Large Thermal Storage Systems Research Articles

Simulation and design of a large thermal storage system: Real data analysis of a smart polygeneration micro grid system

• Optimization of the size of a smart grid integrated thermal storage system. • Implementation of a lumped parameter model based on historical measured data series. • Maximization of the overnight energy production through sensible heat thermal storage. • Investment profitability in terms of CO 2 reduction, share of energy from cogeneration, economics. The Smart Polygeneration Microgrid (SPM) at the Savona Campus of the University of Genoa consists of several renewable and traditional electrical and thermal generating units integrated with electric batteries; buildings and facilities are connected by an electrical grid and a district heating network. Thermal and electrical power flows are managed by a proper Energy Management System (EMS) which includes models for all the SPM components ensuring operational costs minimization in compliance with networks constraints. The present study focuses on the integration of a thermal energy storage (TS) system in the SPM: to this aim, a new thermal storage model based on a stepped two-zone approach has been built inside the dynamic EMS solver. The TS is conceived for recovering additional heat from two 65kW el cogenerative gas turbines (CGT), thus minimizing the operation time of the backup gas heaters (GH): the analysis is aimed at inferring the best TS size in terms of different key parameters, expressed through properly defined economic and energy criteria, including overall energy consumption, reduced greenhouse emissions, minimum payback period. The model is applied to energy demand data (heat and electricity) as measured at 15 min time steps along 2 years. The present dynamic analysis shows that an optimized size TS based on sensible heat can increase the CGT operation hours up to 34% yearly and reduce the equivalent CO 2 emissions by 4%.

Sustainable energy supply for self-sufficient buildings with seasonal energy storages – parametric study

To reduce greenhouse gas emissions, the efficiency of energy supply systems must be increased, for example, using renewable energy sources. Since the generation of renewable energy can depend on weather conditions and other parameters, the use of short- or long-term energy storage enables an increase in the covered building energy demand. Due to the large number of available technologies for renewable energy generation and storage, it is possible to combine these systems into different energy supply concepts. By optimizing and comparing the designed concepts, the most suitable one can be determined with respect to the current and future investments. A comprehensive comparison of energy supply concepts must include both economic and energy evaluation criteria. This study focuses on parametric numerical simulations to identify economically feasible and sustainable energy supply concepts for a practical case of new residential buildings. The results show that electrical storage and on-site power generation can provide the greatest benefits. In contrast, large thermal storage systems are not economically viable.

Sensitivity study for modelling atmospheric attenuation of solar radiation with radiative transfer models and the impact in solar tower plant production

The solar radiation reflected by the heliostats towards the receiver in solar tower plants may be attenuated by scattering and absorption processes along the optical path. This phenomenon has been traditionally computed by the solar tower plant codes using simple models based on polynomial functions of the slant range and taking very extreme conditions for the turbidity based on the standard visual range. Radiative transfer codes (libRadtran) allow modelling the atmospheric attenuation as a function of the slant range considering different aerosol conditions taken from several AERONET stations in regions of interest for CSP. The methodology presented in this work for modelling atmospheric attenuation with libRadtran can be used with any other radiative transfer model. The results showing the sensitivity of the attenuation loss to the aerosol optical depth, assuming homogeneous vertical distribution, have been fit to a simple model that can be used in Solar Advisor Model (SAM). The attenuation loss in the model proposed reaches around 20% at 1km of slant range for highly aerosol load typical of some desert sites. Sensitivity estimations with SAM have been performed also for two reference solar tower plants (Ivanpah 1 and Gemasolar) to study the impact of atmospheric attenuation in the output power of the plant. The different attenuation loss between low and very high turbidity conditions can result in a reduction of the power output of a large plant like Ivanpah 1 of around 12% of average daily production, 20% in the field optical efficiency and 11% in the power absorbed by the receiver. In smaller plants with large thermal storage system (Gemasolar) the impact of the attenuation loss is significantly smaller (around 4%). Modelling the atmospheric attenuation in the solar tower codes should include aerosol optical depth as input in a daily basis for allowing the inclusion of the expected aerosol variability of desert and arid sites.

Impact of atmospheric aerosol loads on Concentrating Solar Power production in arid-desert sites

The accurate quantification of direct normal irradiance (DNI) and the production of time series of DNI have a key role during the planning and designing stages of CSP plants. Satellite derived data are frequently used for that purpose. One of the important sources of uncertainty for satellite derived DNI is the accuracy in the quantification of aerosol optical depth, one of the most important parameters that contribute to solar radiation attenuation at the Earth’s surface. This topic can be extremely important in desert and arid places where sudden and large increase of aerosol optical depth can be eventually expected. This work presents an analysis of the uncertainty about the knowledge of aerosol optical depth in Sede Boqer and Tamanrasset, its contribution to the uncertainty of DNI values estimated from Meteosat imagery, and finally the impact on the CSP plant energy dispatched. Reference plants for CSP parabolic trough and CSP tower technologies have been modelled with SAM with no thermal storage system, and a GEMASOLAR plant-type has been also modelled as an example of tower plant with large thermal storage system. The results have shown that in Tamanrasset the sudden and eventual high peaks of aerosol optical depth resulted in an important decrease of the daily energy produced by the plant; this reduction is not always observed when satellite derived DNI is used to input meteorological conditions in SAM due to the underestimation of the aerosol optical depth. The use of large thermal storage system notably reduces the impact of these phenomena on the CSP power plant output.