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This paper presents latest results and outcomes of a research project about the decentralized feed-in of solar thermal energy into district heating networks. While solar heat exemplarily stands for any other heat source (as waste heat) the focus is on smaller distributed solar thermal heating plants rather than large central systems. The idea is to use the district-heating system as thermal source and sink to ensure the supply of the local heat consumers as well as the transmission of solar heat to other customers. This approach is supposed to minimize investment costs and increase the solar share, thus substituting fossil fuels. Analyses and investigations were done based on computational DH system simulations. A special version of the TRNSYS-simulation program was applied to calculate transient operation of a 3rd generation DH network (following IEA-DHC Annex X classification, see [1]). Several feed-in substations have been integrated into the model. Heat consumption and load profiles of the consumers have been estimated using the Typical-Day Method. This approach allows to adapt any measured data (daily load profiles) to a specific weather data set and to scale heat load profiles of the same type according to a given peak load or daily heat consumption. The simulation otfers the opportunity to have a look to any internal state of the system as local pressure, fluid temperature or mass flow. With this information component stress can be analyzed very well. The paper presents findings of the recently finnished project "Dezentrale Einspeisung in Nah- und Fernwarmesysteme unter besonderer Beriick-sichtigung der Solarthermie"1 and the ongoing research project "Kostenreduktionspotential beim Ausbau der Solarisierung von Femwarmenetzen durch Standardisierung"2. It is based on the German publications [21 and [3]. [ABSTRACT FROM AUTHOR]

Abstract: Solubility of nitrogen in propylene glycol/water mixtures (25%, 41.84% and 100% glycol by weight) have been determined in a temperature range from 10°C to 110°C using a static isochoric measuring method and are compared to the solubility of a typical solar liquid. To evaluate the amount of gas in a solar system it is necessary to measure the part of gases dissolved in the solar liquid, but also to consider the fraction of free gases (gas bubbles or gas cushions) in the system. Measuring this part was either not possible or only possible with a big technical effort until now. Therefore a new method was developed, which easily and fast identifies the volume of undissolved gases (“Gas Bubble Test”). The method was validated in extensive investigations in real solar systems. [Copyright &y& Elsevier]

Abstract: A series of model-predictive control (MPC) techniques have been explored for optimizing control sequences for window operation in mixed-mode (MM) buildings using EnergyPlus, and results for a simplified MM office building have been presented. Initial results for a small office in Boulder, Colorado show the ability to save upwards of 40% of cooling energy through near-optimal night cooling strategies, even in existing facilities. Strategies can be tuned to avoid overcooling the space by introducing heating energy into the objective function used in the MPC process. A complementary statistical technique has been introduced that allows for the “extraction” of logistic decision models from the optimal control results. The process works best when some time-lagged information is present as a predictor variable to ensure that some process memory is preserved. A generalized linear model (GLM) in the form of a multi-logistic regression was able to mimic the general characteristics of the optimizer results, achieving 70–90% of optimizer energy savings, but at a small fraction of the computational expense. Given the simple mathematical formulation of the logistic regression, it would be possible to implement this sort of decision model into modern direct digital control systems to control MM buildings in a near-optimal manner in real time. [ABSTRACT FROM AUTHOR]

Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building''s massive structure or by using active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this paper investigates the merits of harnessing both storage media concurrently in the context of optimal control. The objective function is the total utility bill including the cost of heating and a time-of-use electricity rate without demand charges. The evaluation of the combined optimal control assumes perfect weather prediction and plant modeling, which justifies the application of a consecutive time block optimization that optimizes 24 hour horizons sequentially. The analysis shows that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be drastically reduced and justify the development of a predictive optimal controller that accounts for uncertainty in predicted variables and modeling mismatch in real time. [Copyright &y& Elsevier]

This numerical study evaluates and compares four different flexibility and storage options in building energy systems (batteries, fuel switch, water tanks, and thermal building mass) in terms of potential improvements in load scheduling and energy efficiency. Using a generic modern office building with concrete core conditioning as an example, two different supply concepts (one based on a heat pump, one based on a CHP unit) are considered. A novel hybrid control concept is applied which is designed to be compatible with state-of-the-art controllers implemented in the field. The results show that batteries are the most technically attractive options in terms of grid support, efficiency and ease of implementation. Fuel switch is comparably straightforward to implement, but provides significant benefits only for the considered CHP system. Water tanks with a capacity of about two full operation hours offer nearly the same flexibility as much larger tanks, but negatively influence the efficiency of heat pump systems. The thermal building mass can be used effectively and efficiently for thermal storage, particularly in the heating season, but this is technically challenging to realize. It is shown that current electricity prices do not offer sufficient variations to stimulate grid-supportive operation. [ABSTRACT FROM AUTHOR]

The efficient use of energy for heating and cooling of indoor environments requires an accurate prediction and analysis of radiative heat transfer. Therefore it is necessary to use modern computer methods as otherwise the computational costs may become higher than for convective heat transfer, which is known to be a huge computational problem. A key problem in calculations of radiative heat transfer is the problem of mutual visibility arising in the determination of view factors. This is the same challenge that global illumination has to cope with which is one of the fundamental topics in computational graphics. The visibility problem is efficiently solved by modern graphics hardware. Therefore an OpenGL-based algorithm is developed to quickly and accurately calculate view factors for arbitrary, complex geometries. Theoretical and implementation details of the applied methods are given. We demonstrate the advantages of the developed computational method by a virtual test room for a tubular radiator, a heating of a warehouse by ceramic infrared heaters and the heat transfer in a car cabin. [ABSTRACT FROM AUTHOR]

Optimisation based economic despatch of real-world complex energy systems demands reduced order and continuously differentiable component models that can represent their part-load behaviour and dynamic responses. A literature study of existing modelling methods and the necessary characteristics the models should meet for their successful application in model predictive control of a polygeneration system are presented. Deriving from that, a rational modelling procedure using engineering principles and assumptions to develop simplified component models is applied. The models are quantitatively and qualitatively evaluated against experimental data and their efficacy for application in a building automation and control architecture is established. [ABSTRACT FROM AUTHOR]