Campus Energy Use Research Articles

Research on Key Technologies of Campus Microgrid Control

Taking campus microgrid as the research object, combining the characteristics of campus energy use and the development trend of multi-energy complementary microgrid, a typical architecture of microgrid system suitable for campus is proposed. This paper discusses the significance and future development prospect of microgrid to ensure the safety of campus energy consumption.

Developing a Practical Framework of Sustainability Indicators Relevant to All Higher Education Institutions to Enable Meaningful International Rankings

Higher Education Institutions (HEIs) sustainability assessments are receiving significant attention in the academic literature, with ever more complex grading and ranking systems being developed. This paper aims to provide national policy makers with a simple set of indicators to facilitate measuring progress towards sustainability for the HEI sector, within the context of national sustainability data collection efforts. Candidate indicators were identified and assessed from the two most subscribed to HEI sustainability assessments, namely, the UIGreenMetric and STARS, to develop a sector specific indicator set. This resulted in a final set of 12 indicators, covering on-site energy, greenhouse gas emissions, solid waste, water, travel, education, research, and governance. The proposed indicator set was then compared to publicly available data for Irish HEIs, to identify gaps in data collection, which found that direct campus energy use and associated Scope 1 and 2 emission data alone were collected with sufficient rigour. The described indicator set has the potential to be applied to guiding national sustainability transitions globally and offers a template for accelerating sustainability data collection efforts for the HEI sector.

AI-Based Campus Energy Use Prediction for Assessing the Effects of Climate Change

In developed countries, buildings are involved in almost 50% of total energy use and 30% of global annual greenhouse gas emissions. The operational energy needs of buildings are highly dependent on various building physical, operational, and functional characteristics, as well as meteorological and temporal properties. Besides physics-based energy modeling of buildings, Artificial Intelligence (AI) has the capability to provide faster and higher accuracy estimates, given buildings’ historic energy consumption data. Looking beyond individual building levels, forecasting building energy performance can help city and community managers have a better understanding of their future energy needs, and to plan for satisfying them more efficiently. Focusing at an urban scale, this research develops a campus energy use prediction tool for predicting the effects of long-term climate change on the energy performance of buildings using AI techniques. The tool comprises four steps: Data Collection, AI Development, Model Validation, and Model Implementation, and can predict the energy use of campus buildings with 90% accuracy. We have relied on energy use data of buildings situated in the University of Florida, Gainesville, Florida (FL). To study the impact of climate change, we have used climate properties of three future weather files of Gainesville, FL, developed by the North American Regional Climate Change Assessment Program (NARCCAP), represented based on their impact: median (year 2063), hottest (2057), and coldest (2041).

Energy efficiency optimization strategies for university research buildings with hot summer and cold winter climate of China based on the adaptive thermal comfort

Hot summer and cold winter zone is a typical climate region in China with high temperatures and stuffiness in summer and low temperature and moisture in winter. The existing buildings bear of both poor thermal performance of building envelope and poor indoor thermal environment. With the development of social economy, increasing demand towards building indoor thermal environment is much more urgent than before, and hence energy consumption has rapidly risen. Energy efficiency retrofit with low cost has become a priority in this region.Universities and colleges are one of the typical energy consumers in this region, which are insufficient in research. Over all the campus buildings, research building occupies a large part in total campus energy use, and hence becomes the main retrofit objects. Research buildings have complicated functions of offices, scientific research and laboratories, and space heating and cooling behaviors have their own characteristics, which have the large effect on space heating and cooling use. However, there is little knowledge about adaptive thermal comfort and corresponding heating and conditioning energy-use behaviors.In view of this, in this paper, a typical research building located in Hangzhou was chosen and the measurements on indoor thermal environment heating and cooling behaviors, fenestration and energy consumption were carried out during July 2016 to October 2017. By the analysis on field investigation, delivered questionnaires and measured data, the typical space heating and cooling behaviors, fenestration and thermal environment are analyzed. On this base, energy efficiency optimization strategies in terms of building envelope thermal performance, sun shading, and adaptive space heating and cooling behavior are explored by the simulation. The study provides the technic support for energy saving retrofitting of campus buildings in this region.

Energy planning of university campus building complex: Energy usage and coincidental analysis of individual buildings with a case study

As the demonstration of eco-communities, energy planning becomes more and more important for university campus. However, insufficient energy use data accumulation has been a significant barrier against fully understanding of energy use characteristics, and demand load features of campus buildings, which usually provide the basic support for energy planning from the demand side. A methodology to reveal the features of demand load and energy use of campus building was developed for this purpose. As a case study, both the long-term and real-time data of the electricity, heating, and water usage of a Norwegian university campus were analyzed by the descriptive statistics. On this base, coincidence characteristics of energy and water usage of the entire campus were analyzed, and individual coincidental rates to the campus were also quantified accordingly. The coincidence factors were calculated to be at high levels, which implied that the campus buildings’ usage of energy was quite similar to that of water. Finally, the individual coincidental contribution to total campus energy use was analyzed by the cluster analysis, to identify those buildings with the large potential of operation optimization. The results from this study could be used for the energy planning of cities and other urban energy systems.

Energy Consumption in Creighton University Residence Halls: Comparing Attitudes and Behaviors

<div class="page" title="Page 1"><div class="section"><div class="layoutArea"><div class="column"><p><span>“On U.S. college campuses, growing concerns since the 1960s have demanded that we become more knowledgeable about our impact on the environment.” (Ruckelshaus 455) </span>This research has aimed to understand attitudes and behaviors regarding energy consumption in Creighton University Residence halls by employing quantitative data gathering methods and analysis of campus energy use. The program Stata will be utilized in analysis to allow for a statistical understanding of student attitudes and behaviors regarding their energy consumption. The findings of this research are meant to allow Creighton University officials to understand student energy consumption habits and interest allowing for better energy consumption practices in the future. </p></div></div></div></div>

Development of a Comprehensive Energy Evaluation Program For a Medical Center in the Northeast: A Case Study

ABSTRACTThis article describes the development, results, and practical applications of energy use profiles and trends for a million-sq.-ft. medical center (MC) campus located in western New York.End-use categories and functional areas with the greatest contribution to MC campus energy use are identified. This process supports a conceptual framework for developing energy efficiency measures (EEMs) and provides data for comprehensive energy measurement, verification, and benchmarking.Energy benchmarking results for campus-wide and individual buildings are presented. The significance of detailed energy benchmarking for the individual buildings comprising the MC campus in evaluating campus energy performance as a whole is emphasized. Detailed MC campus energy use trends are presented on various time scales.This comprehensive approach to energy evaluation can be used for streamlining energy performance evaluations and operations/maintenance focus in the healthcare industry.