In recent years, significant advances have been achieved in communication networks and electric power systems. Communication networks are developed to provide services within not only well-connected network environments such as wireless local area networks, but also challenged network environments where continuous end-to-end connections can hardly be established between information sources and destinations. Delay tolerant network (DTN) is proposed to achieve this objective by utilizing a store-carry-and-forward routing scheme. However, as the network connections in DTNs are intermittent in nature, the management of network resources such as communication bandwidth and buffer storage becomes a challenging issue. On the other hand, the smart grid is to explore information and communication technologies in electric power grids to achieve electricity delivery in a more efficient and reliable way. A high penetration level of electric vehicles and renewable power generation is expected in the future smart grid. However, the randomness of electric vehicle mobility and the intermittency of renewable power generation bring new challenges to the resources management in the smart grid, such as electric power, energy storage, and communication bandwidth management. This thesis consists of two parts. In part I, we focus on the resource management in DTNs. Specifically, we investigate data dissemination and on-demand data delivery which are two of the major data services in DTNs. Two kinds of mobile nodes are considered for the two types of services which correspond to the pedestrians and high-speed train passengers, respectively. For pedestrian nodes, the roadside wireless local area networks are used as an auxiliary communication infrastructure for data service delivery. We consider a cooperative data dissemination approach with a packet pre-downloading mechanism and propose a double-loop receiver-initiated medium access control scheme to resolve the channel contention among multiple direct/relay links and exploit the predictable traffic characteristics as a result of packet pre-downloading. For high-speed train nodes, we investigate on-demand data service delivery via a cellular/infostation integrated network. The optimal resource allocation problem is formulated by taking account of the intermittent network connectivity and multi-service demands. In order to achieve efficient resource allocation with low computational complexity, the original problem is transformed into a single-machine preemptive scheduling problem and an online resource allocation algorithm is proposed. If the link from the backbone network to an infostation is a bottleneck, a service pre-downloading algorithm is also proposed to facilitate the resource allocation. In part II, we focus on resource management in the smart grid. We first investigate the optimal energy delivery for plug-in hybrid electric vehicles via vehicle-to-grid systems. A dynamic programming formulation is established by considering the bidirectional energy flow, non-stationary energy demand, battery characteristics, and time-of-use electricity price. We prove the optimality of a state-dependent double-threshold policy based on the stochastic inventory theory. A modified backward iteration algorithm is devised for practical applications, where an exponentially weighted moving average algorithm is used to estimate the statistics of vehicle mobility and energy demand. Then, we propose a decentralized economic dispatch approach for microgrids such that the optimal decision on power generation is made by each distributed generation unit locally via multiagent coordination. To avoid a slow convergence speed of multiagent coordination, we propose a heterogeneous wireless network architecture for microgrids. Two multiagent coordination schemes are proposed for the single-stage and hierarchical operation modes, respectively. The optimal number of activated cellular communication devices is obtained based on the tradeoff between communication and generation costs.

The nature of electrical power requires specific infrastructure in order to operate adequately. Currently, the United States electricity grid contains a number of bottlenecking inefficiencies that arise from the aging infrastructure of the system. This paper examines the current state of the United States electricity grid, how potential changes in weather variables can affect the electricity consumption of residential consumers, and how implementation of Smart Grid technology can potentially mitigate these issues. It is determined through regression analysis that each weather variable that was tested proves significant for at least one of the consumers compared. This indicates that there is an enormous magnitude of individual variables that factor into residential electricity consumption and that more efficient and integrated electricity practices are necessary to optimize efficiency.

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.

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.

This thesis develops a power line carrier(PLC) communication module using FSK modulation technology by integration of PLC chip, with various hardware circuits such as DSP, signal coupling and amplifier circuits, filter. The communication performance and conduction EMI tests and executed for the communication module developed. The PLC module is then applied for appliance control of commercial customers to fulfill the demand response function for energy conservation by reducing the summer peak loading. Besides sending the load control command from central station in the smart grid, the power consumption of various appliances can also be collected and transmitted back to the control station via two way communication with the PLC communication module. Finally, the broadband PLC (BPLC) is applied for the CCTV supervision in system to support asset management of distribution room to prevent the power equipment from steal. With the remote control of light brightness and CCTV lens with high data transmission rate provided, the communication performance of PLC can therefore be verified in this study.

In the next decade, electric vehicles (EV) will be heading to the road in a fast speed. Utility company would have no control over the future EV charging points or stations, and no direct control over periods and frequency of EV charging that could cause great effects to the existing distribution network operations if not well planned. Distribution system operation and expansion planning would become more complicated due to the high degree of uncertainty of the EV charging demand. Markov model is used in this study to calculate the probabilities and locations of EV charging. To mitigate the loading and voltage quality problem, feeder reconfiguration is proposed. The problem is formulated as an stochastic programming program with an objective function of minimizing total switching and system loss costs, and subject to radial structure of the distribution network and security constraints. The problem is solved by a binary particle swarm optimization technique. Test results indicate that feeder reconfiguration can be exercised to match loading patterns of different types of feeders (residential, commercial and industrial) with various stochastic charging scenarios, and consequently, reduce the impacts of EV charging and optimize the use of the existing network.

The issue of energy shortage has arisen in recent years. All countries must discuss the manner to reduce energy consumption, and smart grid is a better one of the solutions. According to related researches, energy consumption can be effectively reduced using energy management information of smart grids. By using smart grids, electricity suppliers can learn about the current energy consumption of neighborhoods, and control the electrical energy generation and price of electrical energy. Users can learn the current price of electrical energy and obtain energy management information from smart meters for energy management and device control. However, electricity consumptions of users may divulge the privacy information of users. Therefore, privacy of users and communication security of smart grid become crucial security issues. In this thesis, we propose a provably secure power usage data aggregation scheme for smart grids. Electricity suppliers can learn about the current power usage of neighborhoods without knowing the individual electricity consumption of each user, and use the current power usage of neighborhoods to arrange energy distribution. Therefore, electricity suppliers cannot use the data to reveal lifestyles of each user. In our scheme, the transmission information is encrypted and signed to prevent theft or tampering of data. Finally, we also provide formal proofs for our scheme in this thesis.

This paper presents a fault-tolerant (fault tolerant) can enhance the communications capabilities, improve the reliability and efficiency of in smart grid signal transmission. Meter layout with PLC or ZigBee in any topology, meter adopt Minimum Spanning Tree algorithm to achieve shortest distance and lost cost in PLC; when device contain wireless receiver, meter adopt Hungarian algorithm can search nearest itself¡¦s device to receive device information. The paper propose two fault tolerant methods: static and dynamic methods. Static method is a meter transmit to another one with regular communication even if a meter tranfmit with ZigBee; dynamic method is a meter transmit another one, ZigBee has low priority according to cost function in effective communication range. The paper simulation in any 100m2 topology, randon produce 13 SmartUnit with different number of meters and coordinate, two fault tolerant method can achieve 100% fault coverage in single link fault case; but static method use FTGDB(Fault Tolerant Generalized De Bruijn algorithm) multiple fault coverage can achieve 43% with d=4 case; dynamic method use Kth shortest path algorithm multiple fault coverage can achieve 61% with d=4 case. In other words FTGDB has average 100 communication line allow average 43 communication line fault tolerant ability with d=4 case in 13 SmartHomeUnit; Kth shortest path algorithm has average 100 communication line allow average 61 communication line fault tolerant ability with d=4 case in 13 SmartHomeUnit. If after fault tolerant achievement, count to demand energy and delay time with PLC and ZigBee, then it can offer electric company information. Electric company evaluate electric cost¡Breal time price etc¡K The paper propose a online demand response method, the method is Online Priority Tree algorithm to be counted end device¡¦s rank priority according to device importance.

Society depends on computer networks for communication. The networks were built to support and facilitate several important applications such as email, web browsing and instant messaging. Recently, there is a significant interest in leveraging modern local and wide area communication networks for improving reliability and performance in critical infrastructures. Emerging critical infrastructure applications, such as smart grid, require a certain degree of reliability and Quality of Service (QoS). Supporting these applications requires network protocols that enable delay sensitive packet delivery and packet prioritization. However, most of the traditional networks are designed to provide best effort service without any support for QoS. The protocols used in these networks do not support packet prioritization, delay requirements and reliability. In this thesis, we focus on the design and analysis of communication protocols for supporting smart grid applications. In particular, we focus on the Substation Automation Systems (SAS). Substations are nodes in the smart grid infrastructure that help the in transportation of power by connecting the transmission and distribution lines. The SAS applications are con figured to operate with minimal human intervention. The SAS monitors the line loads continuously. If the load values are too high and can lead to damage, the SAS declares those conditions as faults. On fault detection, the SAS must take care of the communication with the relay to open the circuit to prevent any damage. These messages are of high priority and require reliable, delay sensitive delivery. There is a threshold for the delay of these messages, and a slight increase in the delay above the threshold might cause severe damages. Along with such high priority messages, the SAS has a lot of background traffic as well. In spite of the background traffic, the substation network must take care of delivering the priority messages on time. Hence, the network plays a vital role in the operation of the substation. Networks designed for such applications should be analyzed carefully to make sure that the requirements are met properly. We analyzed and compared the performance of the SAS under di erent network topologies. By observing the characteristics of the existing architectures, we came up with new architectures that perform better. We have suggested several modi cations to existing solutions that allow significant improvement in the performance of the existing solutions.

A “smarter grid” is expected to be more flexible and more reliable than traditional electric power grids. Among technologies required for the “smarter grid” deployment, this dissertation presents a sustainable microgrid and a spatial and temporal model of plug-in electric vehicle charging demand for the “smarter grid”. First, this dissertation proposes the dynamic modeling technique and operational strategies for a sustainable microgrid primarily powered by wind and solar energy resources. Multiple-input dc-dc converters are used to interface the renewable energy sources to the main dc bus. The intended application for such a microgrid is an area in which there is interest in achieving a sustainable energy solution, such as a telecommunication site or a residential area. Wind energy variations and rapidly changing solar irradiance are considered in order to explore the effect of such environmental variations to the intended microgrid. The proposed microgrid can be operated in an islanded mode in which it can continue to generate power during natural disasters or grid outages, thus improving disaster resiliency of the “smarter grid”. In addition, this dissertation presents the spatial and temporal model of electric vehicle charging demand for a rapid charging station located near a highway exit. Most previous studies have assumed a fixed charging location and fixed charging time during the off-peak hours for anticipating electric vehicle charging demand. Some other studies have based on limited charging scenarios at typical locations instead of a mathematical model. Therefore, from a distribution system perspective, electric vehicle charging demand is still unidentified quantity which may vary by space and time. In this context, this study proposes a mathematical model of electric vehicle charging demand for a rapid charging station. The mathematical model is based on the fluid dynamic traffic model and the M/M/s queueing theory. Firstly, the arrival rate of discharged vehicles at a charging station is predicted by the fluid dynamic model. Then, charging demand is forecasted by the M/M/s queueing theory with the arrival rate of discharged vehicles. The first letter M of M/M/s indicates that discharged vehicles arrive at a charging station with the Poisson distribution. The second letter M denotes that the time to charge each EV is exponentially distributed, and the third letter s means that there are s identical charging pumps at a charging station. This mathematical model of charging demand may allow grid’s distribution planners to anticipate charging demand at a specific charging station. / text