Cascading Probability Distributions in Agent-Based Models: An Application to Behavioural Energy Wastage

This paper presents a methodology to cascade probabilistic models and agent-based models for fine-grained data simulation, which improves the accuracy of the results and flexibility to study the effect of detailed parameters. The methodology is applied on residential energy consumption behaviour, where an agent-based model takes advantage of probability distributions used in probabilistic models to generate energy consumption of a house with a focus on energy waste. The implemented model is based on large samples of real data and provides flexibility to study the effect of social parameters on the energy consumption of families. The results of the model highlighted the advantage of the cascading methodology and resulted in two domain-specific conclusions: (1) as the number of occupants increases, the family becomes more efficient, and (2) young, unemployed, and part-time occupants cause less energy waste in small families than full-time and older occupants. General insights on how to target families with energy interventions are included at last

Power-use profile analysis of non-domestic consumers for electricity tariff switching

For both domestic and non-domestic consumers, dynamic electricity tariffs have been proposed as a way to reduce their energy costs and to facilitate demand-side response. It is difficult for businesses which are tenants to adopt energy efficiency measures; thus, tariff switching is the easier option. Therefore, understanding the limits of the cost saving offered by tariff switching is an important step. This raises two questions: by how much could bills be reduced, and would all consumers benefit equally? Using a dataset of half-hourly electricity readings from more than 7500 British businesses, we performed an empirical analysis to discover which types of businesses might have lower or higher costs when changing between static and real-time tariffs. We identified differences in demand profiles that demonstrate that the decision whether to switch tariff types is a subtle one which may have a significant cost impact. The dataset was aggregated into five categories: Entertainment, Industry, Retail, Social, and Other. Our analytical methods can be used to distinguish the differences between typical electricity demand profiles for small- to medium-sized businesses and sectors in different market options. Our analyses of switching to a real-time tariff suggest that most of those small- to medium-sized businesses that would reduce their annual electricity bill would gain by no more than 10 %. Most of these businesses would gain by less than 5 %. This, we suggest, sets a realistic upper limit of the likely cash savings before energy efficiency, or other measures must be taken to further reduce bills.This work was supported by an UK Engineering and Physical Science Research Council grant (EP/I000194/1)

Consumer Behavior in Building Energy Use

Economic theory of customer preference describes consumer behavior as a \u201cset of activities prospective customers undertake in searching, selecting, valuing, assessing, supplying and using of products and services in order to satisfy their needs and desires\u201d (\u10cavo\u161ki and Markov\uedc 2015). When it comes to research in the field of energy consumption and energy efficiency, there is a lack of common understanding of what consumer behavior is, since it is strongly related to the technical, economic, sociological, and psychological models applied to understand how and why people perform energy-related actions, and to the disciplines which investigate these actions. Hence, consumer behavior might be referred, among others, as occupant behavior and energy behavior. Occupant behavior has been referred as a set of \u201cobservable actions or reactions of a person in response to external or internal stimuli, or respectively actions or reactions of a person to adapt to ambient environmental conditions such as temperature, indoor air quality or sunlight\u201d (International Energy Agency EBCP 2013). However, this definition does not take into account individual attitudes and reasons which lead to a specific action, which instead have been intensively studied in social sciences. Energy behavior has been defined as \u201call human actions that affect the way that fuels (electricity, gas, petroleum, coal, etc.) are used to achieve desired services, including the acquisition or disposal of energy-related technologies and materials, the ways in which these are used, and the mental processes that relate to these actions\u201d (International Energy Agency DSM Energy Efficiency 2014). Energy behavior is the one leading to end-use energy consumption, incorporating two implicit dimensions: the behavior itself and the associated energy consumption (Lopes et al. 2012). Rather than agreeing on unique terms and definitions, this chapter aims at providing an overview of the scope, policy implications, and characteristics of the consumer behavior in building energy use, focusing in particular on the household behavior in the residential sector. To the purpose of this work, all the terms above are assumed to embed energy consumption as subject of investigation; therefore, consumer behavior, user behavior, and occupant behavior are used indifferently

Should we design buildings that are less sensitive to occupant behaviour? A simulation study of effects of behaviour and design on office energy consumption

In an ideal world, occupants have an understanding of how building systems work and are motivated to use the systems as they were designed to be. There is considerable evidence, however, that occupants do not understand the principles of how buildings function and that they use the systems non-optimally. The purpose of the paper is to quantify the effect of occupant behaviour on energy consumption and show how it is affected by design strategies. Numerical simulations of an office were performed with the dynamic thermal simulation software TRNSYS. Three types of behaviour ('careless', 'normal', and 'conscious') and two types of design ('ordinary' and 'robust') were considered. The results show that the effect of occupant behaviour on energy consumption is greatly diminished with robust design solutions, solutions that make buildings less sensitive to occupant behaviour. The careless user consumes 75-79 % less energy if the robust design solutions are applied rather than the ordinary design solutions. It is argued that a realistic view of occupant behaviour is advantageous in the creation of energy-efficient buildings (that is, leaving less need to learn how buildings work, to be motivated to save energy, or to perform specific energy-saving actions). However, the possibility of personal control should not be eliminated

BIM-Enabled Structural Design: Impacts and Future Developments in Structural Modelling, Analysis and Optimisation Processes

This review focuses on identifying the impacts and future development trends for current structural design practice in integration of building information modelling (BIM) technologies. BIM technologies, as novel information management schemes they are, are changing the conventional structure design processes. Currently, utilising BIM technologies for reshaping structural design has been widely acknowledged and embraced by both academic and industry circles. In this research, the current status and issues of the structural design processes (including modelling, analysis, and optimisation of structures) are fully investigated with emphases on specific design stages. The research put efforts on surveying the benefits of BIM in facilitating current structural design, such as systematic modelling processes, powerful interactive visualization platform, and standardised exchanging data interfaces. Impacts of personnel involvement in structural design when adopting BIM have also been identified in detail. Finally, a predicted cross-functional flowchart of BIM-enabled structural design for the near future is proposed, which shows future developing trends in improving structural design quality and addressing current issues