Personal thermal comfort
(status: completed, people involved: A. Rabbani, S. Keshav)
Unlike most current work in the area of demand response, which does not consider the in-home aspects of demand response, our work focuses on the key problem of control of energy use. Moreover, we would like this control to be customized to user preferences. The two key ideas in our approach are:
- Quantitative modeling of human comfort as a function of observable variables. Instead of using surveys or other qualitative approaches to measuring human comfort, we would like to model human comfort using a metric that we call the predicted personal vote (PPV). This is the expected vote of a human being subject to the measured environmental conditions, and it mirrors the notion of perceptual Quality of Service, such as for Voice over IP services, in the Internet. In the same way as perceptual QoS allows a network protocol’s service quality to be determined from quantitative metrics, we believe that our approach will allow the mathematical optimization of user comfort. We believe that the general approach can be extended to other areas, such as lighting comfort.
- Human-in-the-loop control. The control system gives suggestions to humans (using a screen or a text message) to encourage them adopt a green life style. Thus human users play an active role in the control loop as their actions will eventually save energy. We believe that this integration be necessary to overcome barriers to adoption, specifically the fear that system optimizations would lead to an uncontrollable loss of comfort.
- Details on the implementation of this project can be found here.
A. Rabbani and S. Keshav, “The SPOT* Personal Thermal Comfort System,” to appear, Proc. ACM BuildSys’16, November 2016.
(status: completed, people involved: A. Pat, S. Keshav)
The goal of our work is to study the role of non-cash incentives in motivating behavioural change. We are motivated by the fact that the rapid adoption of smartphones has made it possible for home users to gain unprecedented access to their home energy usage. Moreover, it is already possible for a smartphone to display home and building energy usage status and trends, and to turn appliances and other equipment on and off.
In this project, we wish to take this work several steps further. Specifically, we want to study what incentivizes a home or building owner to make this behavioural change? Our hypothesis is that the use of social media and smartphones makes it possible to dramatically improve the role of non-cash incentives. Specifically, we would like to use game theory to study the use of peer pressure and competition to drive down energy usage, similar to the use of peer pressure to enforce good behaviour in peer-to-peer networks. We will build social network applications on smartphones that not only give a home or building owner hints on how to reduce energy usage but also incentivize this behaviour.The key focus of our work will be to design a flexible architecture to allow us to experiment with a variety of schemes for non-cash incentives, implementing the appropriate communication and control protocols as necessary.
A Hybrid Control System for Personal Thermal Comfort in Building
(status: ongoing, people involved: R. Kalaimani, S. Keshav, C. Rosenberg)
Energy consumption in buildings constitutes 40% of the energy use in the US and is responsible for 40% of greenhouse gas emission. The global energy crisis calls for an advanced control strategy to reduce the energy consumption in buildings. Heating Ventilation and Air Conditioning (HVAC) systems maintain appropriate indoor air quality and ensures global thermal comfort in a building. However, a basic HVAC system is neither energy efficient nor designed to provide thermal comfort on an individual basis. Smart Personalized Office Thermal (SPOT) control system, one of the past projects of ISS4e, is capable of providing personal thermal comfort at the individual level but it cannot maintain the indoor air quality and has to work within the HVAC-controlled environment . We are in the process of designing a hybrid control system that integrates HVAC and SPOT systems together. The HVAC system will provide a base thermal comfort level. From this base level, an additional offset thermal level will be provided by SPOT only if the room is occupied. Each offset will be determined by the requirement of the person using SPOT. Hence, such a set up can address the diverse comfort requirements of occupants in a building . Additionally, there will also be energy savings as the HVAC is operated only to provide a base thermal level which will be energy-efficient during partial occupancy in the building.
(status: ongoing, people involved: A. Rosmanis, S. Keshav, C. Rosenberg)
The cost of solid-state lighting has been reduced significantly over the past few years, while its efficiency keeps increasing. Compared to conventional lighting technologies, light emitting diodes also allow wider and faster control over dimming levels and colour properties of the light. Combine this with the advent of ubiquitous, cheap, and self-powered wireless sensing, and the number of applications for lighting increases dramatically. We are studying how to integrate these various technologies in order to provide more personalized and higher quality lighting comfort for occupants of indoor spaces, at the same time reducing costs of such systems.
- Cloud-oriented architecture for smart home data management
Smart grid initiatives look to generate massive amounts of data concerning consumers’ energy consumption, which although useful is privacy sensitive in nature. This project aims to develop a system to allow third party application development targeted towards this data while retaining its privacy, ownership and control.
- Energy-optimal routing for smart home sensor networks
In the future, we expect that day to day objects will be enhanced with computation and communication to make them into smart objects. For example, a sensor on a door could inform nearby objects that the door has been opened to allow them to turn on lights in the house, turn up the heat, and so forth. Thus, this would automate the operation of a home. A similar approach could be used in a larger scale to control the operation of the electrical grid.Many smart object networks however, use unreliable communication media such as low-power wireless communication and power line communication, where the communication takes place over the wires in the electrical grid. They also operate in a highly constrained environment in terms of physical size, available memory, CPU power and battery life. The unreliable link characteristics and scarce resources have motivated the design of routing protocols for smart object networks such as the RPL (Routing Protocol for Low-power and Lossy Networks) protocol. RPL is the IETF (lnternet Engineering Task Force) standard IPv6 routing protocol for smart object networks . The objective of RPL is to nd routes in smart object networks, which may comprise up to thousands of nodes connected with low-power and lossy links. It is a distance vector protocol that builds paths from each node to the root of a directed acyclic graph, where smart objects are the nodes and the root acts as an information aggregator.Although RPL was deemed ready in 2011, it has several undefined specifications which greatly impact its performance. In this work, we have come up with energy-aware routing metrics as well as transmission power control algorithms that decrease the energy cost of RPL.
- Home peak load prediction
Proposed smart grid solutions to reducing peak electricity demand include storage and demand response which require a dynamic prediction of electricity demand. This project involves design of prediction models to predict peak electricity demand of a home on a relatively short timescale such as an hour.
- Smart appliances: In our previous study we have observed significant gains due to elasticity of appliances. In this project, we are extending upon the notion of appliance elasticity by proposing a scheme for appliances to respond to signals received from the power grid and a scheme for the utility to compute the signals to send to appliances so that the carbon footprint of the power grid, caused by commissioning plants with high carbon emissions, will be reduced.
- Temperature setpoint market: The electrical grid is designed to meet peak loads, which may occur for only a few hours each year. Consequently, there are signiﬁcant economic gains from a reduction in the peak load. Air conditioner (AC) load from residential buildings forms a signiﬁcant portion of peak summer loads. The existing ‘peaksaver’ program in Ontario attempts to reduce AC loads by setting thermostats a few degrees higher in volunteer households on hot summer days. This has had only a limited success. To address this issue, we propose a scheme that provides monetary incentive for participation. We describe the operation of this ‘temperature market’ and demonstrate its effectiveness with a heterogeneous population of potential participants. Here is a slide and a paper on the project.
- Real time data monitoring and anomaly of solar panels
We are working with Prof. Paul Parker in the Faculty of Environment to monitor, in real time, individual solar panels on the roof of the Environment 3 (EV3) building at the University of Waterloo. Click here to see solar generation data updated every minute from these sensors. This project also comprised design and implementation of hardware and software for detecting the anomalies on solar panels, such as shadows, snow, hail, dust and clouds. A sensor network to measure solar panel outputs was built, using the Zigbee protocol. We deployed the system on roof-top solar panels and developed machine learning techniques for automated analysis and detection of anomalies in current and voltage outputs. The solar panel data observed on the roof-based panels is here.
- The effectiveness of pricing on residential electrical storage for the smart grid
Storage batteries that can store energy during times of low load and be discharged during times of peak load, is one proposed solution to reduce peak load. This project evaluates the effect of storage on the electrical grid under different consumer electricity pricing schemes.
- Elasticity of Domestic Appliances
Power demand from the residential sector represents a significant fraction of overall demand. Most schemes attempting to curb residential demand rely upon human reactions to pricing signals. We have discovered an inherent property called elasticity present in most appliances that will allow elastic components in appliances to instantaneously reduce their power consumption without any impact on their lifetime. When these components reduce their power consumption, the time required to complete their operation will increase in proportion. The more the time is extended, the more is the degree of possible reduction of comfort for consumers. We had conducted a preliminary assessment of the peak demand reduction potential for regions with different demographics with various degrees of comfort reduction. This study had indicated significant gains in peak demand reduction even for a minor degree of comfort reduction.
- Building monitoring
Development of a testbed to monitor temperature, sound, and motion at the time scale of seconds in order to improve heating and cooling efficiency in commercial buildings. We have deployed a testbed of 24 wired sensors in our building and are gathering data in sound and light levels, temperature, and wind velocity. We are using Partially-observable Markov decision processes to optimally control heating vents to turn off heating and cooling when users are inactive, and to turn it back on when we can predict impending activity based on past patterns of activity.
- Smartphone based energy consumption feedback
This project investigated the effect of native smartphone applications on consumers’ energy aware behavior, in light of the now defunct, browser-based commercial services like Google Powermeter and Microsoft Hohm.
- Interactive home monitoring and control
Our vision of the future home is of an autonomous power generation system that is capable of modulating its consumption in response to system signals as well as augmenting its energy consumption with renewable resources. This includes the real-time monitoring and control of renewable power generation, power storage, and measurement devices. Designed and implemented a fully interactive energy monitoring and control system for a home, comprising off-the-shelf hardware, existing home appliances, Android smartphone applications, intelligent e-mail bots, and a home energy gateway implemented using Microsoft Home OS. Watch this demo for an abnormal consumption e-mail alert application.