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Advanced Metering Infrastructure (AMI) plays a crucial role in Demand Side Management (DSM) in Smart Grid systems. It provides real-time, two-way communication capabilities between a utility/load aggregator and consumers. The communication infrastructure, by virtue of topological weaknesses, is vulnerable to cyber attacks that are undetectable or stealthy. This work investigates the topological vulnerabilities...
Ocean wave energy farms are composed of several wave energy converter devices. The objective of each converter is to capture the potential and kinetic energy in rolling ocean waves and convert them into electricity. An important task in optimizing power delivery from ocean wave energy farms is short term prediction of incoming ocean waves. Accurate predictions enable predictive wave energy converter...
The problem of global positioning system (GPS) spoofing attacks on smart grids endowed with phasor measurement units (PMUs) is addressed, taking into account the dynamical behavior of the states of the system. First, it is shown how GPS spoofing introduces a timing synchronization error in the phasor readings recorded by the PMUs and alters the measurement matrix of the dynamical model. Then, a generalized...
In order to obtain the maximum power absorption of wave power devices, the mean gain factor q for the array and its characteristics are discussed in this paper. Some characteristics about the maximum q are studied through theoretical derivation and numerical examples. Also, the relationship between the maximum q and the properties of the optimum linear arrays of wave power devices are explored through...
In the IEEE 1588 Precision Time Protocol (PTP), the recovery of clock frequency and phase from packet timestamps must be modeled as a statistical estimation problem, due to the random nature of end-to-end delays that is inherent to packet-switched networks. Recently, a new minimax optimum estimator for phase offset estimation was proposed by the authors. This approach assumes that perfect frequency...
In this study we propose the development of an adaptive particle swarm optimization (APSO) learning algorithm to train a non-linear autoregressive (NAR) neural network, which we call PSONAR, for short term time series prediction of ocean wave elevations. We also introduce a new stochastic inertial weight to the APSO learning algorithm. Our work is motivated by the expected need for such predictions...
Short term forecasting is a vital interest to future implementations of a smart grid, particularly in the reliable integration of renewable energy resources. In this study we focus on multi-step prediction of high resolution wave power. Significant wave height data was first obtained from Belmullet Berth, Ireland and underwent several data preprocessing steps. These include a linear interpolation...
Wave energy extraction technologies are rapidly maturing, leading to increased expectations that they will soon be integrated into the electrical grid. This paper reviews the state of the art technologies along with system level modeling while providing an initial study of the impacts of integration on a typical electrical grid network as compared to the closest related technology, wind energy extraction...
There has been recent interest in the use of packet-based synchronization techniques based on the IEEE 1588 Precision Time Protocol, in order to meet challenges arising in mobile telecommunication networks. An important problem in this area is to design estimators that determine the phase offset of slave clocks, while being resilient to the degrading effects of random network traversal times. While...
A key way for the power grid to withstand increasing demand electricity and a more diverse and unpredictable mix of energy resources is to encourage demand side participation in the electricity market. Recent rulings by the Federal Energy Regulatory Commission (FERC) favor not only the inclusion of but also the compensation for Demand Response (DR) aggregators in the wholesale electricity market....
In the near future, our society will face an inevitable transition from consuming fossil fuels to renewable resources like wind and solar energy. It is mainly envisioned that this shift can happen through a widespread deployment of energy storage devices, clean generation reserves, or by making the demand for electricity more price elastic than what is practiced in the current operational framework...
In this paper, we conduct performance analysis for a joint media access and appliance scheduling protocol devised for efficient information-management in smart appliances within a home-area network. This protocol enables appliances in-home to coordinate power usage so that total demand for the home is kept below a target value. In particular, from the system perspective, we model the evolution of...
There is a global consensus that our path towards a greener future depends on finding ways to reliably integrate renewable energy sources into the generation pool of our power grids. This vision is accompanied by the challenge of making demand significantly more flexible in order to compensate for the intermittent nature of renewable generation outputs and keeping the demand and supply continuously...
The future electricity grid will include greater and more sophisticated demand side participation. Favored by recent rulings by the Federal Energy Regulatory Commission (FERC), Demand Response (DR) aggregators can combine load requests from a large consumer base and provide load modifications that will be compensated in the wholesale electricity market at the market price. This paper examines the...
This paper proposes a Real-Time Pricing (RTP)-based power scheduling scheme as demand response for residential power usage. In this scheme, the Energy Management Controller (EMC) in each home and the service provider form a Stackelberg game, in which the EMC who schedules appliances' operation plays the follower level game, and the provider who sets the real-time prices according to current power...
This paper presents the joint transmitter and receiver design with adaptive beamforming for multiple-input multiple output (MIMO) single carrier-frequency division multiple access (SC-FDMA) systems. Overall signal to interference plus noise ratio (SINR) of estimated symbols is maximized by selecting appropriate transmit power, transmit and receive beamforming weights and frequency domain-linear equalization...
This paper proposes a distributed pricing-based user cooperation strategy for a two-user model focusing on performance from the delay perspective. It explores the fact that cooperation (i.e., one-way relaying as opposed to mutual relaying) is beneficial when users channel conditions are distinct. The strategy only allows valuable cooperation, i.e., the user with a good channel helps relay the packet...
This paper presents the system level performance evaluation for energy-detection based cooperative spectrum sensing in cognitive radio networks. Three performance criteria are quantitively analyzed for cooperative spectrum sensing. First, the average error probability is determined given fixed amplifier gains for a fixed number of secondary users by considering all possible channel realizations. Second,...
This paper addresses optimal spectrum sensing in cognitive radio networks considering its system level cost that accounts for the local processing cost of sensing (sample collection and energy calculation at each secondary user) as well as the transmission cost (forwarding energy statistic from secondary users to fusion center). The optimization problem solves for the appropriate number of samples...
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