scholarly journals The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Martin Pullinger ◽  
Jonathan Kilgour ◽  
Nigel Goddard ◽  
Niklas Berliner ◽  
Lynda Webb ◽  
...  

AbstractThe IDEAL household energy dataset described here comprises electricity, gas and contextual data from 255 UK homes over a 23-month period ending in June 2018, with a mean participation duration of 286 days. Sensors gathered 1-second electricity data, pulse-level gas data, 12-second temperature, humidity and light data for each room, and 12-second temperature data from boiler pipes for central heating and hot water. 39 homes also included plug-level monitoring of selected electrical appliances, real-power measurement of mains electricity and key sub-circuits, and more detailed temperature monitoring of gas- and heat-using equipment, including radiators and taps. Survey data included occupant demographics, values, attitudes and self-reported energy awareness, household income, energy tariffs, and building, room and appliance characteristics. Linked secondary data comprises weather and level of urbanisation. The data is provided in comma-separated format with a custom-built API to facilitate usage, and has been cleaned and documented. The data has a wide range of applications, including investigating energy demand patterns and drivers, modelling building performance, and undertaking Non-Intrusive Load Monitoring research.

2019 ◽  
Author(s):  
Marcel Roux ◽  
MJ Booysen

Water heating is a leading cause of household energy consumption and, given its capacitive nature, has been the focus of research on demand side management and grid peak load management. Despite all the existing literature on energy for water heating, very little is known about an inextricably linked key determinant of it - demand for hot water and consumption patterns thereof. Moreover, even though water heating energy demand profiles have been investigated in the past, little is known about the different energy profiles for the days of the week, and regional variance of such profiles. This paper measures and reports actual hot water demand acquired through a novel smart metering solution. The different profiles for the days of the week are evaluated, in addition to weekdays and weekend days. Finally, differences between units in peri-rural Mkhondo and the urban Western Cape are compared in terms of water demand, energy demand, and efficiency (energy in vs. energy out). The results show a striking similarity to previous work, with the exception that scheduling has led to energy demand leading water consumption. The results also show that daily routines vary significantly, and also between regions. Surprisingly, the efficiencies and consumption patterns between the regions are also stark, with the urban Western Cape using 20 % more water on an average day, and with 70.2 % efficiency vs. 45.8 % in Mkhondo.


Proceedings ◽  
2020 ◽  
Vol 65 (1) ◽  
pp. 25
Author(s):  
Antonio Garrido Marijuan ◽  
Roberto Garay ◽  
Mikel Lumbreras ◽  
Víctor Sánchez ◽  
Olga Macias ◽  
...  

District heating networks deliver around 13% of the heating energy in the EU, being considered as a key element of the progressive decarbonization of Europe. The H2020 REnewable Low TEmperature District project (RELaTED) seeks to contribute to the energy decarbonization of these infrastructures through the development and demonstration of the following concepts: reduction in network temperature down to 50 °C, integration of renewable energies and waste heat sources with a novel substation concept, and improvement on building-integrated solar thermal systems. The coupling of renewable thermal sources with ultra-low temperature district heating (DH) allows for a bidirectional energy flow, using the DH as both thermal storage in periods of production surplus and a back-up heating source during consumption peaks. The ultra-low temperature enables the integration of a wide range of energy sources such as waste heat from industry. Furthermore, RELaTED also develops concepts concerning district heating-connected reversible heat pump systems that allow to reach adequate thermal levels for domestic hot water as well as the use of the network for district cooling with high performance. These developments will be demonstrated in four locations: Estonia, Serbia, Denmark, and Spain.


Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2144
Author(s):  
Stefan Reitmann ◽  
Lorenzo Neumann ◽  
Bernhard Jung

Common Machine-Learning (ML) approaches for scene classification require a large amount of training data. However, for classification of depth sensor data, in contrast to image data, relatively few databases are publicly available and manual generation of semantically labeled 3D point clouds is an even more time-consuming task. To simplify the training data generation process for a wide range of domains, we have developed the BLAINDER add-on package for the open-source 3D modeling software Blender, which enables a largely automated generation of semantically annotated point-cloud data in virtual 3D environments. In this paper, we focus on classical depth-sensing techniques Light Detection and Ranging (LiDAR) and Sound Navigation and Ranging (Sonar). Within the BLAINDER add-on, different depth sensors can be loaded from presets, customized sensors can be implemented and different environmental conditions (e.g., influence of rain, dust) can be simulated. The semantically labeled data can be exported to various 2D and 3D formats and are thus optimized for different ML applications and visualizations. In addition, semantically labeled images can be exported using the rendering functionalities of Blender.


1987 ◽  
Vol 109 (2) ◽  
pp. 150-155 ◽  
Author(s):  
M. P. Malkin ◽  
S. A. Klein ◽  
J. A. Duffie ◽  
A. B. Copsey

A modification to the f-Chart method has been developed to predict monthly and annual performance of thermosyphon solar domestic hot water systems. Stratification in the storage tank is accounted for through use of a modified collector loss coefficient. The varying flow rate throughout the day and year in a thermosyphon system is accounted for through use of a fixed monthly “equivalent average” flow rate. The “equivalent average” flow rate is that which balances the thermosyphon buoyancy driving force with the frictional losses in the flow circuit on a monthly average basis. Comparison between the annual solar fraction predited by the modified design method and TRNSYS simulations for a wide range of thermosyphon systems shows an RMS error of 2.6 percent.


2020 ◽  
Vol 122 (10) ◽  
pp. 1-50
Author(s):  
Susan Bush-Mecenas ◽  
Julie A. Marsh ◽  
Katharine O. Strunk

Background/Context School leaders are central to state and district human-capital reforms (HCRs), yet they are rarely equipped with the skills to implement new evaluation, professional development, and personnel data systems. Although districts increasingly offer principals coaching and training, there has been limited empirical work on how these supports influence principals’ HCR-related practices. Purpose Drawing on a two-year, mixed-methods study in the Los Angeles Unified School District (LAUSD), this article examines the role of principal supervisors in HCRs. We ask: What role did principal supervisors (Instructional Directors [IDs]) play in the implementation of human-capital reforms? What did high-quality coaching on the part of IDs look like in this context? Research Design Our two-part analysis draws upon survey and interview data. First, we conducted descriptive analyses and significance testing using principal and ID survey data to examine the correlations among principals’ ratings of ID coaching quality, ID coaching practices, and principals’ implementation of HCRs. Second, we conducted in-depth interviews, using a think-aloud protocol, with two sets of IDs—those consistently highly-rated and those with mixed ratings—who were identified using principals’ reports of coaching quality. Following interview coding, we created various case-ordered metamatrix displays to analyze our qualitative data in order to identify patterns in coaching strategy and approach across IDs, content, and contexts. Findings First, our survey data indicate that receiving high-quality coaching from IDs is correlated with stronger principal support for and implementation of HCRs. Our survey findings further illustrate that IDs support a wide range of principals’ HCR activities. Second, our think-aloud interviews with case IDs demonstrate that coaching strategy and approach vary between consistently highly-rated and mixed-rated coaches: Consistently highly-rated IDs emphasize the importance of engaging in, or defining HCR problems as, joint work alongside principals, while mixed-rated IDs often emphasize the use of tools to guide principal improvement. We find that, on the whole, the consistently highly-rated IDs in our sample employ a nondirective approach to coaching more often than mixed-rated coaches. Conclusions These findings contribute to a growing literature on the crucial role of principal supervisors as coaches to improve principals’ instructional leadership and policy implementation. While exploratory, this study offers the first steps toward building greater evidence of the connections between high-quality coaching and policy implementation, and it may have implications for the design and implementation of professional development for principal supervisors and the selection and placement of supervisors with principals.


Weed Science ◽  
2021 ◽  
pp. 1-19
Author(s):  
Bhagirath S. Chauhan ◽  
Shane Campbell ◽  
Victor J. Galea

Abstract Sweet acacia [Vachellia farnesiana (L.) Willd.]is a problematic thorny weed species in several parts of Australia. Knowledge of its seed biology could help to formulate weed management decisions for this and other similar species. Experiments were conducted to determine the effect of hot water (scarification), alternating temperatures, light, salt stress, and water stress on seed germination of two populations of V. farnesiana and to evaluate the response of its young seedlings (the most sensitive development stage) to commonly available POST herbicides in Australia. Both populations behaved similarly to all the environmental factors and herbicides; therefore, data were pooled over the populations. Seeds immersed in hot water at 90 C for 10 min provided the highest germination (88%), demonstrating physical dormancy in this species. Seeds germinated at a wide range of alternating day/night temperatures from 20/10 C (35%) to 35/25 C (90%) but no seeds germinated at 15/5 C. Germination was not affected by light, suggesting that seeds are nonphotoblastic and can germinate under a plant canopy or when buried in soil. Germination was not affected by sodium chloride concentrations up to 20 mM and about 50% of seeds could germinate at 160 mM sodium chloride, suggesting its high salt tolerance ability. Germination was only 13% at −0.2 MPa osmotic potential and no seeds germinated at −0.4 MPa, suggesting that V. farnesiana seeds may remain ungerminated until moisture conditions have become conducive for germination. A number of POST herbicides, including 2,4-D + picloram, glufosinate, paraquat and saflufenacil, provided >85% control of biomass of young seedlings compared with the nontreated control treatment. Knowledge gained from this study will help to predict the potential spread of V. farnesiana in other areas and help to integrate herbicide use with other management strategies.


2018 ◽  
Vol 7 (4) ◽  
pp. 357-376 ◽  
Author(s):  
Giri Aryal ◽  
John Mann ◽  
Scott Loveridge ◽  
Satish Joshi

Purpose The innovation creation literature primarily focuses on urban firms/regions or relies heavily on these data; less studied are rural firms and areas in this regard. The purpose of this paper is to employ a new firm-level data set, national in scale, and analyze characteristics that potentially influence innovation creation across rural and urban firms. Design/methodology/approach The authors use the 2014 National Survey of Business Competitiveness (NSBC) covering multiple firm-level variables related to innovation creation combined with secondary data reflecting the regional business and innovative environments where these firms operate. The number of patent applications filed by these firms measures their innovation creation, and the paper employs a negative binomial regression estimation for analysis. Findings After controlling for industry, county and state factors, rural and urban firms differ in their innovation creation characteristics and behaviors, suggesting that urban firms capitalize on their resources better than rural firms. Other major findings of the paper provide evidence that: first, for rural firms, the influence of university R&D is relevant to innovation creation, but their perception of university-provided information is not significant; and second, rural firms that are willing to try, but fail, in terms of innovation creation have a slight advantage over other rural firms less willing to take on the risk. Originality/value This paper is one of the first to analyze the 2014 NSBC, a firm-level national survey covering a wide range of innovation-related variables. The authors combine it with other regional secondary data, and use appropriate analytical modeling to provide empirical evidence of influencing factors on innovation creation across rural and urban firms.


1990 ◽  
Vol 12 (4) ◽  
pp. 279-288 ◽  
Author(s):  
Kamal Rijal ◽  
N.K. Bansal ◽  
P.D. Grover

Author(s):  
A. J. Perrotta ◽  
J. V. Smith

SummaryA full-matrix, three-dimensional refinement of kalsilite, KAlSi04 (hexagonal, a 5·16, c 8.69 Å, P6a), shows that the silicon and aluminium atoms are ordered. The respective tetrahedral distances of 1·61 and 1·74 Å agree with values of 1·61 and 1·75 Å taken to be typical of framework structures. As in nepheline, an oxygen atom is statistically distributed over three sites displaced 0·25 Å from the ideal position on a triad axis. This decreases the bond angle from 180° to 163° in conformity with observations on some other crystal structures. The potassiumoxygen distances of 2·77, 2·93, and 2·99 Å are consistent with the wide range normally found for this weakly bonded atom.


Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1928 ◽  
Author(s):  
Alfonso González-Briones ◽  
Fernando De La Prieta ◽  
Mohd Mohamad ◽  
Sigeru Omatu ◽  
Juan Corchado

This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and their application to energy optimization problems. This methodology and related tools have contributed to changes in various paradigms used in energy optimization. Behavior and interactions between agents are key elements that must be understood in order to model energy optimization solutions that are robust, scalable and context-aware. The concept of MAS is introduced in this paper and it is compared with traditional approaches in the development of energy optimization solutions. The different types of agent-based architectures are described, the role played by the environment is analysed and we look at how MAS recognizes the characteristics of the environment to adapt to it. Moreover, it is discussed how MAS can be used as tools that simulate the results of different actions aimed at reducing energy consumption. Then, we look at MAS as a tool that makes it easy to model and simulate certain behaviors. This modeling and simulation is easily extrapolated to the energy field, and can even evolve further within this field by using the Internet of Things (IoT) paradigm. Therefore, we can argue that MAS is a widespread approach in the field of energy optimization and that it is commonly used due to its capacity for the communication, coordination, cooperation of agents and the robustness that this methodology gives in assigning different tasks to agents. Finally, this article considers how MASs can be used for various purposes, from capturing sensor data to decision-making. We propose some research perspectives on the development of electrical optimization solutions through their development using MASs. In conclusion, we argue that researchers in the field of energy optimization should use multi-agent systems at those junctures where it is necessary to model energy efficiency solutions that involve a wide range of factors, as well as context independence that they can achieve through the addition of new agents or agent organizations, enabling the development of energy-efficient solutions for smart cities and intelligent buildings.


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