Since the inception of the Masdar Initiative in 2006, the Emirate of Abu Dhabi has invested a considerable amount of resources to promote renewable sources of energy like solar and wind. With an aim of achieving 7% of its electricity from renewable sources by the year 2020, there is much that the emirate needs to do in order to reduce its reliance on hydrocarbons while still planning capacity for future electricity demand. This report explores the effectiveness of a smart grid infrastructure as a mechanism to afford the flexibility and functionality required to incorporate renewable energy sources into the electric grid, as well as leveraging a real-time data network to attain reductions in peak demand consumption. Specific regulatory structures that exist in Abu Dhabi's electric and telecommunications markets are evaluated to understand the role they will play in dealing with interoperability standards, privacy concerns, and consumer participation issues that influence the effective integration of smart grid into Abu Dhabi's energy future. / text

Future smart grid systems will intelligently monitor and control energy flows in order to improve the efficiency and reliability of power delivery. This monitoring and control requires low-power, low-cost and highly reliable two-way communications between customers and utilities. To enable these two-way communication links, powerline communication (PLC) systems are attractive because they can be deployed over existing outdoor and indoor power lines. Power lines, however, have traditionally been designed for one-directional power delivery and remain hostile environments for communication signal propagation. In particular, non-Gaussian noise that is dominated by asynchronous impulsive noise and periodic impulsive noise, is one of the primary factors that limit the communication performance of PLC systems. For my PhD dissertation, I propose transmitter and receiver methods to mitigate the impact of asynchronous impulsive noise and periodic impulsive noise, respectively, on PLC systems. The methods exploit sparsity and/or cyclostationarity of the noise in both time and frequency domains, and require no or minor training overhead prior to data transmission. Compared to conventional PLC systems, the proposed transceivers achieve dramatic improvement (up to 1000x) in coded bit error rates in simulations, while maintaining similar throughput. / text

The impact of distributed energy resources (DERs), electric vehicles/plug-in hybrid electric vehicles (EVs/PHEVs), and smart appliances on the distribution grid has been expected to be beneficial in terms of environment, economy, and reliability. But, it can be more beneficial by implementing smart controls. In the absence of additional controls, a negative effect was identified regarding the service lifetime of power distribution components. This research presents a new class of a smart house energy management system that can provide management and control of a residential house electric energy without inconvenience to the residents of the house and without overloading the distribution infrastructure. The implementation of these controls requires an infrastructure that continuously monitors the house power system operation, determines the real-time model of the house, computes better operating strategies over a planning period of time, and enables control of house resources. The smart house energy management system provides benefits for the good of utility and customer. In case of variable electricity rates, the management system can reduce the customer’s total energy cost. The benefits can be also extended to provide ancillary services to the utility such as control of peak load and reactive power support– assuming that this is worked out under a certain mutually beneficial arrangement between the utility and customer.

By using IT-solutions, the flexibility on the demand side in the electrical systems could be increased. This is called demand response and is part of the larger concept called smart grids. Previous work in this area has concerned the utilization of demand response by grid owners. In this thesis the focus will instead be shifted towards the electrical companies that have balance responsibility, and how they could use demand response in order to make profits. By investigating electrical appliances in hourly measured households, the business value from decreasing electrical companies’ power imbalances has been quantified. By an iterative simulation scheme an optimal value was found to be 977 SEK/year and appliance. It could however be shown that the value became larger for energy inefficient households, and that such consumers’ participation in a demand response market would be prioritized ahead of other measures like isolating walls is rather unlikely. Thermal appliance whose load depend on the outdoor temperature are less valuable for demand response during the summer months, and the annual value would increase if less seasonally dependent appliances were used. Additionally, by increasing the market price amplitudes and the imbalance price volatility, it could be shown that the potential for such demand response markets is larger in e.g. the Netherlands and Germany.

Bidirectional vehicle-to-grid (V2G) system utilizes the batteries of parked electric-drive-vehicles to provide energy storage and backup services in a power system. Such services in a V2G-equipped microgrid system can be used as an enabler of enhancing the renewable energy source (RES) penetration by storing the energy during the surplus of RES supply and supplying the energy during the lack of RES supply. In this research, we aim at enhancing the storage capacity of V2G system by introducing a novel vehicle-to-vehicle power transfer operation that runs on the top of V2G services. The vehicle-to-vehicle (V2V) operation transfers the energy from the source vehicles (which are parked for relatively longer times) to the destination vehicles (which are parked for relatively shorter times). The depleted energy of the source vehicles is fulfilled by the surplus RES supply in the future. In this way, the destination vehicles are effectively charged by RES supply, thereby enhancing the storage capacity of the V2G system. We can also say that the V2V operation would become beneficial only when there is a sufficient amount of surplus RES supply in the future. We propose a decision rule to distinguish if a vehicle should be a source vehicle or a destination vehicle during the V2V operation. The decision rule is designed based on the two factors, namely the state-of-charge of vehicle’s battery, and the remaining time of vehicle to depart. In this research, we conduct a comprehensive study to analyze the impacts of state-of-charge and mobility pattern of vehicles on different performance metrics via simulation. The results shows that in order to achieve better performance of V2V operation, the state-of-charge of vehicle’s battery should be given more priority over the remaining time of vehicle to depart. The vehicle mobility pattern with unexpected departure greatly reduced the overall performance of the V2G system.

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.

In this dissertation, the issues of the increased awareness of energy use are considered. Energy technologies are continuously improved by energy retailers and academic researchers. The Smart Grid are soon customary as part of the energy domain. But in order to improve energy efficiency the change must come from the consumers. Consumers should be active decision makers in the Smart Grid domain and therefor a Recommender system suits the Smart Grid and enables customers. Customers will not use energy in the way energy retailers, and politicians advocates instead they will do what fits them. By investigating how a Recommender can be built in the Smart Grid we focus on parameters and information that supports the costumers and enables positive change. An investigation of what customers perceive as relevant is pursued as well as how relevancy can adjust the system. A conceptual model of how to build a Recommender is rendered through a literature review, a group interview and a questionnaire.

This thesis addresses the future of sustainable energy distribution and transportation in the United States. Predictions of future energy and transportation demands promote localized energy as the most likely situation. Existing proposals outlining the benefits of decentralized energy production fail to engage architecture. Cities will require new architectural typologies that can integrate new energy infrastructure in the city. Los Angeles, the archetype of the decentralized American city, is introduced as a case study. The city is examined at multiple scales for the integration of a decentralized electricity network and an efficient transportation infrastructure. Siting the proposed facilities capitalizes on new and existing transportation infrastructures and local energy resources. The new electricity-transportation infrastructure is adapted to a decentralized network functioning on principles of ecosystems and energy economics at an urban scale. Energy storage is paired with multi-modal transportation to develop new architectural and urban typologies. This enables the decentralized urban proposal to function as a network exhibiting mutually beneficial characteristics.

With the great potential smart distribution systems have to cause a paradigm shift in conventional distribution systems, many areas need investigation. Throughout the past few decades, many distribution systems reliability indices have been developed. Varying in their calculation techniques, burden, and purpose of calculation, these indices covered wide range of reliability issues that face both utilities and regulators. The major purpose of the continuous development of reliability indices is to capture a comprehensive idea of systems performance. While systems are evolving to a much more smarter and robust ones, so do the assessment tools need to be improved. The lack of consensus among utilities and regulators on which indices should be used complicate the problem more. Furthermore, regulators still come short when it comes to standard implementation because no final standard have been developed. However, regulators tend to advice or impose certain numbers on utilities based on historic performances. Because of the inevitable comparisons made by regulators on the routinely practiced process of utilities’ reporting of some of their indices, adequate and fair process needs to be implemented. The variation in utilities perspective on the advice or imposed indices cause an additional burden to achieving fair and adequate designs, upgrade requirements, and public goodwill. Some utilities consider these regulators recommendations guidelines; others treat them as strict standards, and yet others consider them goals. In this work, a development of a unified reliability index, which can yield proper performance assessment, fair comparisons, and reflection of all the knowledge imbedded within all current indices, will be developed. The developed unified index provides several benefits, among which is adequate standards design, improved tools for planning and design optimization, and less technical burden on operators. In addition, the development of a unified reliability index required the development of a standard normalization methodology.

The few past years have witnessed a huge leap in the field of the smart grid communication networks in which many theories are being developed, and many applications are being evolved to accommodate the implementation of the smart grid concepts. Distribution power systems are considered to be one of the first leading fields having the strong desire of applying the smart grid concepts; resulting in the emersion of the smart distribution power systems, which are the future visualization of the distribution systems having both the ability of smart acting, and the capabilities of automation, self-healing, and decentralized control. For the sake of the real implementation of the smart distribution power systems, the main functions performed by the traditional systems have to be performed by the new smart systems as well, taking into account the new features and properties of those smart systems. One of those main functions is the ability of power networks optimal reconfiguration to minimize the system’s power loss while preserving the system radial topology. The proposed reconfiguration methodology targets the utilization of a hybrid genetic algorithm with two fuzzy controllers that could converge to the global optimal network configuration with the fastest convergence rate consuming the least computational time. The first fuzzy controller is designed to reject any infeasible system configurations that might show up in the population of the genetic algorithm and violate the system radial topology, while the second fuzzy controller is designed to adapt the mutation rate of the genetic algorithm. Consequently, a novel multi-agent system is proposed and designed to perform the reconfiguration application in smart distribution power systems employing the concepts of distributed processing and decentralized control demanded by those systems. A multi-agent system employs a group of intelligent agents that have the capabilities of autonomy, reactivity, pro-activity, and sociality. Those agents cooperate with each other in order to perform a certain function through their powerful abilities to communicate, socialize, and make a common decision in a decentralized fashion based on the information retrieved from the surrounding environment and compiles with their ultimate objective.