Building Energy Management

Commercial buildings consume a considerable amount of the world’s energy and this can be substantially reduced through strategic monitoring and optimization of their energy consumption. Hence, monitoring and managing the available electrical power is a very important part of conserving energy resources, reducing greenhouse gas emissions and cutting down energy expenses. An attempt has been made to model and simulate the HVAC (Heating, Ventilation and Air-Conditioning) system for a typical commercial building, which consumes the most electrical power in such buildings. The various components of an HVAC system were mathematically modeled and were integrated to simulate real-time energy and process parameters. A software application was developed using LabVIEW, which enables the user to configure the system parameters through a Human Machine Interface (HMI). The HMI would enable building design engineers to design and set-up an effective Energy Management System, and test such designs with negligible cost and minimal complexity compared to that involved in using physical loads.

Energy prediction models are used in buildings as a performance evaluation engine in advanced control and optimisation, and in making informed decisions by facility managers and utilities for enhanced energy efficiency. Simplified and data-driven models are often the preferred option where pertinent information for detailed simulation are not available and where fast responses are required. We compared the performance of the widely-used feed-forward back-propagation artificial neural network (ANN) with random forest (RF), an ensemble-based method gaining popularity in prediction – for predicting the hourly HVAC energy consumption of a hotel in Madrid, Spain. Incorporating social parameters such as the numbers of guests marginally increased prediction accuracy in both cases. Overall, ANN performed marginally better than RF with root-mean-square error (RMSE) of 4.97 and 6.10 respectively. However, the ease of tuning and modelling with categorical variables offers ensemble-based algorithms an advantage for dealing with multi-dimensional complex data, typical in buildings. RF performs internal cross-validation (i.e. using out-of-bag samples) and only has a few tuning parameters. Both models have comparable predictive power and nearly equally applicable in building energy applications.

Energy management is becoming a priority as organizations strive to reduce energy costs, conform to regulatory requirements, and improve their corporate image. Despite the upsurge of interest in energy management standards, a gap persists between energy management literature and current implemen- tation practices. This gap can be traced to the lack of an incremental improvement roadmap. In this paper we propose an Energy Management Maturity Model that can be used to guide organizations in their energy management implementation efforts to incrementally achieve compliance with energy management standards such as ISO 50001. The proposed maturity model is inspired on the Plan-Do- Check-Act cycle approach for continual improvement, and covers well-understood fundamental energy management activities common across energy management texts. The completeness of our proposal is then evaluated by establishing an ontology mapping against ISO 50001.

Se presentan 20 documentos originales de utilidad en para administrar la ejecución de proyectos de ahorro y uso eficiente de energía para vehiculos automotores, embarcaciones a vela, nuevos inmuebles comerciales, reconversión de edificaciones del sector público y nuevas construcciones para vivienda.  Para fínes de entrenamiento en el trabajo, este material metarial es complemento de:  Gamboa Rocha, Ricardo Xavier et al.  “Entrenamiento en gestión de proyectos de ahorro y uso eficiente de energía:  Materiales de apoyo, para la formulación de propuestas”, Cuadernos Metodológicos en Línea.  Número 9, Antología de documentos para formular propuestas de AUEE.  Serie: Formación en el manejo de la componente tecnológica desarrollada.  2 de octubre del 2016.  Editorial  Ciencia y Tecnología Aplicada en Línea CITALI.  CEPROS AC. 142 páginas.  Chetumal, Quintana Roo, México.  https://www.academia.edu/30938948/

One of the most cost effective ways to save energy in commercial buildings is through designing a dedicated controller for adjusting environmental set-points according occupancy flow. This paper presents the design of a fuzzy rule-based supervisory controller for reducing energy consumptions while simultaneously providing comfort for passengers in a large airport terminal building. The inputs to the controller are the time schedule of the arrival and departure of passenger planes as well as the expected number of passengers, zone global illuminance (daylight) and external temperature. The outputs from the controller are optimised temperature, airflow and lighting set-point profiles for the building. The supervisory controller was designed based on expert knowledge in MATLAB/Simulink, and then validated using simulation studies. The simulation results demonstrate significant potential for energy savings in the controller's ability to maintain comfort by adjusting setpoints according to the flow of passengers.

Phase change materials (PCMs) can beneficially work as a successful thermal energy storage medium in different applications. PCMs have shown a remarkable enhancement in building energy-saving and thermal comfort in hot locations. In this paper, the thermal behaviour of a PCM-enhanced thermally-poor building envelope is studied experimentally. To this aim, two identical rooms, one loaded with PCM (PCM room) and the other without (reference room), are built and tested under a severe hot climate of Al Amarah city, Iraq. Previously examined parameters, such as the optimal position and thickness of the PCM layer in the roof and the best-thermally performed PCM capsules integrated concrete bricks, are considered to build the PCM room. Several energetic and thermal comfort indicators such as maximum temperature reduction (MTR), average temperature fluctuation reduction (ATFR), decrement factor (DF), time lag (TL), operative temperature difference (OTD), discomfort hours reduction (DHR) and maximum heat gain reduction (MHGR) are determined and discussed to show the potential of PCM. The experimental results revealed that the incorporated PCM could remarkably improve the thermal performance of building envelope exposed to high outdoor temperatures. Amongst envelope elements and compared with the reference room, the roof and east wall of the PCM room recorded the best thermal behaviour, where the MTR difference, ATFR, DF, and TL difference reached 3.75 °C, 6.5 °C, 25.6%, 70 min for the roof, and 2.75 °C, 2.4 °C, 12.8% and 40 min for the east wall, respectively. Moreover, the PCM room shows a thermal comfort enhancement by 11.2% and 34.8%, considering the DHR and MHGR, respectively, compared with the reference one. The study highlighted that suitable ventilation means are necessary to improve the building performance and reach acceptable thermal comfort when the PCM is incorporated passively.

Energy renovation is instrumental for reaching the EU 2020 goals and smart districts are integral parts for the development of Smart Cities in the next future. At building scale, every structure runs differently and energy consumption profiles depends not only on climatic locations and technological quality of buildings, but also on occupancy levels and different types of public utility buildings (school, healthcare and homes for the elderly, office, university). A new smart regeneration approach will represent the central focus beyond a simple technological concept of Smart Building, where the buildings should be seen as part of a larger system of energy networks and whose diffusion within the city could be linked with the concept of urban energy network and physical " nodes ". Currently good practices and projects aims to promote the adoption of the key technology and to identify and remove barriers to deployment, still today approaches to record non-residential assets in a comparable structure have not been successfully implemented yet and data are fairly poor. An integrated approach is proficient to reveal the performance of the innovation, its technical requirement, as well as prerequisite required in terms of existing infrastructures, technical expertise, regulatory requirements and financial costs involved. An ongoing research from the PDTA Dept. is promoting a set of exemplary of public utility buildings and a portfolio of material, industrialized systems, smart and energy equipment solutions to be used in refurbishment projects, in order to stimulate a whole vision of the smart efficient buildings and different scenarios according the boundaries of a smart district level in Rome Municipality.

An Energy Management a monitoring tool that tracks buildings energy con- sumption with the purpose of enhancing energy effi- ciency, by identifying savings opportunities and misuse situations. To achieve this, EMSs collect data flows— data streams—from a network of energy meters and sensors, which are then combined into useful informa- tion. Data must be processed in real-time, to support a timely decision making process. Traditionally EMSs use Database Management Systems (DBMSs) to process data, introducing a persistence step that leads to an unacceptable latency on data evaluation and do not properly support many types of time-series queries. This work explores the feasibility of Data Stream Man- agement Systems (DSMSs) to support Energy Manage- ment applications, pointing out how to implement an EMS capable of real-time data processing.

- The Human-Robot Cloud has previously been introduced
as a framework for the creation of distributed, ondemand,
reconfigurable human-machine cognitive systems.
These systems are made up of sensing, processing, and actuation components that are not limited to a specific type of application and potentially can be extended to multiple domains and may cover spatially smaller or larger areas. In this paper, we revisit the Human-Robot Cloud architecture and present its pilot deployment on the campus of NCSR Demokritos, a research institution in Greece. In particular, our concrete deployment aims to be demonstrated in three specific application scenarios; namely, Human-Aware Smart Buildings with Energy Optimization, Security and Surveillance, and Smart Tour Guide System. In this paper, we present in detail an example implementation of the Smart Buildings scenario: a real-world application with immediate benefits in energy optimization and energy savings. Environmentally
sensitive issues, such as the ground-up development of energy
efficient buildings or reducing the environmental impact of the
existing infrastructure, has received much attention in the past.
However, the traditionally offered solutions are central, nontransferable to other infrastructure, non-scalable and suffer from single points of failure. On the contrary, in this work, which is based on a specialization of the generic Human-Robot Cloud architecture, we attempt to move beyond the industrially available solutions to meet the requirements for scalable, reconfigurable and redistributable sensory, processing, and actuation units within buildings. A set of cameras, laser range finders, and other sensors, together with a number of processing and actuation elements, including face detection, expression recognition, and people trackers, are transformed to a prototypical reconfigurable distributed extended cognitive system, which can support multiple applications in the future.

Reducing building energy consumption has received growing attention in the recent decades.
The primary energy consumption in buildings is related to heating, ventilation, cooling, and lighting systems.
A well-design control system may result in a significant reduction of energy usage. This paper presents and
implements three strategies to control and analyze energy consumption in buildings. The schedule, real-time
monitoring and a multi-agent system are compared with the baseline energy consumption in a university
office. Devices and human agents are introduced to investigate the real-time trend in energy usage and to
optimize the consumption of energy, based on the location of occupants. Initial results demonstrate potential
energy saving of 16% in the office.

Phase change materials (PCMs) can beneficially work as a successful thermal energy storage medium in different applications. PCMs have shown a remarkable enhancement in building energy-saving and thermal comfort in hot locations. In this paper, the thermal behaviour of a PCM-enhanced thermally-poor building envelope is studied experimentally. To this aim, two identical rooms, one loaded with PCM (PCM room) and the other without (reference room), are built and tested under a severe hot climate of Al Amarah city, Iraq. Previously examined parameters, such as the optimal position and thickness of the PCM layer in the roof and the best-thermally performed PCM capsules integrated concrete bricks, are considered to build the PCM room. Several energetic and thermal comfort indicators such as maximum temperature reduction (MTR), average temperature fluctuation reduction (ATFR), decrement factor (DF), time lag (TL), operative temperature difference (OTD), discomfort hours reduction (DHR) and maximum heat gain reduction (MHGR) are determined and discussed to show the potential of PCM. The experimental results revealed that the incorporated PCM could remarkably improve the thermal performance of building envelope exposed to high outdoor temperatures. Amongst envelope elements and compared with the reference room, the roof and east wall of the PCM room recorded the best thermal behaviour, where the MTR difference, ATFR, DF, and TL difference reached 3.75 °C, 6.5 °C, 25.6%, 70 min for the roof, and 2.75 °C, 2.4 °C, 12.8% and 40 min for the east wall, respectively. Moreover, the PCM room shows a thermal comfort enhancement by 11.2% and 34.8%, considering the DHR and MHGR, respectively, compared with the reference one. The study highlighted that suitable ventilation means are necessary to improve the building performance and reach acceptable thermal comfort when the PCM is incorporated passively.

Information technology tools for energy management have, to date, failed to take advantage of the recent advances in human-computer interaction. In fact, considerable expertise is still required to interpret and manage energy data. Other domains, in contrast, including architecture, engineering and construction, have embraced new interaction paradigms aiming at more natural ways to interact with and analyse data. We foresee that integrating natural user interfaces with virtual and augmented reality environments in an energy management system will provide a powerful tool, enabling unskilled users to perform complex energy management activities.