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Safe operation of online learning data driven model predictive control of building energy systems

Energy and AI 2023年第4期14卷 536-549页

作者： Phillip Stoffel Patrick Henkel Martin Ratz alexander kumpel Dirk Muller RWTH Aachen University E.ON Energy Research CenterInstitute for Energy Efficient Buildings and Indoor ClimateMathieustraße 10Aachen52074Germany

Model predictive control is a promising approach to reduce the CO 2 emissions in the building ***,the vast modeling effort hampers the widescale practical ***,data-driven process models,like artificial neural networks,are well-suited to automatize the ***,the underlying data set strongly determines the quality and reliability of artificial neural *** general,the validity domain of a machine learning model is limited to the data that was used to train *** based on system states outside that domain,so-called extrapolations,are unreliable and can negatively influence the control *** present a safe operation approach combined with online learning to deal with extrapolation in data-driven model predictive ***,the k-nearest neighbor algorithm is used to detect extrapolation to switch to a robust fallback *** continuously retraining the artificial neural networks during operation,we successively increase the validity domain of the artificial neural networks and the control *** apply the approach to control a building energy system provided by the BOPTEST *** compare controllers based on two data sets,one with extensive system excitation and one with baseline *** system is controlled to a fixed temperature set point in baseline ***,the artificial neural networks trained on this data set tend to extrapolate in other operating *** show that safe operation in combination with online learning significantly improves performance.

关键词： Data-driven model predictive control Online learning Novelty detection Artificial neural networks Building energy systems

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Development of a Long-Term Operational Optimization Model for a Building Energy System Supplied by a Geothermal Field

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Journal of Thermal Science 2022年第5期31卷 1293-1301页

作者： KÜMPEL alexander STOFFEL Phillip MÜLLER Dirk RWTH Aachen University E.ON Energy Research CenterInstitute for Energy Efficient Buildings and Indoor ClimateAachen 52074Germany

In order to reduce energy consumption and CO_(2) emissions in the building sector, more and more renewable energy sources are integrated into energy systems. Especially geothermal fields combined with heat pumps are able to supply buildings with heat and cold at low carbon emissions. However, using geothermal fields as heat and cold source influences the ground temperature. Consequently, the ground temperature can change dramatically over a building’s lifetime, leading to less efficient operation of the energy system. Therefore, a sustainable operation is required to ensure the long-term efficiency of geothermal fields. In this paper, we develop an optimization model to derive operating strategies for an efficient long-term operation of a building energy system coupled to a geothermal field. The investigated energy system is the main building of the *** Energy Research Center in Aachen, Germany, which includes a heat pump, two boilers, a combined heat, and power unit, a glycol cooler, and a geothermal field with 41 probes. For each component, we develop energy-based sub-models, which are connected to form the overall system. The geothermal field is modeled by using a g-functions approach as well as a simplified resistance-capacitance approach. To achieve short computing times and realize an optimization horizon of several years, the optimization problem is formulated as mixed-integer linear programming(MILP). The developed model is optimized regarding two different objectives: the minimization of energy costs and the minimization of long-term temperature changes in the ground. Conclusions for an efficient and sustainable operation of the field, especially for the cooling supply, can be derived from the optimization results. It is shown that a state of equilibrium should be aimed to achieve an energy-efficient operation, in which the temperature of the field is close to the initial ground temperature.

关键词： geothermal energy building energy systems operational optimization long-term operation

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