• Energy Research

Sorption heat storage has the potential to store large amounts of thermal energy from renewables and other distributed energy sources. This article provides an overview on the recent advancements on long-term sorption heat storage at material- and prototype- scales. The focus is on applications requiring heat within a temperature range of 30–150 °C such as space heating, domestic hot water production, and some industrial processes. At material level, emphasis is put on solid/gas reactions with water as sorbate. In particular, salt hydrates, adsorbents, and recent advancements on composite materials are reviewed. Most of the investigated salt hydrates comply with requirements such as safety and availability at low cost. However, hydrothermal stability issues such as deliquescence and decomposition at certain operating conditions make their utilization in a pure form challenging. Adsorbents are more hydrothermally stable but have lower energy densities and higher prices. Composite materials are investigated to reduce hydrothermal instabilities while achieving acceptable energy densities and material costs. At prototype-scale, the article provides an updated review on system prototypes based on the reviewed materials. Both open and closed system layouts are addressed, together with the main design issues such as heat and mass transfer in the reactors and materials corrosion resistance. Especially for open systems, the focus is on pure adsorbents rather than salt hydrates as active materials due to their better stability. However, high material costs and desorption temperatures, coupled with lower energy densities at typical system operating conditions, decrease their commercial attractiveness. Among the main conclusions, the implementation within the scientific community of common key performance indicators is suggested together with the inclusion of economic aspects already at material-scale investigations.

Abstract The use of structural thermal storage is often suggested as a key technology to improve the penetration of renewable energy sources and mitigate potential production and distribution capacity issues. Therefore, a quantitative assessment of the energy flexibility provided by structural thermal energy storage is a prerequisite to instigate a large scale deployment of thermal mass as active storage technologies in an active demand response (ADR) context. In the first part of the work, a generic, simulation-based and dynamic quantification method is presented for the characterization of the ADR potential, or energy flexibility, of structural thermal energy storage. The quantification method is based on three ADR characteristics – i.e. available storage capacity, storage efficiency and power-shifting capability – which can be used to quantify the ADR potential in both design and operation. In the second part of the work, the methodology is applied to quantify the ADR characteristics for the structural thermal energy storage capacity for the different typologies of the Belgian residential building stock. Thereby an in-depth analysis demonstrates the relation between the building properties and its energy flexibility as well as the dependence of the energy flexibility on the dynamic boundary conditions.

Abstract The integration of buildings in a Smart Grid, enabling demand-side management and thermal storage, requires robust reduced-order building models that allow for the development and evaluation of demand-side management control strategies. To develop such models for existing buildings, with often unknown the thermal properties, data-driven system identification methods are proposed. In this paper, system identification is carried out to identify suitable reduced-order models. Therefore, grey-box models of increasing complexity are identified on results from simulations with a detailed physical model, deployed in the integrated district energy assessment simulation (IDEAS) package in Modelica. Firstly, the robustness of identified grey-box models for day-ahead predictions and simulations of the thermal response of a dwelling, as well as the physical interpretation of the identified parameters, are analyzed. The influence of the identification dataset is quantified, comparing the added value of dedicated identification experiments against identification on data from in use buildings. Secondly, the influence of the data used for identification on model performance and the reliability of the parameter estimates is quantified. Both alternative measurements and the influence of noise on the data are considered.

AbstractGrey-box modelling is a system identification technique that combines parameter estimation methods to quantify the model parameters and physical knowledge to define the model structure. Consequently, the potential of grey-box modelling lies, in addition to the application of reduced-order models in e.g. control strategies or district simulations, in the characterization of the thermal properties of buildings. Nevertheless, the quality of the obtained model is governed by the dynamic information that is available in the training data. Thereby, the required accuracy of the models, and thus the requirements of the training data, differ from application to application.This paper analyses how the significant difference in dynamic behavior of a slow floor heating system compared to a highly responsive radiator heating system results in a variation of the time constants of the building that are excited by the system and therefore identifiable in the system identification process. The performance of grey-box models for prediction and simulations are contrasted for cases with radiators and floor heating and the physical interpretability of the model parameters is demonstrated.

Proceedings of the 4th International Conference on Solar Heating and Cooling for Buildings and Industry (SHC 2015) Within the framework of IEA SHC Task 42 / ECES Annex 29, a simple tool for the economic evaluation of thermal energy storages has been developed and tested on various existing storages. On that account, the storage capacity costs (costs per installed storage capacity) of thermal energy storages have been evaluated via a Top-down and a Bottom-up approach. The Top-down approach follows the assumption that the costs of energy supplied by the storage should not exceed the costs of energy from the market. The maximum acceptable storage capacity costs depend on the interest rate assigned to the capital costs, the intended payback period of the user class (e.g. industry or building), the reference energy costs, and the annual number of storage cycles. The Bottom-up approach focuses on the realised storage capacity costs of existing storages. The economic evaluation via Top-down and Bottom-up approach is a valuable tool to make a rough estimate of the economic viability of an energy storage for a specific application. An important finding is that the annual number of storage cycles has the largest influence on the cost effectiveness. At present and with respect to the investigated storages, seasonal heat storage is only economical via large sensible hot water storages. Contrary, if the annual number of storage cycles is sufficiently high, all thermal energy storage technologies can become competitive. This study is part of IEA SHC Task 42 / ECES Annex 29 „Compact Thermal Energy Storage - Material Development and System Integration“ (http://task42.iea-shc.org). The work of ZAE Bayern is part of the project PC-Cools_V and supported by the German Federal Ministry for Economic Affairs and Energy under the project code 03ESP138A. University of Zaragoza thanks the Spanish Government for the funding of their work under the projects ENE2008-06687-C02-02, ENE2011-28269-C03-01 and ENE2014-57262-R. University of Lleida would like to thank the Catalan Government for the quality accreditation given to their research group (2014 SGR 123). The research leading to these results has received funding from the European Union's Seventh Framework Program (FP7/2007-2013) under grant agreement n° PIRSES-GA-2013-610692 (INNOSTORAGE) and European Union’s Horizon 2020 research and innovationprogramme under grant agreement No 657466 (INPATH-TES). Laia Miró would like to thank the Spanish Government for her research fellowship (BES-2012-051861). The University of the Basque Country acknowledges the financial support of the Spanish’s Ministry of Economy and Competitiveness through the MicroTES (ENE2012- 38633) research project. The responsibility for the content of this publication is with the authors

Sorption heat storage can potentially store thermal energy for long time periods with a higher energy density compared to conventional storage technologies. A performance comparison in terms of energy density and storage capacity costs of different sorption system concepts used for seasonal heat storage is carried out. The reference scenario for the analysis consisted of satisfying the yearly heating demand of a passive house. Three salt hydrates (MgCl2,Na2S, and SrBr2), one adsorbent (zeolite 13X) and one ideal composite based on CaCl2, are used as active materials in solid sorption systems. One liquid sorption system based on NaOH is also considered in this analysis. The focus is on open solid sorption systems, which are compared with closed sorption systems and with the liquid sorption system. The main results show that, for the assumed reactor layouts, the closed solid sorption systems are generally more expensive compared to open systems. The use of the ideal composite represented a good compromise between energy density and storage capacity costs, assuming a sufficient hydrothermal stability. The ideal liquid system resulted more affordable in terms of reactor and active material costs but less compact compared to the systems based on the pure adsorbent and certain salt hydrates. Among the main conclusions, this analysis shows that the costs for the investigated ideal systems based on sorption reactions, even considering only the active material and the reactor material costs, are relatively high compared to the acceptable storage capacity costs defined for different users. However, acceptable storage capacity costs reflect the present market condition, and they can sensibly increase or decrease in a relatively short period due to for e.g. the variation of fossil fuels prices. Therefore, in the upcoming future, systems like the ones investigated in this work can become more competitive in the energy sector.