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Three real-lab trigeneration microgrids are investigated in non-residential environments (educational, office/administrational, companies/production) with a special focus on domain-specific load characteristics. For accurate load forecasting on such a local level, à priori information on scheduled events have been combined with statistical insight from historical load data (capturing information on not explicitly-known consumer behavior). The load forecasts are then used as data input for (predictive) energy management systems that are implemented in the trigeneration microgrids. In real-world applications, these energy management systems must especially be able to carry out a number of safety and maintenance operations on components such as the battery (e.g. gassing) or CHP unit (e.g. regular test runs). Therefore, energy management systems should combine heuristics with advanced predictive optimization methods. Reducing the effort in IT infrastructure the main and safety relevant management process steps are done on site using a Smart & Local Energy Controller (SLEC) assisted by locally measured signals or operator given information as default and external inputs for any advanced optimization. Heuristic aspects for local fine adjustment of energy flows are presented.
The building sector is one of the main consumers of energy. Therefore, heating and cooling concepts for renewable energy sources become increasingly important. For this purpose, low-temperature systems such as thermo-active building systems (TABS) are particularly suitable. This paper presents results of the use of a novel adaptive and predictive computation method, based on multiple linear regression (AMLR) for the control of TABS in a passive seminar building. Detailed comparisons are shown between the standard TABS and AMLR strategies over a period of nine months each. In addition to the reduction of thermal energy use by approx. 26% and a significant reduction of the TABS pump operation time, this paper focuses on investment savings in a passive seminar building through the use of the AMLR strategy. This includes the reduction of peak power of the chilled beams (auxiliary system) as well as a simplification of the TABS hydronic circuit and the saving of an external temperature sensor. The AMLR proves its practicality by learning from the historical building operation, by dealing with forecasting errors and it is easy to integrate into a building automation system.
Prädiktive Betriebsverfahren
(2010)
Durch die Nutzung von Wetterprognosen lässt sich der Betrieb moderner Bürogebäude hinsichtlich Energiebedarf und Komfort verbessern. Ziel dieses Vorhabens ist es, mathematische Optimierungsverfahren für die Nutzung in der Gebäudeautomation zu entwickeln. Die Entwicklung einer vom Internet unabhängigen Versorgung mit Wetterprognosen über einen Langwellensender ist ebenfalls Gegenstand des Forschungsprojekts.