In this dissertation we study the problem of allocating computational resources and managing applications in a data center to serve incoming requests in such a way that the energy usage, reliability and quality of service considerations are balanced. The problem is motivated by the growing energy consumption by data centers in the world and their overall inefficiency. This work is focused on designing flexible and robust strategies to manage the resources in such a way that the system is able to meet the service agreements even when the load conditions change. As a first step, we study the control of a Markovian queueing system with controllable number of servers and service rates (M=Mt=kt ) to minimize effort and holding costs. We present structural properties of the optimal policy and suggest an algorithm to find good performance policies even for large cases. Then we present a reactive/proactive approach, and a tailor-made wavelet-based forecasting procedure to determine the resource allocation in a single application setting; the method is tested by simulation with real web traces. The main feature of this method is its robustness and flexibility to meet QoS goals even when the traffic behavior changes. The system was tested by simulating a system with a time service factor QoS agreement. Finally, we consider the multi-application setting and develop a novel load consolidation strategy (of combining applications that are traditionally hosted on different servers) to reduce the server-load variability and the number of booting cycles in order to obtain a better capacity allocation.

The current state of Ontario???s electricity system and natural environment has prompted the provincial government to call for the province to adopt a ???culture of conservation.??? Answering this call will involve the promotion of a variety of solutions. Included in that will be the use of information and communication technology, which encompasses technologies such as home energy management system (HEMS). It is believed that the feedback and home automation features of the HEMS will enable its users to alter their electricity consumption behaviours, via net reductions and/or load shifting. This study has assessed the ability of HEMS to encourage reduction in total and on-peak electricity consumption while in a time-of-use pricing environment. Additional focus was on which consumers had the greatest success using the HEMS to adopt electricity conservation behaviours. Two hundred and sixteen participants of a Milton, Ontario HEMS pilot study were chosen to take part in this case study. These participants were divided into two equal groups: a sample group, those who received a HEMS, and a control group, those who did not receive a HEMS. Participants from both groups were asked to complete two surveys and allow their electricity consumption data to be analyzed. The initial survey was to establish some baseline information about the participants. The second survey was designed to determine if changes had occurred in the household since the initial baseline survey. Through the analysis of the survey and households electricity consumption data, conclusions were drawn on how participants used the HEMS. The study had a 2.9% relative reduction in total electricity consumption and a 13.2% relative reduction in on-peak electricity consumption. However, additional analysis of the results revealed promising findings with regard to the HEMS ability to catalyze conservation and demand management among recent time-of-use pricing adopters.

Sensor network web services have recently emerged as promising tools to provide remote management, data collection and querying capabilities for sensor networks. They can be utilized in a large number of elds among which Demand-Side Energy Management (DSEM) is an important application area that has become possible with the smart electrical power grid. DSEM applications generally aim to reduce the cost and the amount of power consumption. In the traditional power grid, DSEM has not been implemented widely due to the large number of households and lack of ne-grained automation tools. However by employing intelligent devices and implementing communication infrastructure among these devices, the smart grid will renovate the existing power grid and it will enable a wide variety of DSEM applications. In this thesis, we analyze various DSEM scenarios that become available with sensor network web services. We assume a smart home with a Wireless Sensor Network (WSN) where the sensors are mounted on the appliances and they are able to run web services. The web server retrieves data from the appliances via the web services running on the sensor nodes. These data can be stored in a database after processing, where the database can be accessed by the utility, as well as the inhabitants of the smart home. We showthat our implementation is e cient in terms of running time. Moreover, the message sizes and the implementation code is quite small which makes it suitable for the memory-limited sensor nodes. Furthermore, we show the application scenarios introduced in the thesis provide energy saving for the smart home.

Prepared in association with the Alfred P. Sloan School of Management

Prepared in association with the Alfred P. Sloan School of Management

Sensor network web services have recently emerged as promising tools to provide remote management, data collection and querying capabilities for sensor networks. They can be utilized in a large number of elds among which Demand-Side Energy Management (DSEM) is an important application area that has become possible with the smart electrical power grid. DSEM applications generally aim to reduce the cost and the amount of power consumption. In the traditional power grid, DSEM has not been implemented widely due to the large number of households and lack of ne-grained automation tools. However by employing intelligent devices and implementing communication infrastructure among these devices, the smart grid will renovate the existing power grid and it will enable a wide variety of DSEM applications. In this thesis, we analyze various DSEM scenarios that become available with sensor network web services. We assume a smart home with a Wireless Sensor Network (WSN) where the sensors are mounted on the appliances and they are able to run web services. The web server retrieves data from the appliances via the web services running on the sensor nodes. These data can be stored in a database after processing, where the database can be accessed by the utility, as well as the inhabitants of the smart home. We showthat our implementation is e cient in terms of running time. Moreover, the message sizes and the implementation code is quite small which makes it suitable for the memory-limited sensor nodes. Furthermore, we show the application scenarios introduced in the thesis provide energy saving for the smart home.

Smart grid is an emerging technology that aims to empower the current power grid with the integration of two-way communication and computer technology. This thesis deals with energy management in smart grid with focus on the smart home and the Intelligent Transportation System (ITS). The smart home contains a network that connects home elements like smart appliances, HVAC (heating, ventilation, and air conditioning), thermostat, smart meter, sensors, solar panels and energy storage. ITS integrates computer and communication technologies for advanced traffic management and communication among road infrastructure, vehicles and users. A web service describes a collection of operations that are accessible via the Internet. Web services can also provide security and interoperability. Due to the rising cost of energy, more and more residential consumers are interested in controlling temperature or appliances in order to reduce energy consumption. In this thesis, we propose an approach that uses Web services to remotely and efficiently interact with smart home devices in order to manage energy consumption, in a smart grid environment. Consequently, the user is able to adjust the temperature, control appliances or read energy consumption values quickly, remotely and securely. A smart home with a wireless network based on ZigBee and XMPP (eXtensible Messaging and Presence Protocol) is simulated. The advantage of XMPP is that it provides near real-time communication and security. There is a central computer that can communicate with all home elements. Business Process Execution Language (BPEL) is used to implement the Web service on a central computer. Furthermore, quality of service is offered. Therefore, different levels of security and an access control mechanism are provided. An algorithm is proposed that can sell stored energy back to the grid from smart home. Another algorithm is proposed that can facilitate demand response. Moreover, dynamic programming is used to minimize energy consumption. Also, a broadcasting algorithm is presented that can be used by an electric vehicle to find the most suitable charging station in ITS. Simulation and analytical study is undertaken to demonstrate the performance and advantage of the proposed approach and algorithms.

The Oil and Gas (O&G) Industry has been one of the most environmentally questioned sectors in the lastdecades, where the management of the resources and impact over natural life has been severelycriticized. There are many adverse effects of the activities around the O&G business, from which theconsumption of energy and the emissions of Greenhouse Gases (GHG) stand out to be one of the mostimportant aspects to mitigate. This project studies the actual EnMS in E&P and develops measures of improvement using establishedmanagement tools in the division, applying the principles of the ISO 50001 Standard, to include energysavings and GHG emissions mitigation in the lifecycle of Repsol’s E&P operated assets. The main focuslands over three core elements: the Integrated Project Management platform for new projects, the EnergyPlanning follow-up applications, and the implementation of relevant energy audit outlines.

Electric buses offer a range of benefits, including a drastic reduction of greenhouse gas emissions compared to personal transit, or to conventional diesel buses. Unfortunately, electric buses also require additional planning to ensure affordable and reliable operation. This thesis proposes two contributions that help to model and plan electric bus deployments, and generally examines how system-focused thinking is required for this application. First, a novel data driven method for estimating the energy consumption of a bus is presented and validated against 1 Hz driving data. Rather than requiring ad hoc data collection, or entire theoretical drivecycle patterns, this new method leverages existing low fidelity driving data from public transit feeds. This data driven method can be used to quickly and accurately model the driving patterns and energy consumption of a whole fleet of buses, as is demonstrated for a case study in Victoria, BC, Canada. Second, using the energy estimating methods previously mentioned, the electricity demand profile for a high-power electric bus charging hub is modelled for various locations and charging systems. Using this modelled demand profile, the potential for using a stationary energy storage system to reduce the peak power demand is investigated. The advantages of three different energy storage technologies (lithium ion, redox flow, and flywheel energy storage systems) are explored. Energy storage was found to be optimal for most charging scenarios modelled, with lithium ion providing the most economical solution for 65% of cases considered. Both the data drive energy estimation modelling, and the energy storage feasibility study constitute novel contributions to the literature. These contributions help to advance the knowledge surrounding electric bus planning and modelling, and help to underpin the systems level thinking required for electric bus deployments. / Graduate

With growing concerns on global energy demand and climate change, it is important to focus on efficient utilization of electricity in commercial buildings, which contribute significantly to the overall electricity consumption. Accordingly, there has been a number of Building Energy Management (BEM) software/hardware solutions to monitor energy consumption and other measurements of individual building loads. BEM software serves as a platform to implement smart control strategies and stores historical data. Although BEM software provides such lucrative benefits to building operators, in terms of energy savings and personalized control, these benefits are not harnessed by most small to mid-sized buildings due to a high cost of deployment and maintenance. A cloud-based BEM system can offer a low-cost solution to promote ease of use and support a maintenance-free installation. In a typical building, a conventional router has a public address and assigns private addresses to all devices connected to it. This led to a network topology, where the router is the only device in the Internet space with all other devices forming an isolated local area network behind the router. Due to this scenario, a cloud-based BEM software needs to pass through the router to access devices in a local area network. To address this issue, some devices, during operation, make an outbound connection to traverse through the router and provide an interface to itself on the Internet. Hence, based on their capability to traverse through the router, devices in a local area network can be distinguished as cloud and non-cloud devices. Cloud-based BEM software with sufficient authorization can access cloud devices. In order to access devices adhering to non-cloud protocols, cloud-based BEM software requires a device in the local area network which can perform traversal through the router on behalf of all non-cloud devices. Such a device acts as an IoT gateway, to securely interconnect devices in a local area network with cloud-based BEM software. This thesis focuses towards architecting, designing and prototyping an Internet-of-Things (IoT) gateway which can perform traversal on behalf of non-cloud devices. This IoT gateway enables cloud-based BEM software to have a comprehensive access to supported non-cloud devices. The IoT gateway has been designed to support BACnet, Modbus and HTTP RESTful, which are the three widely adopted communication protocols in the building automation and control domain. The developed software executes these three communication protocols concurrently to address requests from cloud-based BEM system. The performance of the designed architecture is independent of the number of devices supported by the IoT gateway software. / Master of Science