Optimization Of Thermal Energy Storage Research Articles

Optimization of thermal energy storage: Evaluation of natural convection and melting-solidification time of eccentricity for a rotational shell-and-tube unit

Changing the eccentricity between outer and inner tubes in horizontal shell-and-tube unit during phase change of the heat storage medium is an economical procedure to improve overall heat transfer. However, because of the reverse effect of a fixed eccentric structure (downward or upward) on melting and solidification processes, investigators in previous studies have only examined the potential of performance improvement separately. Finding a technical approach to ensure lower times for melting and solidification in the fixed eccentric structure can yield significant benefits. This study numerically evaluates the processes of melting and solidification in the eccentric design for a shell-and-tube unit concurrently based on the second law of thermodynamics and natural convection. Based on the second law of thermodynamics analysis confirms that natural convection can be analyzed using the fractional entropy generation. The results show that downward eccentric designs enhance natural convection during the process of melting in stationary units. Solidification results show the significance of natural convection in the primary stage of the process. Melting time decreases by 71 % in the case with the eccentric number of 0.4 whereas solidification time decreases in upper eccentric cases (eccentric number of <0.1 in the stationary units). Reduction in solidification time by 13 % is demonstrated with the eccentric number of 0.05 and the diameter ratio of 2.52. This study presents a novel and applicable method (180-degree rotation) to achieve a shorter melting-solidification time in eccentric configurations. Additionally, a rotational mechanism is investigated to reduce the total melting-solidification time.

Sizing and control optimization of thermal energy storage in a solar district heating system

Solar district heating systems have shown significant promise to facilitate the large scale adoption of solar energy technologies and thus substantially reduce greenhouse gas emissions. Given the mismatch between solar energy and district heating demand, energy storage devices play a critical role given their capacity to stockpile solar energy in both the short-term (hours to days) and long-term (months). However, the integration, sizing and control of energy storage technologies is far from simple. This paper investigates sizing and controlling thermal energy storage from the perspective of its performance within a district heating system, highlighting the close link between design and control. A 52-house Canadian solar district heating system, the Drake Landing Solar Community (DLSC), was used as a case study. This system uses solar collectors as main energy supply, borehole thermal energy storage (BTES) for seasonal storage and two 120-m3 water tanks for short-term thermal storage (STTS).The effect of (a) storage sizing (STTS volume) and (b) storage control (rate at which energy is either injected or extracted from the BTES) was evaluated. A control-oriented model, calibrated and validated with operational data at 10-min intervals, was used along with an optimal rule-based control to gauge system primary energy use. Different scenarios were tested, with STTS volumes ranging from 120 m3 to 480 m3, and BTES loop nominal flow rates between 2.5 and 4.5 L/s. An optimization routine was developed to calculate the optimum parameters of the rule-based control strategy. Results show that, in comparison with the design and control in place, primary energy savings of 13%–30% (with BTES flow rates of 2.5–4.5 L/s) could have been obtained with the proposed rule-based control strategy. By decreasing the STTS volume to 120-m3, energy savings up to 6% could still be achieved; savings could reach 27%–36% by increasing the STTS size to 360-m3.

Strategic control and cost optimization of thermal energy storage in buildings using EnergyPlus

An operational strategy to optimize building operating energy costs for suppliers and consumers is an important challenge for electrical power utilities. There are various supply-side measures that utilities have to take to ensure continuous energy supply for building heating and air-conditioning. During peak energy demand, utilities are often forced to use more expensive and less efficient generation, thereby increasing the cost of energy. However, some demand-side management practices behind the consumer meter can help in meeting this challenge. One such measure is the use of thermal storage for heating, ventilation, and air-conditioning applications in commercial buildings. There is a gap of adequate knowledge of an optimal control strategy of cold storage operation in buildings adapting to applicable time of day tariffs to minimize annual energy use and annual energy cost of operation. There is also a need to use commercially available tools to avoid the use of complex mathematical models. This study demonstrates strategic controls with six operating modes for using thermal energy storage to shift peak electricity demand, using the time of day tariffs as a decision variable, and reducing operating costs, while also minimizing the size of the system. EnergyPlus was used to model a standard reference large office building for three thermal energy storage system cases: mixed chilled water storage, stratified chilled water storage, and ice storage. An annual average shifting of 25–78% of peak electricity was achieved from the simulation results. The strategy was able to achieve an annual 10–17% cost reduction for consumers using the time of use rates available from a local utility.

An analytical optimization of thermal energy storage for electricity cost reduction in solar thermal electric plants

Solar Thermal Electric (STE) plants can integrate Thermal Energy Storage (TES) in order to generate electricity when the energy source (Sun radiation) has vanished. TES technology has become a very important asset for this type of renewable energy source, but it has induced a rise in electricity cost in many cases. One of the reasons is the need of larger solar fields as the TES capacity increases because the solar field has to provide thermal power both to generate electricity and to charge the storage. The economic effects of improving the plant performance seem to have some internal complexities that must be investigated covering the internal relations among the main parts of a STE plant: the solar field, the power block and the energy storage. This paper presents an analytical study of these relations aimed at deriving a better understanding of the cost/performance behavior of STE plants. As the power block is a mature and commercial technology with well-established efficiencies and specific costs (in $/W, for instance), it has been taken as the reference element in modelling the plant. The other parts of the plant, i.e., the solar field and the energy storage, have been characterized in cost and energy management by a set of high-level parameters. Of course, a coarse definition cannot give very accurate results for a specific design, but it can be the guideline for the selection and sizing of a plant. It is worth noting that each type of solar thermal power plant has a different parametric scenario, corresponding to its essential design window. In this paper, comparisons among plants with different parametric scenarios are restricted to one-axis concentration solar fields, where the coarse model is easily characterized. The results show that the optimum plant configuration, in terms of TES capacity and solar field size, depends on the solar field and TES costs relative to power block cost. Moreover, it is shown that some parametric scenarios always lead to an increase in the cost of electricity when the energy storage capacity is enlarged. On the contrary, parametric scenarios associated to cheaper solar fields yield a much better economic result when TES is embodied in the plant. Additionally, TES efficiency is also identified as a parameter with high impact in the performance of the whole system. This result seems obvious, but the model gives numerical values that can help to optimize the selection process in a project. For instance, it is assessed that the lower the TES efficiency, the greater the relevance of reducing solar field costs is in order to obtain low electricity generation costs. As a general conclusion, the model points out that Fresnel-type solar fields are much better suited than parabolic trough collectors for integrating thermal energy storage. This implies that Fresnel plants present a higher potential to cover the peaks of electricity demand, which results into bigger profits.

Energy model optimization for thermal energy storage system integration in data centres

In the last years the total energy consumption of data centre industry has experienced a rapid increase due to the vast growth in internet usage. This phenomenon has aroused the interest for both, data centre industry and researchers in energy consumption and carbon footprint mitigation. Data centres operational expenses are also a key parameter for the productivity and competitiveness of the industry. In the present work, the implementation and optimization of thermal energy storage (TES) into a real data centre is presented. To the knowledge of the authors this is the first time that a methodology based on TraNsient System Simulation (TRNSYS), GenOpt and the application of Hooke and Jeeves optimization algorithm is used to study the implementation of TES, in particular water storage tanks, in data centres. A sensitivity analysis on the TES system cost is performed in function of the available literature information. The results show that the operating temperature of the chillers should be as lower as the system allows and therefore this open the possibility to study ice storage system. Regarding the economic analysis, the data centre electricity expenses can be reduced annually up to 3%. The uncertainty of the electricity price in the future is a major issue and it is also discussed.

Thermal Energy Storage Optimization in Shopping Center Buildings

In this research, cooling system optimization using thermal energy storage (TES) in shopping center buildings was investigated. Cooling systems in commercial buildings account for up to 50% of their total energy consumption. This incurs high electricity costs related to the tariffs determined by the Indonesian government with the price during peak hours up to twice higher than during off-peak hours. Considering the problem, shifting the use of electrical load away from peak hours is desirable. This may be achieved by using a cooling system with TES. In a TES system, a chiller produces cold water to provide the required cooling load and saves it to a storage tank. Heat loss in the storage tank has to be considered because greater heat loss requires additional chiller capacity and investment costs. Optimization of the cooling system was done by minimizing the combination of chiller capacity, cooling load and heat loss using simplex linear programming. The results showed that up to 20% electricity cost savings can be achieved for a standalone shopping center building.

Optimum heat storage design for solar‐driven absorption refrigerators integrated with heat exchanger networks

A methodology is presented for optimizing hybrid renewable energy‐fossil fuel systems with short‐term heat storage. The considered system is an absorption‐refrigeration (AR) cycle integrated with a heat exchanger network (HEN) requiring cooling below ambient temperature. The AR cycle can be driven by multiple energy sources including excess energy from hot process streams, renewable energy sources (solar and biofuels), and fossil fuels. A two‐step approach based on mixed integer nonlinear programming methods is used for the optimization. First, the problem of optimal energy integration in the hybrid energy system without heat storage is solved on a monthly basis by minimizing simultaneously the total annual cost and the overall greenhouse gas emissions. In the second step, the multi‐tank thermal energy storage (TES) design problem is solved. The design involves the identification of the optimal number of storage tanks, their sizes, configuration and operation policies. The TES optimization is carried out on an hourly basis while incorporating the design targets determined by the first step. © 2013 American Institute of Chemical Engineers AIChE J, 60: 909–930, 2014

Molecular dynamics simulations of nano-encapsulated and nanoparticle-enhanced thermal energy storage phase change materials

The nano-encapsulated and nanoparticle-enhanced phase change materials (PCM) which can be used for thermal energy storage have attracted much attention in recent years. To understand the heat and mass transfer mechanisms of the nano-encapsulated and nanoparticle-enhanced PCM on the molecular and atomic scale, the molecular dynamics (MD) simulations were performed in the present paper. The nano-encapsulated PCM with different shell thicknesses were fabricated by using n-octadecane as core material and SiO2 as shell material. The nanoparticle-enhanced PCM were formulated by mixing Al nanoparticles into n-nonadecane. The n-nonadecane, n-eicosane, n-heneicosane and n-docosane were used to build the pure PCM models as unencapsulated PCM systems for comparison. The results showed that the torsion and extension of the core material molecule chains could be restricted by excessive thick shell in the nano-encapsulated PCM systems. The mobility of the nanoparticle-enhanced PCM decreased with the increase of the diameter of added nanoparticles. Both excessive thick and thin shells were disadvantageous for encapsulated PCM. And the appropriate size of particle was very important for heat transfer enhancement of the nanoparticle-enhanced PCM. The MD simulations proposed herein can be helpful for the material design and performance optimization of thermal energy storage and transport PCM.

Methodology for determining the optimal operating strategies for a chilled-water-storage system—Part II: Project application

A new methodology for determining the optimal operating strategies for a chilled-water-storage system under a time-of-use electricity rate structure is introduced in Part I. In Part II, a practical project is introduced to illustrate the application of this methodology. It is is a large-scale chilled-water system with a 5.4 million gallon water storage tank and an advanced control system. The methodology proposed in this dissertation is successfully applied in this system to search the optimal operations of the thermal energy storage (TES) and chiller plant. The profiles of system cooling load and weather conditions between March 2007 and February 2008 are selected as the baseline. The utility rate structure is introduced and analyzed to define the off-peak and on-peak periods for the summer and winter months. Each component is modeled based on the trended data, and an hourly simulation is performed month by month. Six scenarios are designed and simulated to study the savings due to TES application, TES optimization, and plant optimization. The chiller chilled water leaving temperature and cooling tower approach temperature are optimized to further improve the plant performance. The simulation results show that the savings due to TES operation optimization and plant optimization could be very significant compared with the savings due to TES application. Many of these optimal control strategies have been implemented in the actual optimization performed on the system and achieved significant savings.

Optimization of thermal energy storage in packed columns

We propose a method for optimizing the net economic income for thermal energy storage in a cylindrical column packed with solid spheres. The economic value of stored heat is maximized relative to equipment and operating costs for air-based solar energy storage systems packed with either rock or steel spheres. Variables optimized separately are bed length and diameter, air flow rate, spherical particle diameter and collection time. Simultaneous optimization of a subset of these variables is illustrated. The mathematical model for the transient temperature profile in the bed includes intraparticle heat conduction, axial dispersion and heat losses to the surroundings, as described in earlier papers.