IBPSA2015

This paper presents a new methodology of machine aided HVAC system optimization with currently available building simulation and optimization frameworks. The method consists of a two part approach using Modelica for accurate but simple system simulation as well as Matlab for automated model configuration, result evaluation and parameter variation.

The paper focuses on control optimization of nonlinear system models where the differential-algebraic equations are formulated in Modelica. Two optimiziation approaches utilizing (i) direct search methods and (ii) derivative-based methods are compared. The approaches are applied to a thermohydraulic low-exergy heating and cooling system model in form of a borehole heat exchanger, a heat pump, a hydraulic distribution system, thermally activated building systems (TABS) and a simplified building model.

In previous studies, the authors combined load shifting and Model-based Predictive Control (MPC) for the optimization of a HVAC system. The precision of the predicted model outputs (primary energy, comfort in temperature and peak heat flow rate) depends on the accuracy of several factors (model parameters, inputs and initial state).

This research aims to define a modelling approach to simulate District Cooling Systems (DCS). A model of the network has been developed using the equation-based object-oriented language Modelica. This model includes a cooling production plant, a distribution network of pipes and 6 substations. This integrated modelling approach allows us to study interactions between substations cooling demand and cooling production plant efficiency. Hourly measurements from Eastern Paris DCS are used as inputs for cooling demand. A simplified model of substations with ideal control has been developed.

A simulation model is developed that allows to investigate the infection risk for Legionella Pneumophila in the design phase of a DHW system and to test the effectiveness of disinfection techniques on an infected system. With the thermodynamic model, the Legionella P. infection risk of the DHW recirculation loop in a case study building is assessed and important components for an optimization study on the trade-off between infection risk and energy efficiency are identified. 

The major goal of this study is to demonstrate the feasibility of the dynamic modeling and simulation of both conventional and direct exchange geothermal heat pump applications particularly with regard to performance evaluations. Therefore, in this research, dynamic models for the simulation of geothermal heat pump systems with the working fluid propane for the application in building-scale energy systems have been developed based on the Moving Boundary approach and the challenges of dynamically evaluating these kind of energy systems have been hereby met.

This paper presents a new approach to calibrate air handling unit models. This approach studies every heat exchanger component separately based on the inverse problem framework, the Preisach model of hysteresis and machine learning techniques. For each component model, the first step is to solve the inverse problem in order to calculate the optimal control signal that generates the output values expected from real data.

In this paper, four different data-driven algorithms including AutoRegressive with eXternal inputs (ARX), State Space (SS), Subspace state space (N4S) and Bayesian Network (BN) are evaluated and compared using a case study of predictions of Air Handler Unit (AHU) thermal energy consumption. Training and testing data are generated from a dynamic Modelica-based AHU model.

This paper presents a methodology of simultaneous sizing of building envelope and heating system integrating management strategies in sketch phase. This method uses a global optimization approach taking into consideration a lot of parameters and constraints. Our goal is to implement it in performance software tools, which allow architects and designers to analyze and quickly compare design solutions taking into account the cost over the building life cycle (including the envelope investment, heating system investment and operating cost) with respect to the need of comfort and budget.

Ceiling fans recirculate air within a space and affects the comfort of the occupant. It is widely used in India. It reduces the perceived temperatures by assisting cooling by evaporation through skin. Many mathematical models and studies are available which show the variation of comfort temperatures subsequent calculation of discomfort hours with varying ceiling fan air speed.Studies have also shown deviations of local comfort surveys with the PMV/PPD and ASHRAE adaptive standards in predicting human comfort.