Modelling of high temperature storage systems for latent heat

There is a huge demand for heat storages for evaporation applications. Thermal storage systems are used to increase the efficiency of thermal systems by an improved adaption of energy availability and energy demand. In this paper a possible solution for modular storage systems from 200-600 °C and pressures up to 100 bar is presented. The application of steam as a working medium requires the availability of isothermal storage if charging/discharging should take place at almost constant pressure. The saturation temperature range is between 200°C and 320°C. Therefore nitrate salts are used as phase change material (PCM). The solution developed at DLR is characterized by a modular concept of tube register storages surrounded by both sensible and latent heat storage material. The focus in this paper is on modelling of the PCM storage. A model is introduced for melting and freezing of the PCM. To perform with an acceptable heat transfer rate inside the PCM, fins are used to increase the overall thermal conductivity. Instead introducing mean storage material parameters, like thermal conductivity or specific heat capacity, the geometry of the finned tube is modelled by using discrete elements. Therefore the model allows detailed studies on heat transfer during space and time. The fin design can be varied in order to find an optimal configuration. A set of partial differential equations is created and solved. When considering a stand alone system, that means tube, fin and PCM, without a connection to other components, investigation is quite effective. In case of the PCM storage there is the big advantage, compared with a sensible regenerator, that the almost constant fluid temperature, when evaporating or condensing, leads to a uniform temperature distribution in fluid flow direction. Therefore only a very rough discretisation in axial direction is needed, what even allows bonding with other components e.g. from the Modelica Fluid Library. Sensible storages as they are used for preheating and superheating have a characteristic temperature gradient in axial direction. To describe their thermal behaviour concentrated models, using dimensionless numbers, are used

The Constitution and the Recovery Legislation: The Roles of Document, Doctrine, and Judges

Matlab is a proprietary, interactive, dynamically-typed language for technical computing. It is widely used for prototyping algorithms and applications of scientific computations. Since it is a dynamically typed language, the execution of programs has to be analyzed and interpreted which results in lower computational performance. In order to increase the performance and integrate with Modelica applications it is useful to be able to translate Matlab programs to statically typed Modelica programs. This project presents the design and implementation of Matlab to Modelica translator. The Lexical and Syntax analysis is done with the help of the OMCCp (OpenModelica Compiler Compiler parser generator) tool which generates the Matlab AST, which is later used by the translator for generating readable and reusable Modelica code

Comparison of moving boundary and finite-volume heat exchangers models in the Modelica language

When modelling low capacity energy systems such as a small (5–150 kWel) organic Rankine cycle unit, the governing dynamics are mainly concentrated in the heat exchangers. As a consequence, accuracy and simulation speed of the higher level system model mainly depend on the heat exchanger model formulation. In particular, the modelling of thermodynamic systems characterized by evaporation or condensation, requires heat exchanger models capable of handling phase transitions. To this aim, the finite volume (FV) and the moving boundary (MB) approaches are the most widely used. The two models are developed and included in the open-source ThermoCycle Modelica library. In this contribution a comparison between the two approaches is performed. Their performance is tested in terms of model integrity and accuracy during transient conditions. Furthermore the models are used to simulate the evaporator of an ORC system and their responses are validated against experimental data collected on an 11 kWel ORC power unit

Building fault detection data to aid diagnostic algorithm creation and performance testing.

It is estimated that approximately 4-5% of national energy consumption can be saved through corrections to existing commercial building controls infrastructure and resulting improvements to efficiency. Correspondingly, automated fault detection and diagnostics (FDD) algorithms are designed to identify the presence of operational faults and their root causes. A diversity of techniques is used for FDD spanning physical models, black box, and rule-based approaches. A persistent challenge has been the lack of common datasets and test methods to benchmark their performance accuracy. This article presents a first of its kind public dataset with ground-truth data on the presence and absence of building faults. This dataset spans a range of seasons and operational conditions and encompasses multiple building system types. It contains information on fault severity, as well as data points reflective of the measurements in building control systems that FDD algorithms typically have access to. The data were created using simulation models as well as experimental test facilities, and will be expanded over time

Thermal System Oriented Simulation of Aircraft Electrical Environmental Control Systems Including its Electric Coupling

A flexible numerical platform based on libraries has been developed within the Dymola/Modelica framework to simulate Environmental Control Systems (ECS). The goal was to build up a flexible tool to analyse complex systems including their thermal and electrical perimeters at both steady and transient conditions focusing on three key characteristics: numerical robustness, optimal time consumption, and high accuracy. This document aims to underline both the most relevant features of the numerical tool and the main challenges addressed during its development. Some illustrative simulations are shown in order to highlight the tool capabilities.Peer ReviewedPostprint (published version

Hybrid Simulation Safety: Limbos and Zero Crossings

Physical systems can be naturally modeled by combining continuous and discrete models. Such hybrid models may simplify the modeling task of complex system, as well as increase simulation performance. Moreover, modern simulation engines can often efficiently generate simulation traces, but how do we know that the simulation results are correct? If we detect an error, is the error in the model or in the simulation itself? This paper discusses the problem of simulation safety, with the focus on hybrid modeling and simulation. In particular, two key aspects are studied: safe zero-crossing detection and deterministic hybrid event handling. The problems and solutions are discussed and partially implemented in Modelica and Ptolemy II

An assessment of the load modifying potential of model predictive controlled dynamic facades within the California context

California is making major strides towards meeting its greenhouse gas emission reduction goals with the transformation of its electrical grid to accommodate renewable generation, aggressive promotion of building energy efficiency, and increased emphasis on moving toward electrification of end uses (e.g., residential heating, etc.). As a result of this activity, the State is faced with significant challenges of systemwide resource adequacy, power quality and grid reliability that could be addressed in part with demand responsive (DR) load modifying strategies using controllable building technologies. Dynamic facades have the ability to potentially shift and shed loads at critical times of the day in combination with daylighting and HVAC controls. This study explores the technical potential of dynamic facades to support net load shape objectives. A model predictive controller (MPC) was designed based on reduced order thermal (Modelica) and window (Radiance) models. Using an automated workflow (involving JModelica.org and MPCPy), these models were converted and differentiated to formulate a non-linear optimization problem. A gradient-based, non-linear programming problem solver (IPOPT) was used to derive an optimal control strategy, then a post-optimization step was used to convert the solution to a discrete state for facade actuation. Continuous state modulation of the façade was also modeled. The performance of the MPC controller with and without activation of thermal mass was evaluated in a south-facing perimeter office zone with a three-zone electrochromic window for a clear sunny week during summer and winter periods in Oakland and Burbank, California. MPC strategies reduced total energy cost by 9–28% and critical coincident peak demand was reduced by up to 0.58 W/ft2-floor or 19–43% in the 4.6 m (15 ft) deep south zone on sunny summer days in Oakland compared to state-of-the-art heuristic control. Similar savings were achieved for the hotter, Burbank climate in Southern California. This outcome supports the argument that MPC control of dynamic facades can provide significant electricity cost reductions and net load management capabilities of benefit to both the building owner and evolving electrical grid

Generator Power Optimisation for a More-Electric Aircraft by Use of a Virtual Iron Bird

A prodedure is developed to minimise the generator design power within the electric power system of a future more-/ all-electric aircraft. This allows to save weight on the generators and on other equipment of the electic power system. Execution of the optimisation procedure by hand demonstrates the complexity of the problem. An automation of the process shows the capabilities of integrated modelling, simulation and optimisation tools