Building Energy Monitoring System Research Articles

Application research of deep learning-based BIM Technology in Intelligent Construction

Abstract With the increasing importance of energy-efficient renovations in architecture, the pressing issue of how to enhance the effectiveness of such renovations through advanced technology has come to the forefront. This article affirms the significance of building information modeling (BIM) technology in energy consumption renovations. It introduces a BIM-based building energy monitoring system, which not only provides comprehensive and effective static information for energy consumption analysis but also offers real-time visualization of energy consumption status for daily management. By collecting all necessary data for energy management and storing it in the cloud, this system greatly facilitates data analysis. Moreover, the article proposes a short-term electricity load forecasting method for community buildings based on empirical mode decomposition (EMD)-gated recurrent unit (GRU). The EMD-GRU method proposed in this article exhibits superior accuracy compared to other methods, with a mean absolute percentage error value of 14.43%. By considering factors such as historical load, weather, and date, this method accurately predicts short-term electricity loads for communities. This research provides a robust framework for improving energy management in buildings through advanced technologies, ultimately leading to more effective energy-saving renovations and optimizations.

Development and realization of the electric energy monitoring system for cloud-based intelligent buildings

With the in-depth development of cloud computing technology and the continuous application of various new technologies in the process of modern building construction, the application of embedded technology, communication sensing technology, cloud computing technology and other technologies to create energy-saving building energy monitoring systems has become a research hotspot. This paper first compares and analyzes the network structure of the traditional building energy monitoring system and cloud-based building energy monitoring system, and then focuses on the overall architecture of the system and the design and implementation of the terminal intelligent monitoring unit. On the one hand, the development of building energy monitoring system based on cloud computing realizes cloud processing of building energy monitoring. On the other hand, the control strategy formulated by big data effectively improves the overall energy saving efficiency of the building.

IoT Based Building Energy Monitoring and Controlling System Using LoRa Modulation and MQTT Protocol

Building energy monitoring systems are carried out to facilitate the monitoring and controlling of building energy consumption. Monitoring and controlling the use of electrical energy in real-time in a building has an impact on the pattern of regulating the efficiency level of energy use. This paper presents an effort to optimize energy consumption by using an energy management system using LoRa modulation and MQTT protocols. Sensors that feed electrical power data to a custom energy monitoring system are compiled by a set of sensors equipped with a power supply that is fastened to the system on a microcontroller with a LoRa communication interface then are called nodes. The nodes consist of arduino uno as a microcontroller, dragino LoRa Shield, ACS712 current sensor, ZMPT101B voltage sensor, and relay. Dragino LoRa Gateway LG01-N is used to connect the measured parameters to the IoT cloud server. MQTT protocol is used for the broker between nodes and servers using subscribe and publish method. In the initial experiments, the data visualization platform used was the open-source thingspeak platform. This platform includes a data visualization template and enables device control for savings. In the end nodes, the voltage, current, and power sensor accuracy error are 1,24%, 2.60%, and 3.13%.

Energy-saving Analysis of Energy Consumption in Public Buildingsand Case Application

This paper introduces the basic principles and characteristics of the energy consumption monitoring system, design situation, equipment parameters, system form and application examples of energy consumption monitoring system in public buildings, explains the role of public building energy monitoring system. Starting from the artificial collection and data transmission, this paper analyzes the application status of public building energy consumption monitoring technologies, and based on this, proposes application countermeasures based on energy conservation management under public building energy consumption monitoring system, which can provide some references for energy-saving application technology in public buildings.

Reliable data transmission method based on 6LoWPAN for building energy systems

The building energy internet of things is based on radio frequency technology and a wireless sensor network that can collect building energy consumption data in real time. However, with the increasing complexity of wireless sensor network topology, there is a problem of insufficient IP address space relying on IPv4 protocol. In this paper, a design scheme of a building energy system based on 6LoWPAN network is proposed. IPv4/IPv6 address conversion is used to realise the access of IP addresses to each other, so as to monitor building energy consumption information anytime and anywhere. In view of the shortcomings of existing wireless network data transmission methods in low energy consumption and high reliability in building energy monitoring applications, a reliable data transmission method based on multipath routing coding algorithm is proposed. This strategy improves the transmission reliability of the network by increasing the number of redundant packets, and reduces the energy consumption of the network by reducing the number of transmission paths. The simulation results show that the proposed method can effectively improve the success rate of data packet transmission, reduce the standard energy consumption of sensor networks, and provide an effective method for the application of wireless sensor networks in building energy monitoring systems. Practical application: This paper studies how to improve transmission reliability and energy efficiency in cluster-based WSN and proposes a multi-path transmission strategy for selective coding of intermediate cluster head nodes. The strategy improves the transmission reliability of the network by increasing the number of transmissions of redundant packets and reduces the network energy consumption by reducing the number of transmission paths. It has good use value for the actual development and application of the building energy consumption monitoring system.

Monitoring System Analysis for Evaluating a Building's Envelope Energy Performance through Estimation of Its Heat Loss Coefficient.

The present article investigates the question of building energy monitoring systems used for data collection to estimate the Heat Loss Coefficient (HLC) with existing methods, in order to determine the Thermal Envelope Performance (TEP) of a building. The data requirements of HLC estimation methods are related to commonly used methods for fault detection, calibration, and supervision of energy monitoring systems in buildings. Based on an extended review of experimental tests to estimate the HLC undertaken since 1978, qualitative and quantitative analyses of the Monitoring and Controlling System (MCS) specifications have been carried out. The results show that no Fault Detection and Diagnosis (FDD) methods have been implemented in the reviewed literature. Furthermore, it was not possible to identify a trend of technology type used in sensors, hardware, software, and communication protocols, because a high percentage of the reviewed experimental tests do not specify the model, technical characteristics, or selection criteria of the implemented MCSs. Although most actual Building Automation Systems (BAS) may measure the required parameters, further research is still needed to ensure that these data are accurate enough to rigorously apply HLC estimation methods.

A Methodology to Identify Multiple Equipment Coordinated Control with Power Metering System

Modern buildings are equipped with advanced Building Energy Monitoring System (BEMS) for energy supervision and management. To fully leverage the power of this system, a dynamic real time data analysis to understand the building operational strategies is critical. Considering the significant volume of building energy data, a computer aided technique is necessary for any this kind of analysis. However, until now, there still lacks an effective method to automatically identify building operational strategies. In this paper, a new methodology targeting at identify multiple equipment coordinated control is proposed, which adopts Symbolic Aggregation AproXimation (SAX) as data pre-processor and performs a weighted association rule mining algorithm (WARM) to identify the coordinated control strategy. Case studies show that the proposed framework can effectively identify schedule based operational strategies and detect abnormal energy use behavior.

Design of Building Energy Consumption Monitoring System

Building energy consumption has become large energy consumption in our country. In order to realize the full range of buildings energy-saving, this paper designed a building energy monitoring system and which can effective measure, monitor, control and regulate each energy equipment and systems within the building. It makes a large number of dispersed energy data sort, optimization, control and reasonable allocation by combining networking technology and cloud computing technology, forming the construction of community energy overall control, optimization, service and redistribution system. Finally realizes the monitoring, control of buildings energy consumption, achieving the purpose of saving the energy.

Continuous Commissioning Through Real-Time Simulation with a Building Energy Monitoring System

Continuous Commissioning Through Real-Time Simulation with a Building Energy Monitoring System

Comparison of building energy use data between the United States and China

Buildings in the United States and China consumed 41percent and 28percent of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.-China Clean Energy Research Center for Building Energy Efficiency. The goal is to decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply.

Building Energy Audit and Energy-Saving Analysis for a Five-Star Hotel in Beijing

Building energy audit and equipment energy-saving assessment are an important part of the building energy monitoring system in the construction. This paper takes a five-star hotel in Beijing as an example and audits the building energy consumption of the hotel. By testing air conditioning chillers, chilled water pumps, cooling water pumps and other equipments analyses energy-saving potentiality of the conditioning system and lighting equipments. The results would help us put forward some sound energy-saving measures, regulatory frameworks and reduce energy equipment consumption.

A Novel Method for Detecting Abnormal Energy Data in Building Energy Monitoring System

This paper presents a novel abnormal data detecting algorithm based on the first order difference method, which could be used to find out outlier in building energy consumption platform real time. The principle and criterion of methodology are discussed in detail. The results show that outlier in cumulative power consumption could be detected by our method.

Benchmarking model for the ongoing commissioning of the refrigeration systemof an indoor ice rink

Abstract This paper proposes the development of the benchmarking model for the ongoing commissioning of the operation of the refrigeration system of an indoor ice rink. The paper presents (1) the development of models for chillers, ice-concrete slab and controller, (2) the training phase in which the parameters of the benchmarking model are identified based on measurements under normal operating conditions, and (3) the comparison between measured and predicted energy performances. The proposed approach for the development of a benchmarking model can be implemented as application software in the Building Energy Monitoring System of any ice skating rink, if measurements of relevant independent variables are available.

Based on Large Public Building Energy Monitoring System of Things

The existing energy use for real-time monitoring, to the statistical data of system analysis, main factors determining energy consumption, through the computer, mobile phone, PDA and other port monitoring display. According to the specific energy consumption situation in the development of targeted energy-saving plan, adopt infrared intelligent switch, air conditioning control, efficient lighting, infrared remote sensing switches and other measures to achieve energy-saving emission reduction demonstration effect.