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

Building energy performance diagnosis using energy bills and weather data

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.

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

Building energy management systems (BEMS) are integrated computerized systems that track and manage the energy use of many pieces of building-related machinery and equipment, including lighting, power systems, and HVAC systems. Modern buildings must have BEMSs in order to reduce energy usage while maintaining comfort. Not only for energy-saving purposes, BEMS is essential in enhancing the quality of the energy supply, which helps to gain a better understanding of how energy is used and the building's energy usage. When the dynamics of a building's energy usage are known, it is possible to determine which changes are most likely to reduce consumption. Numerous connected devices, operating modes, energy usage, and environmental factors can all be monitored and controlled in real-time using BEMS. Changing operating times and setting points to maximize comfort and efficiency is made simple by this. In this paper, we have primarily addressed the two significant issues of model optimization and electricity consumption forecasts. Future forecasting has been done using the LSTM based time series approach. We generated data on the amount of electricity consumed by a hospital facility and tested our suggested methodologies on actual data. The findings gained demonstrated that the strategies were successful with both types of data. On actual data, the trend in electricity consumption can be accurately predicted. Several model optimizers enhanced the suggested methods' performance as well. Our objective function gain accuracy result of 95%.

How do green roofs affect per capita energy consumption in residential buildings under various climate conditions?

An increase in the world population has led to a sharp decrease in fossil fuel sources; and, therefore, substituting them with renewable sources as well as optimizing energy consumption could be considered ideal solutions. One of the major problems is the excessive use of energy in residential buildings, with Iran's consumption rate in this field being five times the global average. Building facades play a fundamental role in optimizing energy consumption. This paper aims to study the factors affecting the performance of coherent facades in terms of climatic conditions, using a comparative study between traditional-indigenous and modern building facades in the city of Mashhad. In addition, it employs an analytical descriptive method and applies case analysis by numerical calculations as well as software simulations using the DesignBuilder software tool. Other researchers have conducted similar studies, but no comprehensive research has yet been done by making a comparison between traditional-indigenous buildings and modern buildings in Mashhad, Iran, with existing climatic conditions considered. By studying and comparing the window-to-wall ratio, building materials, and facade thickness, it was concluded that the ratio of openings to walls was 20–35% and 30–42% in traditional-indigenous houses and in modern houses, respectively. Similarly, the range of the thermal resistance of facades in traditional buildings was 0.56–0.87 (m2C/W), and it was 0.38–0.48 m2C/W in modern buildings. The analysis of the simulated models showed less thermal dissipation in traditional models than in modern ones. Thus, traditional-indigenous models are more optimized when it comes to energy consumption, apart from creating thermal comfort for building residents. By referring to past architecture and gaining inspiration from the features of traditional building facades in constructing modern buildings, we will be able to help reduce energy consumption in these buildings.

The rising global demand for energy is best addressed by adopting and promoting sustainable methods of power consumption. We employ an informatics approach towards forecasting the energy consumption patterns in a university campus micro-grid which can be used for energy use planning and conservation. We use novel indirect indicators of energy that are commonly available to train regression tree models that can predict campus and building energy use for coarse (daily) and fine (15-min) time intervals, utilizing 3 years of sensor data collected at 15min intervals from 170 smart power meters. We analyze the impact of individual features used in the models to identify the ones best suited for the application. Our models show a high degree of accuracy with CV-RMSE errors ranging from 7.45% to 19.32%, and a reduction in error from baseline models by up to 53%.

Commercial building energy use in six cities in Southern China

Spatial distribution of building energy use in the United States through satellite imagery of the earth at night

Urban microclimate and its impact on building performance: A case study of San Francisco

Physics-informed ensemble learning with residual modeling for enhanced building energy prediction

Worldwide, the current energy system increasingly shows economic, social and environmental drawbacks and it does not appear to be sustainable. Among the most pressing problems are climate change due to CO2 emissions, the depletion of fossil resources, the security of energy supply, and threats to economic development. These problems can be addressed by moving towards energy systems that increasingly rely on renewable and sustainable energy sources. At the same time, the rapid progress in renewable energy harvesting and information and telecommunication technologies offer unprecedented opportunities for energy generation, distribution and management, and to more strongly involve people in the process of energy generation and management, which is needed to further enhance the sustainable energy systems. Indeed, renewable and sustainable energy sources are likely to be produced and distributed in a decentralised manner, and require energy management systems that differ greatly from the current centralised system. Hence, the integration of renewable sources has major implications for the design and management of energy systems, relying on innovative ICT solutions and stronger user involvement that facilitate supply and demand matching. Effective energy management requires the active participation and support of end users, who should accept the energy management systems, and adapt their energy use to the available demand as to enhance the efficiency and stability of the energy system. Hence, the design of future smart grids should be based on sound behavioural models, which should be integrated in ICT centred solutions that facilitate supply and demand matching. More specifically, we need to understand how truly complex information on energy production, use and storage can be effectively communicated among relevant actors, and what type of information and incentives should be provided to realise effective supply and demand matching. In addition, we need to understand how to take into account cultural specifics in the design of energy management systems, to enhance effective energy management across the world. The active and aware involvement of the end-user can only be achieved if a scalable and reliable ICT infrastructure is in place, which naturally interfaces the energy flows with the decision autonomy of the people. Hence, the design of effective energy management systems should be take into account key behavioural as well as ICT requirements in an integrated way. Our proposal is thus to investigate (1) ICT based solutions for monitoring and controlling the power grid focusing on the distribution networks (medium-low voltage) and buildings (offices and residential complexes) specific to the Qatar context; (2) behavioural models on effective and acceptable incentives to match energy supply and demand; (3) cultural specificities in the design of energy management systems by comparing results from research in Qatar to similar research in other parts of the world, in particular Europe. Together, these will provide important insights in how to promote efficient and stable renewable energy systems that meet Qatar's sustainability goals.

Rapid urbanization, climate change, and aging infrastructure pose significant challenges to achieving sustainability and resilience goals in urban building energy use. Although retrofitting offers a viable solution to mitigate building energy use, there has been limited analysis of its effects under various weather conditions associated with climate change in urban building energy use simulations. Moreover, certain parameters in energy simulations necessitate extensive auditing or survey work, which is often impractical. This research proposes a framework that integrates various datasets, including building footprints, Lidar data, property appraisals, and street view images, to conduct neighborhood-scale building energy use analysis using the Urban Modeling Interface (UMI), an Urban Building Energy Model (UBEM), in a coastal neighborhood in Galveston, Texas. Seven retrofit plans and three weather conditions are considered in the scenarios of building energy use. The results show that decreasing the U-value of building envelopes helps reduce energy use, while increasing the U-value leads to higher energy consumption in the Galveston neighborhood. This finding provides direction for coastal Texas cities, like Galveston, to update building standards and implement retrofit measures.

Building energy use in China: Ceiling and scenario

The warming urban climates increase the building energy consumption by changing the heating/cooling loads of the buildings. On the other hand, building induced anthropogenic heat emissions can also contribute to the urban heating, creating a warming feedback loop. Such impact is more profound in the (sub)tropical and hot/arid context, where Air Conditioning (AC) systems are widely used. A better understanding of the building energy consumption and its contribution to urban heating can therefore help mitigate urban heating. To this end, we aim to estimate building energy use and induced heat emissions in Kuala Lumpur, Malaysia, using both a bottom-up strategy based on building energy modelling and a top-down strategy based on national scale energy inventory. We further integrate the building energy model with measured diurnal temperature profiles at different land use areas, to discuss the impact of urban heat island (UHI) on energy use, and potential mitigation strategies through different urban morphologies. The estimated energy use obtained via both bottom-up and the top-down approaches were within the range of actual energy use from case studies available for Kuala Lumpur. It also highlights the need to adapt multi-scale strategies to mitigate the building energy use, and the associated impacts on the UHI.