Deployment and control of adaptive building facades for energy generation, thermal insulation, ventilation and daylighting: A review

A major objective in the design and operation of buildings is to maintain occupant comfort without incurring significant energy use. Particularly in narrower-plan buildings, the thermophysical properties and behaviour of their façades are often an important determinant of internal conditions. Building facades have been, and are being, developed to adapt their heat and mass transfer characteristics to changes in weather conditions, number of occupants and occupant’s requirements and preferences. Both the wall and window elements of a facade can be engineered to (i) harness solar energy for photovoltaic electricity generation, heating, inducing ventilation and daylighting (ii) provide varying levels of thermal insulation and (iii) store energy. As an adaptive façade may need to provide each attribute to differing extents at particular times, achieving their optimal performance requires effective control. This paper reviews key aspects of current and emerging adaptive façade technologies. These include (i) mechanisms and technologies used to regulate heat and mass transfer flows, daylight, electricity and heat generation (ii) effectiveness and responsiveness of adaptive façades, (iii) appropriate control algorithms for adaptive facades and (iv) sensor information required for façade adaptations to maintain desired occupants’ comfort levels while minimising the energy use

Wireless sensors and IoT platform for intelligent HVAC control

Energy consumption of buildings (residential and non-residential) represents approximately 40% of total world electricity consumption, with half of this energy consumed by HVAC systems. Model-Based Predictive Control (MBPC) is perhaps the technique most often proposed for HVAC control, since it offers an enormous potential for energy savings. Despite the large number of papers on this topic during the last few years, there are only a few reported applications of the use of MBPC for existing buildings, under normal occupancy conditions and, to the best of our knowledge, no commercial solution yet. A marketable solution has been recently presented by the authors, coined the IMBPC HVAC system. This paper describes the design, prototyping and validation of two components of this integrated system, the Self-Powered Wireless Sensors and the IOT platform developed. Results for the use of IMBPC in a real building under normal occupation demonstrate savings in the electricity bill while maintaining thermal comfort during the whole occupation schedule.QREN SIDT [38798]; Portuguese Foundation for Science & Technology, through IDMEC, under LAETA [ID/EMS/50022/2013

Optimization of building performance via model-based predictive control

Il controllo predittivo basato su modello (MPC) è una tecnica di controllo avanzata che ha svolto un ruolo importante nella gestione di molti processi nel settore industriale. Oggi, nell’ottica di una gestione energetica efficiente degli edifici, l’utilizzo di questa strategia si sta dimostrando una soluzione promettente per ridurre al minimo i consumi e i costi energetici complessivi. Tuttavia, gli studi sulla sua fattibilità tecnica in edifici esistenti sono ancora in una fase iniziale. Pertanto, il risultato principale di questa tesi è la progettazione e lo sviluppo di un prototipo hardware e software per la verifica sul campo di un sistema di controllo predittivo, basato su modello, integrando un modello predittivo virtuale della porzione dell'edificio in esame, il controllore e l'interfaccia grafica per i dispositivi di monitoraggio e regolazione utilizzati. Inoltre, particolare attenzione è stata posta sulla fattibilità tecnica relativa all'implementazione di un tipico sistema MPC, che include un sottosistema di monitoraggio, un set di acquisizione dati e un metodo di identificazione del sistema per ottenere il modello per il controllore, mediante un approccio di modellazione grey-box. La fase di modellazione e l'approccio empirico sviluppato sono presentati nella prima parte di questa tesi di ricerca, mentre la parte centrale riguarda: lo sviluppo del prototipo di controllo predittivo, basato su modello, all'interno di uno strumento virtuale del software LabVIEW e la descrizione del test sperimentale, effettuato durante la stagione di riscaldamento, garantendo la normale operatività dell’edificio durante l'intero periodo di monitoraggio. Infine, è presentato lo studio sviluppato in ambiente di simulazione per indagare il potenziale della logica di controllo per la valutazione di scenari di riqualificazione. Il focus è sulla definizione dei principali componenti del simulatore MPC e sui risultati ottenuti testando uno degli scenari di intervento.Model Predictive Control (MPC) is an advanced control technique which has played an important role in the management of many processes in the industry sector. Nowadays, in the perspective of an efficient building energy management, the exploitation of this strategy is proving to be a promising solution for minimising overall energy consumptions and costs. However, investigations on the feasibility of the technique in real existing buildings are at an initial stage. Hence, the main outcome of this dissertation is the design and development of a prototype hardware and software set up for on-field testing of a model-based predictive control system, integrating a virtual predictive model of the portion of the building under investigation, the controller and the interface to the monitoring and regulation devices used. Moreover, this research is addressed to investigate the technical feasibility of the development and deployment of a typical MPC system, which includes a monitoring sub-system, a data acquisition set up and a system identification method to obtain the model for the controller by means of a grey-box modelling approach. The modelling phase and the empirical approach developed are presented in the first part of this research thesis, while the core part concerns: the development of the MPC prototype, within a virtual instrument of LabVIEW software and the description of the experimental test, which was carried out during heating season, ensuring normal building operation during the entire monitoring period. Finally, this dissertation presents the study developed in simulation environment to investigate the potential of the control logic for the evaluation of retrofitting scenarios. The focus is on the definition of the main MPC simulator components and on the results obtained by testing one of the intervention scenarios

A PV/T and Heat Pump based trigeneration system model for residential applications

A solar trigeneration system, based on photovoltaic-thermal (PV/T) collectors, photovoltaic (PV) modules and a heat pump unit for heating and cooling, is modelled to forecast the thermal and electric yields of the system. The aim of the trigeneration system is to provide enough electricity, domestic hot water (DHW), heating and cooling power to meet the typical demand of an urban single family dwelling with limited roof area and allow the household to achieve a positive net energy status. The PV/T collectors and PV modules provide the electricity while the former also powers the DHW component of the trigeneration system. The heating and cooling components rely on a vapour compression cycle heat pump unit powered by electricity. In Fong et al. (2010), solar-powered electric compression refrigeration was found to have the most energy saving potential in subtropical climates. Thus, a heat pump based cooling system is a cost effective solution for residential applications in Lisbon,Portugal. Thus, according to the dwelling's location, construction details and energy demand patterns, the model computes the system's net results by comparing the dwelling demand with the trigeneration system supply. The paper presents a breakdown of the proposed trigeneration system model and describes each component briefly. Preliminary results produced by the model are presented and analysed in order to identify possible ways of improving the overall system performance

Institutional smart buildings energy audit

Smart buildings and Fuzzy based control systems used in Buildings Management System (BMS), Building Energy Management Systems (BEMS) and Building Automation Systems (BAS) are a point of interests among researcher and stake holders of buildings’ developing sector due to its ability to save energy and reduce greenhouse gas emissions. Therefore this paper will review, investigates define and evaluates the use of fuzzy logic controllers in smart buildings under subtropical Australia’s subtropical regions. In addition the paper also will define the latest development, design and proposed controlling strategies used in institutional buildings. Furthermore this paper will highlight and discuss the conceptual basis of these technologies including Fuzzy, Neural and Hybrid add-on technologies, its capabilities and its limitation

Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.Comment: 28 pages, Published 21 April 2015 at MDPI's journal "Sensors

Supervisory model predictive control of building integrated renewable and low carbon energy systems

To reduce fossil fuel consumption and carbon emission in the building sector, renewable and low carbon energy technologies are integrated in building energy systems to supply all or part of the building energy demand. In this research, an optimal supervisory controller is designed to optimize the operational cost and the CO2 emission of the integrated energy systems. For this purpose, the building energy system is defined and its boundary, components (subsystems), inputs and outputs are identified. Then a mathematical model of the components is obtained. For mathematical modelling of the energy system, a unified modelling method is used. With this method, many different building energy systems can be modelled uniformly. Two approaches are used; multi-period optimization and hybrid model predictive control. In both approaches the optimization problem is deterministic, so that at each time step the energy consumption of the building, and the available renewable energy are perfectly predicted for the prediction horizon. The controller is simulated in three different applications. In the first application the controller is used for a system consisting of a micro-combined heat and power system with an auxiliary boiler and a hot water storage tank. In this application the controller reduces the operational cost and CO2 emission by 7.31 percent and 5.19 percent respectively, with respect to the heat led operation. In the second application the controller is used to control a farm electrification system consisting of PV panels, a diesel generator and a battery bank. In this application the operational cost with respect to the common load following strategy is reduced by 3.8 percent. In the third application the controller is used to control a hybrid off-grid power system consisting of PV panels, a battery bank, an electrolyzer, a hydrogen storage tank and a fuel cell. In this application the controller maximizes the total stored energies in the battery bank and the hydrogen storage tank

Reduced Order Modeling for Virtual Building Commissioning

Model order reduction can help reduce the time and monetary constraints associated with building commissioning and significantly decrease overall building energy consumption through virtual commissioning. This research aimed to determine the effectiveness of using reduced order models to simulate the overall building energy consumption, and to estimate the energy savings from control-based commissioning recommendations. A case study building was modeled using a ‘Lumped RC’ thermal model with three thermal resistances and capacitances (3R3C) for the building interior and a 2R1C model describing the building foundation. Due to energy consumption being dependent on building systems, this model was coupled with a simplified HVAC model to translate indoor zone temperature predictions into total annual energy consumption. The coupled reduced order model (ROM) model was compared to an identical model constructed in EnergyPlus, and it was determined that a reduced order model was capable of predicting annual energy consumption. The case study building lacked thermostat setbacks during periods the building was unoccupied, and the ROM was used to predict the energy savings associated with updating the controller. It was found that approximately 104,000 kWh of potential energy savings could be realized if the thermostat had properly programed temperature setbacks during times the building is unoccupied