Cooling Plant Thermal Storage Scheduling Optimization
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Solution Overview
Problem
Existing cooling systems face challenges in efficiently managing time-varying cooling demands and underutilization of thermal ice storage systems due to conservative scheduling methods and oversimplification of chiller operation modes, leading to increased costs and reliability concerns.
Innovation Solution
A cooling plant system incorporating thermal and electrical energy storage systems, coupled with an energy storage and scheduling control system that optimizes operations through a scheduling module, providing selective electrical energy to thermal energy storage systems and enabling frequency regulation and contingency reserve services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple resources are used to meet cooling demand, then reliability is improved, but operating cost increases
Solution Approach 1:
The system pre-charges thermal energy storage systems during low-demand periods when electricity prices are lower, storing cooling capacity in advance. This preliminary action allows the system to meet peak cooling demands using stored energy rather than activating additional resources, thereby maintaining reliability while reducing operating costs during high-demand periods.
2Use of energy by moving object
If thermal ice storage systems are used to assist chillers, then economic viability is improved, but system complexity increases
Solution Approach 1:
The system merges thermal energy storage systems with the existing chiller infrastructure into an integrated cooling plant. The control system coordinates operation between chillers and thermal storage, allowing them to work as a unified system rather than separate components. This combination achieves economic benefits through optimized resource utilization while managing complexity through integrated control architecture.
Solution Approach 2:
The thermal energy storage systems serve multiple functions: they provide auxiliary cooling capacity during peak periods, store energy for economic operation during low-price periods, and can be charged using waste heat from chiller operations. This multi-functionality justifies the added complexity by delivering multiple benefits from a single system component.
3Reliability
If conservative scheduling algorithms are used for thermal ice storage systems, then reliability is improved, but underutilisation occurs
Solution Approach 1:
The control system implements feedback mechanisms that continuously monitor cooling demand patterns, thermal storage state of charge, and electricity pricing signals. Based on this real-time feedback, the system dynamically adjusts charging and discharging schedules, enabling more aggressive and optimized utilization of thermal storage while maintaining reliability constraints. This feedback-driven approach replaces conservative static scheduling with adaptive dynamic scheduling.
Solution Approach 2:
The system transitions from static, conservative scheduling algorithms to dynamic scheduling that adapts to real-time conditions. The control strategy continuously optimizes thermal storage utilization based on varying cooling demands, electricity prices, and system state, allowing the system to exploit storage capacity more fully while maintaining reliability through real-time adjustments rather than fixed conservative rules.
4Device complexity
If chiller scheduling assumes only two working modes, then device complexity is reduced, but productivity is limited
Solution Approach 1:
The chiller operation is segmented into multiple discrete modes (e.g., full cooling, partial cooling, heating-only, idle) rather than treating it as a continuous two-state system. This segmentation allows the control system to select from a richer set of operational states, improving productivity and flexibility in meeting varying cooling demands while maintaining manageable scheduling complexity through discrete mode transitions.
Solution Approach 2:
The system changes the operational parameters of chillers beyond simple on/off states, including variable cooling capacity levels, variable heating capacity levels, and different operational modes (cooling vs. heating). These parameter changes enable more flexible and productive chiller operation while the control system manages the increased complexity through structured parameter management and mode-based control strategies.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enhances economic viability and reliability by optimizing energy usage, reducing operational costs, and effectively managing peak demands through advanced scheduling and energy storage strategies.
Implementation Method 1
one or more thermal energy storage systems coupled to the one or more cooling towers
Implementation Method 2
thermal ice storage systems (ISSs; a type of thermal storage system)
Implementation Method 3
one or more electrical energy storage systems, the one or more electrical energy storage systems being coupled to the one or more thermal energy storage systems for selectively providing electrical energy
Data Source
AI summary
The present disclosure may provide a cooling plant system, a method of operating a cooling plant system and an energy storage and scheduling control system, the cooling plant system comprising one or more cooling towers; one or more thermal energy storage systems coupled to the one or more cooling towers; one or more electrical energy storage systems, the one or more electrical energy storage systems being coupled to the one or more thermal energy storage systems for selectively providing electrical energy to the one or more thermal energy storage systems; and an energy storage and scheduling control system coupled to the one or more thermal energy storage systems and the one or more electrical energy storage systems.