Size Of Thermal Energy Storage Research Articles

Modelling and optimization of concentrated solar power using response surface methodology: A comparative study of air, water, and hybrid cooling techniques

This research introduces a novel approach specifically designed to improve the design of Concentrated Solar Power plants utilizing the Response Surface Methodology. The objective of the suggested methodology is to enhance energy production efficiency by simultaneously minimizing the levelized cost of electricity and the land footprint associated with the power plant while comparing three different cooling techniques: air, water, and hybrid. Two software tools, System Advisor Model and Design-Expert, are employed to validate the primary model, evaluate the responses, generate the predictive models, and verify the results. The configuration of a Concentrated Solar Power plant is influenced by four main factors: the size of the solar field (solar multiple), row spacing, number of solar assemblies per loop, and size of thermal energy storage. In this study, these factors are varied within the following ranges: solar multiple from 1 to 5, row spacing from 10 to 30 m, number of solar assemblies from 4 to 10 per loop, and thermal energy storage from 5 to 15 h. The generated predictive models demonstrated very high accuracy, particularly for the annual energy production, with an error ranging between 0.2% and 1.5%. The findings showed that the hybrid cooling system is the most cost-effective cooling technique and has the highest energy output compared to the evaporative and air-cooling methods. When optimizing the required area of the hybrid cooled plant with a reduction of 47.44%, the analysis indicated a minimal decrease in energy output of 3.61% and a slight increase in the levelized cost of electricity by 0.95%. According to the results, the effect of area on the annual energy production and levelized cost of electricity is significant below the optimal area, while this effect becomes minor at higher values.

Technical and Financial Viability of a 1 MW CSP Power Plant with Organic Rankine Module: Case Study for a Northeastern Brazilian City

In this study, a 1 MWe parabolic trough concentrating solar power plant using an Organic Rankine Cycle to convert thermal power into electricity was simulated. The solar data used is from Fortaleza, the capital city of Ceara, a state in the northeast region of Brazil. The simulation was year-round and used hourly acquired data. Several different configurations differing in number of collectors and size of thermal energy storage were considered and, by the end of the study, according to the technical and financial results, one best configuration was defined. With a net annual energy generation of 4815.50 MWh, a 12.08% total efficiency and a levelized cost of electricity (LCOE) of 186.98 US$/MWh, the best defined configuration was the one with 100 collector assemblies and 48 MWh storage system. Besides that, the capital and OM costs of the various components were compared to define the most expensive to the power plant, being the collectors acquisition the biggest cost, which represents 74% and 58% of capital and OM costs respectively.

Optimum combination of diesel and concentrating solar in remote area power generation using supercritical CO2 turbines

Electrification of remote communities is a great challenge worldwide. Their reliance on economically and environmentally unfavourable diesel generators makes these communities attractive target markets for renewables. Concentrating solar thermal (CST) plants operating on supercritical CO2 (s-CO2) Brayton power cycles have been proposed for their high efficiency, compactness, compatibility with natural air-cooling, and capability of being built at a small size without significant efficiency penalties. Thermal energy storage (TES) technology can mitigate intermittency problems. This study aims to identify the optimal configuration of hybrid CST and diesel generation (DG) for different types of remote locations based on annual simulations involving key system design features including solar multiple, TES size, and CST size. One novelty in this study is the inclusion of actual weather information and load demand profiles for selected potential locations. Another is that a realistic economic model for s-CO2 power blocks for small to medium sizes, based on accurate cost data, is presented. More importantly, a realistic representation of the s-CO2 turbine, which includes isentropic efficiencies varying at off-design conditions, is used. This facilitates a study into the effects that the inclusion of realistic off-design turbine information has on the thermodynamic and techno-economic performances of the system. This is done by comparing the simulation results with results obtained using a conventional method that uses a constant turbine efficiency. This paper presents the optimal system configurations offering the lowest levelised cost of energy (LCOE) obtained using three-variable exhaustive search optimisation. The results show that the system is an economically favourable option and provides substantial environmental benefits.

Machine learning for performance prediction in smart buildings: Photovoltaic self-consumption and life cycle cost optimization

The application of Photovoltaic (PV) system in buildings is growing rapidly in response to the need for clean energy sources and building decarbonization targets. Nonetheless, enhancing PV self-consumption through technical solutions such as Energy Storage Systems (ESS) is getting higher importance to increase the profitability of PV plants, by minimizing the building-grid interaction. In this context, analyzing PV self-consumption of different energy storage configurations becomes more relevant and crucial in building energy modeling although it is heavily time-consuming and complicated, particularly within a multi-objective optimization related to the ESS design. As a solution to resolve this issue, this paper evaluates the accuracy, training, and prediction speed of 24 Machine Learning (ML) models to be used as surrogate models for analyzing PV self-consumption in smart buildings. Furthermore, the performance of short-term Thermal Energy Storage (TES) to increase PV self-consumption is assessed and presented using ML models. The results showed the Gaussian Process Regression (GPR), Neural Networks (NN) including bilayered and trilayered NN models, Support Vector Machines (SVM) including the fine gaussian and cubic SVM models, and Ensembles of Trees (EoT) as superior ML models. The results also revealed that TES systems can efficiently increase PV self-consumption in the building equipped with electric heat pumps to provide heating, cooling, and domestic hot water. Moreover, the TES size optimization regarding the Life Cycle Cost (LCC) showed that the LCC-based optimum TES size can yield 7.1% savings within 30 years of the building service life. The novelties of this research are first to provide a reference to select the most suitable ML models in predicting PV self-consumption, second to implement machine learning for analyzing the performance of short-term thermal energy storage to enhance PV self-consumption in buildings, and third to carry out an LCC-based optimization on TES size using ML-based prediction models.

Thermodynamic and Economic Analysis of a Gas-Turbine Combined Heat and Power Plant Considering Operational Flexibility

The operational flexibility is improved to decouple the thermoelectric limitation of the combined heat and power (CHP) system and meet the dynamic changes of heat and electrical loads in an affordable economic and thermodynamic cost. A gas-turbine CHP system combined with thermal energy storage of molten salt is proposed in this paper. The thermodynamic models of components are constructed and simulated in Ebsilon, and the indicators are defined to evaluate thermodynamic and economic performances and operational flexibility of the coupled CHP system. The thermodynamic analysis indicates that under the design conditions, when CHP operates without thermal energy storage, gas turbine has the largest energy and exergy losses due to the combustion irreversibility, accounting for 51.28 and 55.76% of total energy and exergy losses, respectively. In addition, the effects of thermal energy storage capacity on system performances are analyzed and discussed. The results indicate that when the capacity of the thermal energy storage increases from 0 to 2000 kWh, the primary energy ratio is decreased by 4.56%, the exergy efficiency only declines by 0.74%, and the economic revenue of the system is also reduced by 15.70%. But the adjustable ability of the heat and electricity is increased by 44.84%. The optimal thermal energy storage size of the CHP plant is comprehensively determined according to the integrated benefits of energy, economic, and operation flexibility.

Effects of different sizes and dispatch strategies of thermal energy storage on solar energy usage ability of solar thermal power plant

The solar energy usage ability is mainly considered in the construction of solar thermal power plant (STPP) which is affected by factors of design direct normal irradiance (DNI), solar multiple (SM), thermal energy storage (TES) size and dispatch fraction (DF). In this paper, a general model is developed in order to obtain the relationship among these factors, the electricity output and the solar energy usage efficiency of STPP. Based on the modeling method, a critical design of DNI is derived and some suggestions for improvement in the design of DNI are presented in order to improve the efficiency, which can result in the reduction of waste solar energy. The effects of SM, TES size and DF on the critical design of DNI are also investigated. It is found that the solar energy usage ability will be only dependent on the TES size when TES size is below 6 h and the solar energy usage ability will be dependent on both TES size and DF when TES size is above 6 h. The increase of TES size and the decrease of DF beyond their corresponding critical design DNI will reduce the solar energy usage ability of STPP. The results obtained can provide an important basis for studying the solar energy utilization capacity of STPP and determine the design parameters of STPP.

Feasibility of thermal energy storage integration into biomass chp-based district heating system

Despite the advancements in thermal energy storage (TES) systems for combined heat and power plants (CHP) operation, these technologies are not implemented in CHP-based district heating (DH) systems in some of the countries where DH systems are still in development. An analysis of economic and environmental benefits that can be reaped as a result of the TES integration within the DH system is required to successfully promote TES as a technology for the DH system improvement. An actual large-scale biomass CHP-based DH system is explored as a case study. Scenarios for two types of support policies (feed-in premium electricity produced by biomass CHP and high-efficiency biomass CHP) were examined by varying the size of TES. The aim of the research was to evaluate the impact of the biomass CHP support policy on TES integration feasibility. Calculations show that TES installation combined with biomass CHP is less feasible when all of the electricity produced by biomass CHP is subsidised.

Numerical modeling and analysis of dual medium thermocline thermal energy storage

In this study, a computational model is developed to investigate packed-bed thermocline thermal energy storage. Its three-dimensional transport mechanisms are simulated under different flow conditions, and the transport model is based on a macroscopic version of the k–epsilon equation for turbulent flow conditions. Dispersive and secondary heat transfer have also been considered for turbulent flows. The thermal characteristics and efficiency of the system are examined under different operational and geometrical conditions for the charging and discharging processes for a fixed thermal energy storage size of 50 MWh.The Taguchi method is used to optimize the design parameters of the thermocline thermal energy storage system. Its performance is evaluated by performing numerical simulations based on a three-dimensional computational fluid dynamics (CFD) model. In this study, the effects of the variations in parameters such as the inlet fluid Reynolds number, aspect ratio, porosity, and filler size, on the storage performance are also evaluated. The optimal condition and geometry of the thermocline thermal energy storage system are determined by the CFD–Taguchi combined method. The analysis results indicate that the porosity and aspect ratio are the most important design parameters for thermocline thermal energy storage.

Thermoeconomic assessment of a solar polygeneration plant for electricity, water, cooling and heating in high direct normal irradiation conditions

A thermoeconomic assessment of the joint production of electricity, fresh-water, cooling and heat for a solar polygeneration plant is carried out. The aims are to assess the actual cost of each product, to conduct a sensitivity analysis of investment, fuel cost and demand, and to evaluate the effects of solar field size and the sizing of thermal energy storage, for a polygeneration plant located in an area with high solar irradiation conditions and where there is demand for its production. The solar polygeneration plant is configured by a concentrated solar power (CSP) parabolic trough collector field with thermal energy storage and backup system, multi-effect distillation (MED) module, single-effect absorption refrigeration module, and process heat module. The solar polygeneration plant is simulated in a transient regime, in a representative location with high irradiation conditions, such as in northern Chile. Three configurations are investigated: two polygeneration schemes and one considering stand-alone systems. This study reveals that a solar polygeneration plant is more efficient and cost-effective than stand-alone plants for a zone with high irradiation conditions and proximity to consumption centers, such as mining industries, which require continuous operation and energy supply with fundamentally constant demand. Furthermore, according to northern Chilean market, solar polygeneration configurations are competitive regarding electricity, fresh-water, cooling and heat productions. Additionally, solar polygeneration plants can increase the economic profit by selling carbon credits and credits of renewable-energy quotas based on the Kyoto Protocol and Chilean legislation, respectively.

Annual performance of solar tower aided coal-fired power generation system

Solar tower aided coal-fired power generation system (STCG) is able to provide high solar utilization efficiency with low coal consumption rate. This paper compares performances of a solar tower aided coal-fired power plant, a solar tower power plant and a coal-fired power plant under different operative conditions. The comparison includes various solar multiple and thermal energy storage size. According to solar radiation resource and grid power dispatching demand, STCG, solar tower power generation system (STG) and coal-fired power generation system (CPG) work under off-design conditions all the year around. Results show that STCG has higher solar utilization efficiency than STG and lower coal consumption rate and CO2 emission rate than CPG. In addition, solar-to-electricity exergy efficiency of STCG is at least 1.83% higher than that of STG. Compared to CPG, the 1000 MWe STCG can reduce coal consumption by 2.0 × 105 t/y, with the saving ratio being 10.4%. The annual average coal consumption rate of STCG is 27.3 g/kWh lower than that of CPG. In addition, the annual average CO2 emission rate of STCG is reduced by 10.1% compared with that of CPG. Solar tower aided coal-fired power generation can facilitate energy conservation and emission reduction of STG and CPG.

Partitioning of MCHP-TES system run time to incorporate transient system behaviour: a comprehensive exergy-based analysis using simulation

By combining heat and power generation, mini-combined and micro-combined heat and power systems (MCHP) provide an efficient, decentralised means of power generation that can complement the composition of the electricity generation mix. Dynamic tools capable of handling transient system behaviour are required to assess MCHP efficiency beyond a mere static analysis based on steady-state design parameters. Using a simulation of a cogeneration system, we combine exergetic definitions for different operational system states to quantify the overall system efficiency continuously over the whole period of operation. The concept of exergy allows direct comparison of different forms of energy. A sensitivity analysis was performed where we quantified the effect on MCHP overall performance under varying engine rotational speed, thermal energy storage size and fluid storage temperature in a range of MCHP simulations. We found that the exergetic quantity of natural gas used by the MCHP decreased slightly at higher engine speeds (−2% to −4%). While the total amount of electricity generated is almost constant across the range of different engine output, more thermal exergy (up to +21%) can be recovered when the engine is operating at elevated speeds. Furthermore, selection of specific optimal thermal storage fluid temperatures can aid in improving system efficiency. Copyright © 2016 John Wiley & Sons, Ltd.

Analysis and sizing of thermal energy storage in combined heating, cooling and power plants for buildings

Thermal energy storage (TES) can lead to significant energy savings and economic benefits in combined heating, cooling and power plants (CHCPs) for buildings in the tertiary sector. However, their complex interactions with the rest of the CHCP system make their adequate sizing difficult without using extensive and detailed simulations. The authors have developed a new method to evaluate the thermal contribution of TES based on simple procedures. Comparisons with detailed simulations for a range of situations confirm the ability of this method to predict the effect of TES on CHCP systems with good approximation, as well as to find the optimal size in a relatively simple manner and with few required data. The case studies show a strong dependence of the TES contribution on the demands profile and the operation strategy. However, adequately sized TES are proven to bring relevant energy savings as well as economic profit to CHCP plants. In this paper, sizing procedures are provided to find the optimal volume both in terms of thermodynamic efficiency and of economic profit.