, avoiding the need for complex real-time adjustments during operation.
Solution Approach 2:
The controller periodically verifies the feasibility of the previously determined allocation by estimating remaining thermal energy demand and comparing it against the allocated capacity. When verification fails, the controller corrects the allocation for the remainder of the time period, providing feedback-based optimization that maintains simplicity while adapting to changing conditions.
2Duration of action of moving object
If thermal energy demand is allocated to optimize long-term performance, then resource management is improved, but short-term performance may be compromised
Solution Approach 1:
The controller determines an allocation of thermal energy demand over a future time period in advance, optimizing resource management for the entire period rather than making short-sighted decisions. This preliminary planning ensures long-term performance by considering the complete time horizon and resource availability.
Solution Approach 2:
The controller verifies feasibility of the allocation and corrects it beforehand if critical situations are predicted. By identifying and addressing potential shortfalls before they occur, the system cushions against future performance degradation while maintaining optimal long-term resource management.
3Adaptability or versatility
If the controller continuously adjusts allocation based on actual conditions, then adaptability is improved, but computational complexity increases
Solution Approach 1:
The controller periodically repeats the verification and correction steps at predetermined intervals rather than continuously adjusting allocation. This periodic approach maintains adaptability by regularly checking feasibility and correcting deviations, while significantly reducing computational complexity compared to continuous real-time optimization.
Solution Approach 2:
The controller determines an initial allocation over the entire future time period in advance, providing a comprehensive plan that reduces the need for frequent adjustments. This preliminary determination captures most optimization opportunities upfront, making subsequent periodic corrections simpler and less computationally intensive.
Data Source
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AI summary
Method for controlling a hybrid thermal system (10) having a plurality of thermal energy generators and using various resources for producing thermal energy and a controller (3) for individually controlling operation of each thermal energy generator of said plurality of thermal energy generators, the plurality of thermal energy generators comprising a first thermal energy generator (1) using a first resource and a second thermal energy generator (2) using a second resource different from the first resource, the method comprising the steps of obtaining a predicted thermal energy demand to be satisfied by the hybrid thermal system (10) over a future time period; determining an allocation of said predicted thermal energy demand between the plurality of thermal energy generators of said thermal energy system (10) over said future time period in order to optimize a parameter (FP) associated with operation of the hybrid thermal system (10); operating said hybrid thermal system (10) during said time period, by: 1) individually controlling each thermal energy generator of said plurality of thermal energy generators according to the determined allocation in order to satisfy an instant thermal energy demand; 2) estimating a remaining thermal energy demand of said predicted thermal energy demand to be satisfied by the hybrid thermal system (10) over the remainder of said time period and verifying the feasibility of the previously determined allocation for satisfying said remaining thermal energy demand; 3) if said verifying is negative, correcting the previously determined allocation for said remainder of said time period in order to satisfy said remaining thermal energy demand while optimizing said parameter (FP) associated with operation of the hybrid thermal system (10) over said remainder of said time period; 4) periodically repeating steps 1) to 3) above until the end of said time period. Controller (3) and hybrid thermal system (10) implementing the method.