Cold Storage Tank Research Articles

The influence of uncertainty parameters on the double-layer model predictive control strategy for the collaborative operation of chiller and cold storage tank in data center

The influence of uncertainty parameters on the double-layer model predictive control strategy for the collaborative operation of chiller and cold storage tank in data center

Optimizing supply and production management through energy storage strategies: A solar cold production approach using artificial neural networks

The reliability of clean renewable energy hinges on robust energy systems, with storage serving a critical function. This paper investigates the influence of various storage types and configurations on thermal performance, with a focus on optimal sizing for economic and environmental cost reduction. To achieve this objective, we simulate a solar cooling facility with varied configurations of hot/cold storage installations. This study employs an ANN methodology with a multi-layer perceptron approach to forecast unit performance for each configuration based on data generated during the simulation process. In the pursuit of the most efficient and high-performance network, a comprehensive investigation is conducted on the number of neurons, activation functions, and training algorithms. Subsequently, the optimization process, conducted through a genetic algorithm, determines the Pareto fronts representing the best solution sets. The comparison shows that a system design with double hot and cold storage tanks shows superior techno-economic-environmental performance. Among possible optimum solution sets, a point with this specification is selected; flow rate ratio, minimum flow ratio, cooling capacity ratio, cold storage ratio, and hot storage ratio of 1.2, 0.4, 0.91, 3.4, and 3.8, respectively. This configuration anticipates a levelized cost of cooling at 341 USD/MWhr, representing a 13 % reduction compared to the benchmark.

Impact of nano-powders on conduction mechanism during solidification through cold storage tank

In this article, numerical modeling with the aim of decreasing the solidification time is presented. The solidification process is primarily influenced by conduction, leading to the application of two techniques aimed at enhancing this mechanism: the install of fins and the addition of nano-powders. Various shapes and fractions of alumina nanoparticles are introduced into the H2O to accelerate the solidification. To predict the properties of the nanoparticle-infused mixture, single-phase formulations are employed. The Finite Element Method (FEM) is then hired to model the system, with an adaptive grid implemented to enhance accuracy. Validation against previous works demonstrates the capability of the developed code for the present study. The incorporation of nanoparticles results in a significant 32.7 % increase in the freezing rate, highlighting the effectiveness of this approach. Additionally, altering the shape of the nanoparticles can further increase the process rate by approximately 10.73 %. The transition from a water-based system to one infused with nanomaterials leads to a notable decrement in freezing time, from 957.64 s to 6447.35 s. These outputs emphasize the potential of nanomaterial-enhanced cold energy storage systems to significantly improve efficiency and performance. In summary, the study showcases the effectiveness of numerical simulation in optimizing cold energy saving processes through the strategic utilization of nanoparticles.

Comparative analysis of charging and discharging characteristics in novel cold and hot simultaneous energy storage tanks

Energy storage technology is instrumental in reducing energy costs and crucial for balancing demand and supply. This study proposes a cold and hot simultaneous energy storage tank (CAHSEST) for the first time, although its heat transfer characteristics are not yet clear. The objective is to explore the heat transfer properties of CAHSEST. Utilizing computational fluid dynamics (CFD) software, three-dimensional models for five distinct tanks were developed and comparative analyses were performed focusing on temperature distribution, velocity distribution, thermocline thickness and storage efficiency. The findings indicate that tanks with separated cold and hot water (cases 3–5) exhibit significantly better stratification than those with mixed water (cases 1 and 2), showing higher energy storage efficiency. At a heating time of 3600 s, cases 3 and 5 shows higher heat charging efficiency than other cases. In addition, case 3 achieves the highest cold discharging efficiency of 90.25 %, whereas case 2 has the lowest, at only 15.94 %. Overall, case 3 emerges as the optimal configuration. This research offers technical assistance for the design and understanding heat transfer characteristics of CAHSEST, and provides new directions for achieving long-term heat storage and short-term cold storage.

Thermo-economic analysis of a pumped thermal energy storage combining cooling, heating and power system coupled with photovoltaic thermal collector: Exploration of low-grade thermal energy storage

As renewable energy penetration grows, traditional power systems face significant challenges due to their intermittency and volatility. Pumped thermal energy storage (PTES) is a potential energy storage technology that has a low specific cost and geographical restriction. In this paper, a PTES system which is coupled with solar photovoltaic thermal (PVT) collectors is proposed to satisfy the demand for cooling, heating and electricity supply, and achieve energy cascade utilization. An ejector refrigeration cycle and the turbine extraction heating are accompanied with a PTES system. Thermodynamic analysis of the system is performed by evaluating the influence of key parameters on system performances for 1 MW power output. The economic analysis adopted levelized cost of energy storage (LCOS), which mainly includes investment costs, operation and maintenance costs and system depreciation. The results show that the maximum amplification of roundtrip efficiency with PVT is 12.04 % compared to the system without PVT. Moreover, the maximum average power generation benefit of PVT is 4.85 %. The increase in cold energy storage tank temperature can effectively improve the roundtrip efficiency of the system. The lower cold energy storage tank temperature and higher hot energy storage tank temperature have a negative impact on system thermal efficiency (ηthermal) but benefits for LCOS. Multi-objective optimization is carried out to obtain the optimal design performance that ηthermal and LCOS are 51.06 % and 0.533$/kWh respectively.

The SPARC cryogenic system

The SPARC project at Commonwealth Fusion Systems (CFS) is a tokamak system designed to demonstrate commercially relevant fusion energy and achieve net fusion power output during the first operating campaign, with eventual fusion pulse energies exceeding 1 GJ. The SPARC tokamak includes eight magnet systems, three that use high-temperature superconducting (HTS) tapes. The SPARC cryogenic system (CRYO) consists of three supercritical helium cryogenic loops at nominal temperatures of 8 K, 15 K, and 80 K. CRYO 8 K and 15 K loops cool the HTS magnets to maintain thermal stability and prevent quench, while magnets cooled to 80 K are normally conductive. CRYO provides cold helium using a hybrid system that includes a Brayton-cycle-based cryoplant supporting all CRYO temperature loops, and a fixed volume 8 K blowdown system to remove heat and maintain temperature stability of the toroidal field (TF) magnets during and immediately following fusion pulses. CRYO 4.5 K equivalent peak cooling power is 17 kW for the cryoplant and 2.9 MW for the blowdown system during a 10-second fusion pulse. Primary cryoplant mechanical equipment includes screw compressors, turbo-expanders, heat exchangers, and circulation pumps, while the blowdown system consists of a series of warm and cold helium storage tanks operating at independent temperatures and pressures, with make-up compressors to reset the blowdown system between pulses. CRYO also includes a distribution valve box and multiple vacuum-jacketed (VJ) process lines ranging in nominal diameter from 20 to 600 mm. This paper investigates the various sub-elements which in combination represent SPARC CRYO, and attempts to address some of the technical challenges identified by the team.

Research on the Cold Storage Characteristics of Ice Storage Photovoltaic Cold Storage

The ice-on-coil storage tank is one of the core devices in the latent heat cold storage system. The main objective of this study is to couple the solar photovoltaic cold storage with Cold Thermal Energy Storage technology. The internal ice-melting coil energy storage system used the water as a heat transfer fluid for adopting a day and night cold storage control strategy. The experiments were conducted for several days under the conditions of photovoltaic-driven cold storage with and without load for a continuous cold storage. The reasons for the occurrence of ice layers during ice accumulation and melting, as well as the operational economy of the system were analyzed. Moreover, the characteristics of the cold storage tank were summarized. Consequently, when the external ice thickness of the coil was within the range of 27 to 32mm, the ice storage rate reached 35.82% and achieved the optimal refrigeration efficiency in both the coil and the cold storage. The daily ice production in the cold storage tank decreased by an average of 22.06% during continuous operation with load compared to the unloaded operation. However, the daily refrigeration capacity increased by 45.774%. In addition, when cold thermal energy storage was coupled with solar photovoltaic technology, the refrigeration capacity decreased by 7.15% compared to using Cold Thermal Energy Storage technology alone, which resulting in an annual electricity cost saving of 30.20%.

Hybrid energy storage configuration method for wind power microgrid based on EMD decomposition and two-stage robust approach

Data centers are usually characterized by high energy loads, which raises increasing sustainability concerns in both academic and daily usage. To mitigate the uncertainty and high volatility of distributed wind energy generation, this paper proposes a hybrid energy storage allocation strategy by means of the Empirical Mode Decomposition (EMD) technique and the two-stage robust method. First, this paper conducts the evolution analyses for the over- and under-evaluated uncertainty of wind power fluctuation under different time scales. Second, we employ the EMD technique to configure a high-frequency flywheel energy storage device, realizing the wind power transformation from large fluctuations to small fluctuations and the convergence of the wind power fluctuation curves in minute- and hour levels. Finally, based on the hour-level wind energy stable power curves, we carry out two-stage robust planning for the equipment capacity of low-frequency cold storage tanks and lithium bromide chillers. The case study on a data center microgrid in northeastern China confirms the effectiveness of our proposed strategy.

An advanced control strategy of hybrid cooling system with cold water storage system in data center

The inefficient operation of cooling equipment is a significant impact factor to the high energy consumption of cooling system in data center. This study proposes an advanced model predictive control (MPC) strategy for a hybrid cooling with water storage system to improve energy efficiency and reduce the accumulation of cold storage losses. Mixed integer linear programming (MILP) in MPC strategy is used to optimize the operating parameters under free cooling, hybrid cooling, and mechanical cooling modes, further solving the problem of precise optimization for different modes. Taking Guangzhou city as an example, the equipment scheduling and the appropriate volume of cold water storage tank for MPC strategy are analyzed. The results indicate that, the emergency cold water storage tank 500 m3 only supports the efficient operation of cooling system under the maximum 60 % IT load rate, meanwhile, the optimal tank volume 1400 m3 could meet the 60–100 % IT load rate. Compared to Baseline strategy, the biggest reduction of annual energy consumption using MPC strategy would be attained by 12.19 % under free cooling mode, by 4.04 % under hybrid cooling mode, and by 22.15 % under mechanical cooling conditions at the 55 % IT load rate. Therefore, the MPC strategy proposed in this paper has important guiding significance for energy conservation and carbon reduction in global data centers.

Evaluations of low-temperature mechanical properties and full-range constitutive models of AA 5083-H112/6061-T6

The low-temperature mechanical properties of aluminium alloys (AAs) are important for the analysis and design of infrastructures in cold regions and LNG storage tanks made of AAs. This paper investigated the stress-strain behaviours of AA 5083-H112/6061-T6 materials through conducting tensile tests on 32 AA coupons at 20 ℃ ∼ −165 ℃. All the tested AA coupons exhibited ductile failure modes. Their results showed that the stress-strain curves of AA 5083-H112 exhibited the Portevin-Le Chatelier effects that gradually weakened with the decreasing temperature. Reducing the temperature from 20 ℃ to −165 ℃ increased the elastic modulus, yield and ultimate strengths of AA 5083-H112 (or 6061-T6) by 5.1% (6.5%), 8.7% (12.0%) and 7.8% (13.1%), but reduced the fracture strain by 16.4% (12.4%). The fracture surfaces of all AA 5083-H112 and 6061-T6 coupons displayed localised cross-sectional area reductions and substantial plastic deformation. Meanwhile, precipitation-hardened AA 6061-T6 exhibits a more pronounced enhancement compared to strain-hardened AA 5083-H112. Furthermore, regression analyses were performed to establish prediction equations for the low-temperature mechanical indexes of AAs. Subsequently, a full-range constitutive model was proposed to estimate the stress-strain behaviours of AA 5083-H112 and 6061-T6. Validations against reported experimental observations demonstrated that the developed model reasonably described the stress-strain responses of AA 5083-H112 and 6061-T6 from 20 ℃ to −165 ℃.

Triple-objective MPSO of zeotropic-fluid solar ejector cycle integrated with cold storage tank based on techno-economic criteria

The current study objective is to optimize the integration of a solar ejector cycle with cold storage by applying a multi-objective modified particle swarm optimization technique. Various collector and working fluid's effects are evaluated on dynamic system behavior, which zeotropic fluid and parabolic trough collector have been the most effective choices. Hot and cold storage tanks are applied to overcome the instability of solar energy and ensure sustainable access to produced cold. Design parameter's optimum values are estimated through sensitivity analysis and genetic algorithm optimization which are decreased up to 70% compared to initial guesses. An artificial neural network is employed to train exergo-economic-environmental data which fed into the multi-objective modified particle swarm optimization algorithm. With using of cold storage tank, the system's coefficient of performance is enhanced up to three times compared to the ejector cycle at optimum design variable. By employing of parabolic trough collector, the system has its maximum coefficient of performance and exergy efficiency, as well as the minimum size of the ejector cycle and cold storage tank. The parabolic trough collector, air handling unit, and cold storage tank waste over 80% of the overall system's exergy. The payback period of system is estimated about 3.5 years.

Cold water storage tank enhancement using response surface methodology leading cooling peak shaving along with load shifting

In hot areas, electricity consumption in the cooling sector holds 66% of the electricity usage by residential buildings. The need for electricity during peak times causes various problems in the electricity supply network. Adding a cold water storage tank can achieve two goals: 1- peak load shifting and 2- peak load shaving. In this study, first, the volume of the storage tank was calculated by energy analysis for the day with the maximum cooling needs. Owing to installing the tank, the electricity consumption not only reaches zero during the peak time (7 a.m.–11 p.m.) but also the total electricity demand decreases by 5.1%. According to the ASHRAE, throughout the 8760 h in one year, the deviation of the interior temperature from the setpoint should not exceed the 300-h threshold (i.e., unmet hours <300 h). Considering the allowable amount of unmet hours as a constraint, optimal points were acquired using Response Surface Methodology (RSM). This method reduces the cold storage tank by 40% and decreases the electricity need by 16.5% compared to the reference case (without a storage tank). Furthermore, the optimal storage tank eliminates the cooling-associated electricity demand to zero during peak periods.

On-site solar PV generation and use: Self-consumption and self-sufficiency

As energy storage systems are typically not installed with residential solar photovoltaic (PV) systems, any “excess” solar energy exceeding the house load remains unharvested or is exported to the grid. This paper introduces an approach towards a system design for improved PV self-consumption and self-sufficiency. As a result, a polyvalent heat pump, offering heating, cooling and domestic hot water, is considered alongside water storage tanks and batteries. Our method of system analysis begins with annual hourly thermal loads for heating and cooling a typical Australian house in Geelong, Victoria. These hourly heating and cooling loads are determined using Transient System Simulation (TRNSYS) software. The house’s annual hourly electricity consumption is analysed using smart meter data downloaded from the power supplier and PV generation data measured with a PV system controller. The results reveal that the proposed system could increase PV self-consumption and self-sufficiency to 41.96% and 86.34%, respectively, resulting in the annual imported energy being reduced by about 74%. The paper also provides sensitivity analyses for the hot and cold storage tank sizes, the coefficient of performance of the heat pump, solar PV and battery sizes. After establishing the limits of thermal storage size, a significant impact on self-efficiency can be realised through battery storage. This study demonstrates the feasibility of using a polyvalent heat pump together with water storage tanks and, ultimately, batteries to increase PV self-consumption and self-sufficiency. Future work will concentrate on determining a best-fit approach to system sizing embedded within the TRNSYS simulation tool.

Thermo-economic assessment of sub-ambient temperature pumped-thermal electricity storage integrated with external heat sources

Thermally integrated pumped-thermal electricity storage (TI-PTES) offers the opportunity to store electricity as thermal exergy at a large scale, and existing studies are primarily focused on TI-PTES systems based on high-temperature thermal energy storage. This paper presents a thermo-economic analysis of a “cold TI-PTES” system which converts electricity into cold energy using a vapor compression refrigeration (VCR) unit and stores it at sub-ambient temperatures during the charging process, and generates electricity by using an organic Rankine cycle (ORC) working between the sub-ambient temperature and an external low-grade heat source during the discharging process. The effects of key parameters, i.e., mass flowrate and temperature of the storage medium, ORC evaporation temperature, component efficiencies, and pinch-point temperature differences, on the system performance are evaluated based on a whole-system thermo-economic model. The results reveal that the roundtrip efficiency and levelized cost of storage (LCOS) of the system increases while the electrical energy storage capacity decreases as the temperatures of the two cold storage tanks approach each other. When the temperature of the cold storage tank 1 rises from 1 °C to 8 °C while the cold storage tank 2 remains as 13 °C, there is an increase of 25% and 20% in the roundtrip efficiency and LCOS respectively while the energy storage capacity decreases by 69%. A roundtrip efficiency of 0.74 and LCOS of 0.32 $/kWh are achieved with a heat source temperature of 85 °C, using a mass flowrate and temperature of the cold storage medium of 50 kg/s and 1 °C. Furthermore, any change in cold storage medium mass flowrate changes both electrical energy storage capacity and power output by the same proportions. With a continuous high-flowrate external heat source, the LCOS can be as low as 0.17 $/kWh. By providing sufficient heat from an external heat source, the proposed system possesses a high potential for medium-to-large scale energy storage with a unique hybrid nature for electricity storage and thermal integration.

Thermal Analysis of Absorption Air Conditioning Cycle Using Glycerin in Hot and Cold Storage Tanks

Increasing demand for cooling operations in the oil and other sectors, this has led to an increase in electrical energy consumption. The most sustainable solution is to use absorption cooling technology by utilizing solar heat as driving energy instead of electricity. The primary advantage of absorptive cooling is lower electricity costs. In this study, the effect of changing the thermal storage capacities of hot and cold storage tanks and the solar collector area on the performance of the absorption air conditioning cycle was investigated. The optimum operating conditions, the maximum number of processing hours, and the optimum performance coefficient of the absorption conditioning cycle system were selected. The water-lithium bromide solution was used as a fluid in the sorption cycle, and glycerin was used in the hot and cold tank cycle and in the solar collector because it can with stands both high and low temperatures. The simulation process was carried out using (Fortran 90) program with the help of (Port log) program, (Carrier HAP420) program and (Curve Expert) program. The absorption conditioning cycle was simulated during the day to choose the best capacity for hot and cold storage tanks, as well as to choose the solar collector with the best performance factor. Changing the area of the solar collector (from 9.6 m2 to 16.7 m2), and the volume of the hot tank (from 0.55 m3 to 1.4 m3) have been done to provide the maximum temperature that the hot tank can reach with varying expected cooling load per hour, as well as the size of the tank cold (from 0.9 m3 to 1.6 m3) which gets additional cooling capacity, since the effect of these variables was tested separately. According to the research results, the best and most suitable volume for the hot tank is (0.55 m3), and for the cold tank is (1.5 m3), and the best and appropriate area for a solar concentric collector is (11.7 m2), which can provide longer running hours. Finally, the higher the generator's temperature, the higher the system's coefficient of performance (COP). The lowest COP value (0.68) is used to guarantee that the system runs for longer periods of time.

A model for energy master planning and resilience assessment of net-zero emissions community

ABSTRACT New community-scale developments should address both greenhouse gas emissions mitigation and climate adaptation goals. This paper presents a systematic approach to energy master planning (EMP) of net-zero emissions communities via probabilistic analysis of the resilience and cost effectiveness of various energy provision portfolios (supply, conversion and storage) in early design stage. Applied in the EMP of a new university satellite campus, comprising of five buildings with mixed energy uses, both the 2050 net-zero emissions and the energy resilience objectives are met by an energy provision portfolio that consists of air source heat pumps for heating and cooling, and a combination of PV panels, purchased green power, standard (non-green) grid power, battery and thermal heat and cold storage tanks – with only a modest 6% increase in costs compared to a reference solution. The case project demonstrates the financial feasibility of a resilient energy system that also meets a net-zero emissions objective.

Collaborative optimization method and energy-saving, carbon-abatement potential evaluation for nearly-zero energy community supply system with different scenarios

As a typical representative of a green and low-carbon community, a nearly-zero energy community is the main development direction of future building forms. Therefore, to improve the proportion of renewable energy and reduce primary energy consumption and carbon emissions, this paper constructed a nearly-zero energy community supply system, including the battery, heat storage tank, and cold storage tank. A multi-parameter collaborative optimization model considering system design and operation was established to improve the economy, energy-saving, and carbon-abatement potential of the system. This paper took a nearly-zero energy community to study the influence of different electric vehicle numbers on typical daily energy balance, energy-saving, and carbon-abatement potential of the nearly-zero energy community supply system. The results showed that when the number of electric vehicles increased from 0 to 600, the zero energy potential, primary energy saving rate, and carbon emission reduction rate of the nearly-zero energy community supply system decreased by 6.8%, 2.6%, and 1.8%, respectively. The cost per unit supply area increased by 7.8CNY/m2, and the annual cost saving rate increased by 29.7%. The system's optimization design method and energy-saving and carbon-abatement potential evaluation result provided a valuable reference for the integrated building and transportation sector development.

Selecting rock types for very-low-cost crushed rock heat storage systems with nitrate salt heat transfer

Today the demand for variable electricity is met by fossil-fuel power plants because the capital costs and the cost of storing fossil fuels are very low. A low-carbon grid requires replacements for stored fossil fuels to provide variable heat and electricity as needed. The thermal energy replacement option is to send heat from nuclear and concentrated solar power (CSP) plants operating at full capacity to heat storage with variable heat output to the power block to provide variable electricity to the grid. Very low-priced electricity from wind and solar can also be converted into stored heat. Today the lowest-cost commercial heat storage systems are in CSP plants and use nitrate salt stored in hot and cold storage tanks. Advanced heat storage systems use nitrate salt for heat transfer but replace some or all the nitrate salt with lower cost crushed rock for heat storage. These systems may lower the capital cost of heat storage by a factor of five or more to several dollars per kWh of stored heat. Locally acquired crushed rock is the lowest-cost heat-storage material but not all rock is compatible with heat storage requirements including chemical compatibility, mechanical properties, and durability under thermal cycling. Rocks have been sorted into categories likely, possibly, and unsuitable and the basis for these conclusions has been documented. Potentially suitable rock types include basalt, peridotite, taconite, quartzite, quartzitic sandstone and serpentinite. Except for taconite, sedimentary rocks are unlikely to be suitable for service.

Optimal Design of Cryogenic Insulation System for Large Liquefied Natural Gas (LNG) Storage Tanks Based on Operation Factors

Liquefied natural gas (LNG), as a recognized clean energy, has seen a rapid increase in global consumption in recent years. As the core equipment of the LNG receiving terminal, the large LNG storage tanks, its’ cryogenic insulation system design is particularly important. The insulation system is mainly used to maximize the control of the daily evaporation of cold storage tanks, so as to achieve long-term storage of LNG in the tank. Its design is particularly important. At present, the internal design of the industry often only considers the construction conditions, without comprehensive consideration of operation, maintenance and other full-life cycle conditions. This paper analyzes and optimizes the design of the insulation system of large LNG storage tanks from the aspects of the performance of the insulation material itself, the construction period, pre-cooling start-up, operation and maintenance and other comprehensive operating factors. And taking the 30,000 m3 LNG storage tanks as an example, through the analysis and comparison of some columns, obtained the optimal daily evaporation rate requirements of the insulation system, which can be used as a reference for the design of LNG projects during the construction period.

Novel optimized hybrid neuro-fuzzy approach for analysis of cold thermal storage system-assisted air conditioning system performance

HVAC (Heating, ventilation, and air conditioning) systems can be used as a basic flexible load to provide approximately 20% of a building's energy demand and possess the capacity to transfer energy. Effective cooling load forecasting is one of the most important methods for achieving energy savings in buildings. This study proposes a Heap Optimization Based Generalized Intelligent Neural Fuzzy Control (HO-GINFC) for estimating the cooling load of an air conditioning system with cold thermal storage. It was primarily utilized to research historical meteorological data on cooling load. Using the quantitative data of a massive Saudi Arabian commercial structure, the model is validated. Using the HO algorithm, the performance of GINFC is optimized. Additionally, the cold storage tank's maximum capacity can be reached. Moreover, the results demonstrated that the HO-GINFC model accurately predicted the CV-RMSE (coefficient of variation of the root mean squared error), MSE (Mean Square Error), MAE (mean absolute error), R2 (squared correlation coefficient), and RMSE (root mean squared error) values to be 2.107%, 100%, 0.258%, 0.992%, and 1.058%, respectively. Comparative studies demonstrate that the HO-GINFC model outperforms neural networks in terms of prediction accuracy, execution speed, and resiliency when dealing with a large number of samples. The predictions of the model proposed in this work provide significant technical support for computing rising energy demands and can be implemented in actual engineering.