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air energy storage model optimization
A cost-effective two-stage optimization model for microgrid planning and scheduling with compressed air energy storage
This paper proposes a cost-effective two-stage optimization model for microgrid (MG) planning and scheduling with compressed air energy storage (CAES) and preventive maintenance (PM). In the first stage, we develop a two-objective planning model, which consists of power loss and voltage deviation, to determine the optimal
Day-ahead scheduling of air-conditioners based on equivalent energy storage model
Air-conditioners (ACs) can fully utilize the inherent characteristics of storing heat/cold in demand response (DR), achieving peak load shifting and renewable energy consumption. However, traditional control strategies based on compressor ON/OFF state require
A cost-effective two-stage optimization model for microgrid planning and scheduling with compressed air energy storage
This paper proposes a cost-effective two-stage optimization model for microgrid (MG) planning and scheduling with compressed air energy storage (CAES) and preventive maintenance (PM). In the first stage, we develop a two-objective planning model, which consists of power loss and voltage deviation, to determine the optimal location and
Liquid air energy storage technology: a comprehensive review of
Liquid air energy storage (LAES) uses air as both the storage medium and working fluid, and it falls into the broad category of thermo-mechanical energy storage
First and second law analysis and operational mode optimization of the compression process for an advanced adiabatic compressed air energy storage
A complex dynamic model of compression process for CAES was established and tested. • The exergy losses in the compressors are higher than those in the heat exchangers. • Multi-optimization for parametric design was conducted by Genetic Algorithm method.
Energy model optimization for thermal energy storage system integration
This paper presents a dynamic energy model to study the implementation of thermal energy storage (TES) systems in data centres with the objective to reduce the operational expenses. The optimization of the operational conditions of a real 100 IT kW data centre and the storage tank volume was evaluated in function of operational
A new multi-objective optimization model of multi-layer prestressed lining cavern for compressed air energy storage
Underground multi-layer cavern is a key component in the compressed air energy storage (CAES) engineering and its optimal design is of vital importance for improving the CAES efficiency, while most of the optimization models for CAES cavern only have strength index without consideration of economical index. In this study, a finite
Optimal bidding and offering strategies of merchant compressed air energy storage in deregulated electricity market using robust optimization
As one of market players, merchant compressed air energy storage system can be studied to investigate how energy is purchased/sold in the presence of electricity market price uncertainty. Therefore, this paper proposes, robust optimization approach is employed to achieve the offering and bidding curves of compressed air
Compressed Air Energy Storage Models for Energy Arbitrage and
A mixed integer linear programming (MIP) model is developed to simulate the dynamic performance of compressed air energy storage (CAES) systems in
Design and Optimization of PMSM for Compressed Air Energy Storage Based on Mop Model
In order to reduce the torque ripple of the motor for compressed air energy storage and improve the operation efficiency of the motor, an optimization method based on Mop model is proposed. A permanent magnet motor scheme for 1 MW/1500 rpm compressed air energy storage is designed, and the influencing factors of torque ripple
Energies | Free Full-Text | Performance Analysis and Optimization of Compressed Air Energy Storage Integrated with Latent Thermal Energy
In an A-CAES system, thermal energy storage (TES) materials are used to store the compression heat of compressed air during the compression process and release heat to high-pressure air during the expansion process, and
Optimization model for the power system scheduling with wind generation and compressed air energy storage
When energy storage is involved in the power system scheduling, the new challenge is presented as the storage facilities can be considered as either a generator (discharging) or a load (charging). To address this challenge, the paper proposes a method of optimization of power system scheduling with the first generation of compressed air energy storage
Multivariate multi-objective collaborative optimization of pumped
Pumped thermal-liquid air energy storage (PTLAES) is a novel energy storage system with high efficiency and energy density that eliminates large volumes of
Performance Analysis and Optimization of Compressed Air Energy Storage Integrated with Latent Thermal Energy Storage
KW - underground energy storage KW - compressed air energy storage KW - latent thermal energy storage KW - compression waste heat recovery U2 - 10.3390/en17112608 DO - 10.3390/en17112608 M3 - Article SN - 1996-1073 VL - 17 JO - Energies
Model predictive control for the ice-storage air-conditioning system coupled with multi-objective optimization
At the strategy level, a multi-objective global optimization model is established, considering both cost and energy efficiency. This model enables the determination of the optimal load distribution of the chiller and ice storage, which serves as the referenceMPC.
Model predictive control for the ice-storage air-conditioning system coupled with multi-objective optimization
After multi-objective global optimization, the energy consumption in a cycle can be saved by 25 %, and operating cost can be saved by 20.9 %. Therefore, the established multi-objective global optimization model is
Optimizing hybrid power systems with compressed air energy storage
An optimization model is developed here to determine the performance of a hydro-thermal-wind-solar hybrid power system with the possibility of integrating a compressed air energy storage system. The hybrid power system is implemented in the IEEE-30 bus system.
IET Digital Library: Compressed air energy storage system dynamic modelling and simulation
The compressed air energy storage (CAES) system is a very complex system with multi-time-scale physical processes. Following the development of computational technologies, research on CAES system model simulation is becoming more and more important for resolving challenges in system pre-design, optimization, control and implementation.
A New Adiabatic Compressed Air Energy Storage System: Modeling, Design, Optimization
An adiabatic compressed air energy storage (ACAES) system based on the novel compression strategy is proposed to store and release energy when needed to reduce
Numerical study of heterogeneous condensation in the de Laval nozzle to guide the compressor performance optimization in a compressed air energy
Grid 4 is applied to check the condensation models. The GY, FS, YO, PW, blend models have been calculated, and Fig. 4 shows the difference between numerical results and experiential data [50] om Fig. 4, the results can be concluded that the condensation wave appears in the HK, GY, FS, YO, Blend models, as same to the PW
Optimization of data-center immersion cooling using liquid air energy storage
At this point, the minimum outlet temperature of the data center is 7.4 °C, and the temperature range at the data center inlet is −8.4 to 8.8 °C. Additionally, raising the flow rate of the immersion coolant, under identical design conditions, can decrease the temperature increase of the coolant within the data center.
Rolling-horizon dispatch of advanced adiabatic compressed air energy storage based energy hub via data-driven stochastic dynamic programming
Comparison of the compressed air energy storage model and optimization method with dispatch-related studies. Ref. CAES type System SoC model Off-design features Temperature effect method [24] AA-CAES IES Air pressure in AT + heat storage in HTES
Thermo-economic multi-objective optimization of the liquid air
Liquid Air Energy Storage (LAES) is a promising energy storage technology for large-scale application in future energy systems with a higher renewable
Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage
An integrated energy system with compressed air energy storage is proposed. • A game-theoretic method is designed to optimize integrated energy system capacity. • Nash equilibrium is proven to exist and solved by the best response algorithm. •
Thermodynamic analysis and optimization of liquefied air energy storage
Liquefied air energy storage (LAES) technology is a new type of CAES technology with high power storage density, which can solve the problem of large air storage devices that other CAES systems need to configure. In this study, thermodynamic models of the main components of an LAES system are first established, and the main
Optimization model for the power system scheduling with wind generation and compressed air energy storage combination
It is an important schedule parameter which can have effects on benefits of the wind power and energy storage combined system [7,8]. In conventional self-scheduling models for the WF and CAES
Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage
Operation optimization and income distribution model of park integrated energy system with power-to-gas technology and energy storage Journal of Cleaner Production, Volume 247, 2020, Article 119090 Shenbo Yang, , Feng''ao Zhou
[PDF] Comparison of optimization methods for model predictive control: An application to a compressed air energy storage
Different linear and nonlinear optimization methods for model predictive control of energy storage systems are compared to minimize operational costs covering a given 24-hour air demand using a time-sensitive electricity price as an incentive. This thesis compares different linear and nonlinear optimization methods for model predictive control of
A new multi-objective optimization model of multi-layer prestressed lining cavern for compressed air energy storage
A new multi-objective optimization model of multi-layer prestressed lining cavern for compressed air energy storage HUANG Dian-yi()1, MA Yan()1, RAO Qiu-hua()1*, YI Wei() 1*, YANG Wen-tao(), LI Peng()2 1. School of Civil
A new multi-objective optimization model of multi-layer
Underground multi-layer cavern is a key component in the compressed air energy storage (CAES) engineering and its optimal design is of vital importance for
Modeling and dynamic safety control of compressed air energy storage
The control methodology has three factors: (1) dynamics of process system described by the state-space models; (2) safety index from energy process risk analysis; (3) advanced control which takes action to bring the system back to safety operation. (1) The state-space models of process system are obtained from energy and mass balance of
Bi-level optimization design strategy for compressed air energy storage
The air storage tank employs the constant volume model (i.e., volume of the air storage tank has no change). 4) The compressor and turbine use the adiabatic model. 5) Heat loss of the thermal energy storage tank is
Energies | Free Full-Text | Research on Virtual Energy Storage Scheduling Strategy for Air Conditioning Based on Adaptive Thermal Comfort Model
The research on incorporating the characteristics of air conditioning building thermal storage into power grid optimization scheduling mainly focuses on the analysis of user demand response models [13,14,15], applications for different scenarios [16,17,18,193,15,,,
Performance Analysis and Optimization of Compressed Air Energy
The fundamental of the CAES system is that air is compressed to a high-pressure state and stored in underground space or tanks using surplus renewable
Modelling and optimization of liquid air energy storage systems
Currently, cryogenic energy storage (CES), especially liquid air energy storage (LAES), is considered as one of the most attractive grid-scale thermo-mechanical energy storage technologies [1], [2]. In 1998, Mitsubishi Heavy Industries, ltd. designed the first LAES prototype and assessed its application feasibility and practical performance [3] .
Structure optimization and operation characteristics of metal gas storage device based on compressed air energy storage
Introduction The development of renewable energy has received significant attention as a means to reduce carbon emissions and shift away from reliance on fossil fuels [1,2]. Compressed air energy storage (CAES) systems utilize
The optimal design and operation of a hybrid renewable micro-grid with the decoupled liquid air energy storage
Ayele et al. (2019) developed a load flow model based on an extended energy hub approach, and used a nested particle swarm optimization (NPSO) algorithm for the optimization. Buonomano et al. (2014) designed a new HRES and carried out a techno-economic analysis in the TRNSYS (Transient System Simulation) environment.
Multi-factor analysis and optimization design of a cascaded packed-bed thermal storage system coupled with adiabatic compressed air energy storage
In an adiabatic compressed air energy storage (A-CAES), one of the key components is the heat storage system, in which the packed bed filled with encapsulated phase-change capsules has been widely investigated because of
Finite-time thermodynamics modeling and analysis on compressed air energy storage systems with thermal storage
The energy storage and energy release processes of CAES system are only restrained by the balance of total energy and mass [21]. Therefore, the operation of compressed air energy storage system depends on the setting of energy storage time and energy release time generally, according to time-sharing characteristics.
