Eco-Forecasting for Domestic Electricity Use

Over the past decade we have seen an increased awareness about domestic energy consumption and a growing focus on eco-feedback displays. In this paper we explore the concept of providing forecasts in such displays as a supplement to information about past usage. Our prototype, eForecast, extends the display of past electricity usage with forecasts about expected usage, electricity price, availability of wind power, and expected demand drops and peaks. Building on previous eco-feedback display research, our approach specifically enables people to use electricity at more opportune times – when it is cheap, green, or when there is an abundance of capacity. We evaluated eForecast in real world use in three domestic households for 22 weeks, where we explored potentials and limitations of forecasting for shifting electricity consumption. In this way, families were able to act in a more sustainable way – without necessarily reducing the amount of electricity consumed. Author Keywords Sustainability; forecasting; energy consumption; domesti

Using smart meters for household water consumption feedback: Knowns and unknowns

Published16th Conference on Water Distribution System Analysis, WDSA 2014A range of adaptive strategies are needed to mitigate the growing threats to water security. Demand management will play a central role in adaptation. The proliferation of smart metering provides a means for utilities to better quantify end user demand, and to provide consumption feedback to consumers in (near) real-time. Such feedback can help close the gap between perceived and actual water consumption. However, relatively few studies have considered the effectiveness of feedback in promoting water saving behavior. This paper evaluates the evidence for the effectiveness of water consumption feedback technology in promoting water saving behavior.The research leading to this report has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under the iWIDGET project, grant agreement no. 318272

Effectiveness of smart-meter based consumption feedback in curbing household water use: Knowns and unknowns

This is the author accepted manuscript. The final version is available from the American Society of Civil Engineers via the DOI in this record.Adaptive approaches are required to counteract the mounting threats to water security. Demand management will feature centrally in such adaptation. The increase in use of smart meter technology offers an improved way for utilities to gauge consumer demand and to supply consumers with consumption feedback in (near) real-time. Such feedback can decrease the discrepancies between perceived and actual water usage. In contrast to the energy sector, however, where the advantages associated with smart meter consumption feedback are extensively documented, few studies have focused on the usefulness of such feedback when it comes to managing water consumption. This review assesses the evidence base for the effectiveness of water usage feedback technology in encouraging water conservation. The review highlights the potential value of high-granular smart-meter feedback technology in managing domestic water consumption. Findings from the papers included in this review (N = 21) indicate that feedback was associated with decreases of between 2.5% and 28.6% in water use, with an average of 12.15% (SD = 8.75). A single paper reported a 16% increase in consumption associated with smart-meter feedback. The benefits for water utilities are highlighted, but the costs for utilities need to be considered further. Overall, more work is needed to conclusively pinpoint the most effective type of feedback in terms of information content and granularity, frequency of delivery and medium, and how water consumption is linked to energy consumption. This information is needed to make concrete recommendations to the water industry about the costs and benefits of investment in smart metering and consumer feedback.This research received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under the iWIDGET project, grant agreement no. 318272. An earlier version of this paper was published in the conference proceedings of the 2014 Water Distribution Systems Analysis Conference (Sonderlund et al., 2014, Procedia Engineering, 89, 990-997)

Contextualising water use in residential settings: a survey of non-intrusive techniques and approaches

Water monitoring in households is important to ensure the sustainability of fresh water reserves on our planet. It provides stakeholders with the statistics required to formulate optimal strategies in residential water management. However, this should not be prohibitive and appliance-level water monitoring cannot practically be achieved by deploying sensors on every faucet or water-consuming device of interest due to the higher hardware costs and complexity, not to mention the risk of accidental leakages that can derive from the extra plumbing needed. Machine learning and data mining techniques are promising techniques to analyse monitored data to obtain non-intrusive water usage disaggregation. This is because they can discern water usage from the aggregated data acquired from a single point of observation. This paper provides an overview of water usage disaggregation systems and related techniques adopted for water event classification. The state-of-the art of algorithms and testbeds used for fixture recognition are reviewed and a discussion on the prominent challenges and future research are also included

Context of Use and Timing of Social Comparison Techniques in Behavior Change Support: A qualitative systematic review

ABSTRACT This paper aims to examine the timing and contexts of use of social comparison techniques in supporting behavior change. Timing is evaluated through stages of the behavior change process in accordance with the Transtheoretical Model, while context of use is defined through the level of publicity at three levels: public, semi-public and private. A qualitative systematic review was conducted of prior research dealing with applications featuring social comparison techniques. Through a systematic search strategy, eleven IT artifacts were selected for analysis. Then, patterns of use were analyzed so as to identify experiences on proper timing and context of use. The analysis shows that the technology placed in public spaces is suitable mainly for the first stages in the behavior change process. A private context of use is preferred in later stages