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This paper focuses on appropriately measuring the accuracy of forecasts of load behavior and renewable generation in micro-grid operation. Common accuracy measures like the root mean square of the error are often difficult to interpret for system design, as they describe the mean accuracy of the forecast. Micro-grid systems, however, have to be designed to handle also worst case situations. This paper therefore suggests two error measures that are based on the maximum function and that better allow understanding worst case requirements with respect to balancing power and balancing energy supply.
Demand Side Management for Thermally Activated Building Systems based on Multiple Linear Regression
(2015)
There is a growing trend for the use of thermo-active building systems (TABS) for the heating and cooling of buildings, because these systems are known to be very economical and efficient. However, their control is complicated due to the large thermal inertia, and their parameterization is time-consuming. With conventional TABS-control strategies, the required thermal comfort in buildings can often not be maintained, particularly if the internal heat sources are suddenly changed. This paper shows measurement results and evaluations of the operation of a novel adaptive and predictive calculation method, based on a multiple linear regression (AMLR) for the control of TABS. The measurement results are compared with the standard TABS strategy. The results show that the electrical pump energy could be reduced by more than 86%. Including the weather adjustment, it could be demonstrated that thermal energy savings of over 41% could be reached. In addition, the thermal comfort could be improved due to the possibility to specify mean room set-point temperatures. With the AMLR, comfort category I of the comfort norms ISO 7730 and DIN EN 15251 are observed in about 95% of occasions. With the standard TABS strategy, only about 24% are within category I.
Adaptive predictive control of thermo-active building systems (TABS) based on a multiple regression algorithm: First practical test. Available from: https://www.researchgate.net/publication/305903009_Adaptive_predictive_control_of_thermo-active_building_systems_TABS_based_on_a_multiple_regression_algorithm_First_practical_test [accessed Jul 7, 2017].
Energy consumption for cooling is growing dramatically. In the last years, electricity peak consumption grew significantly, switching from winter to summer in many EU countries. This is endangering the stability of electricity grids. This article outlines a comprehensive analysis of an office building performances in terms of energy consumption and thermal comfort (in accordance with static – ISO 7730:2005 – and adaptive thermal comfort criteria – EN 15251:2007 –) related to different cooling concepts in six different European climate zones. The work is based on a series of dynamic simulations carried out in the Trnsys 17 environment for a typical office building. The simulation study was accomplished for five cooling technologies: natural ventilation (NV), mechanical night ventilation (MV), fan-coils (FC), suspended ceiling panels (SCP), and concrete core conditioning (CCC) applied in Stockholm, Hamburg, Stuttgart, Milan, Rome, and Palermo. Under this premise, the authors propose a methodology for the evaluation of the cooling concepts taking into account both, thermal comfort and energy consumption.
Innovative technologies and concepts will emerge as we move towards a more dynamic, service-based, market-driven infrastructure, where energy efficiency and savings can be facilitated by interactive distribution networks. A new generation of fully interactive Information and Communication Technologies (ICT) infrastructure has to be developed to support the optimal exploitation of the changing, complex business processes and to enable the efficient functioning of the deregulated energy market for the benefit of citizens and businesses. The architecture of such distributed system landscapes must be designed and validated, standards need to be created and widely supported, and comprehensive, reliable IT applications will need to be implemented. The collaboration between a smart house and a smart grid is a promising approach which, with the help of ICT can fully unleash the capabilities of the smart electricity network.
Mit längerfristigen Nutzerbefragungen in zwei unmittelbar benachbarten Bürogebäuden in Freiburg wurden das Temperaturempfinden der Nutzer und deren Zufriedenheit mit dem thermischen Raumkomfort zweimal täglich erfasst. Ein Bürogebäude wird im Sommer mit einem maschinellen Nachtlüftungskonzept konditioniert und das zweite verfügt über eine Betonkerntemperierung und eine Zu‐ und Abluftanlage. Auf Basis der vorhandenen Daten aus der Erhebung wurde mit Hilfe von Regressionsanalysen ein Modell zur Vorhersage der Komforttemperatur berechnet und mit den Modellen in DIN EN 15251 verglichen.
The uncertain and time-variant nature of renewable energy results in the need to deal with peaks in the production of energy. One approach is to achieve a load shift and thereby help balancing the grid by using thermally Activated Building Systems (TABS). Control systems currently in place do not exploit the full potential of TABS. This paper reviews how Model Predictive Control can possibly reduce the fluctuations of the demand and supply of (renewable) energy as it enables the TABS to react to the dynamics of weather and its impact on the grid at any time.
Wärmepumpen sind eine Schlüsseltechnologie der Wärmewende. Durch die Nutzbarmachung von Umweltwärme und den Antrieb mit Elektrizität, die zunehmend aus erneuerbaren Energien gewonnen wird, kann die CO2-Intensität der Wärmeversorgung gesenkt werden. Eine Herausforderung besteht in der Anwendung in größeren Mehrfamilienbestandsgebäuden. Lösungsansätze und beispielhafte Umsetzungen werden hierzu vorgestellt.