Showing 1–12 of 66 results
A cloud computing framework on demand side management game in smart energy hubs
The presence of enerرایگان!
The presence of energy hubs in the future vision of energy networks creates an opportunity for electrical engineers to move toward more efficient energy systems. At the same time, it is envisioned that smart grid can cover the natural gas network in the near future. This paper modifies the classic Energy Hub model to present an upgraded model in the smart environment entitling ‘‘Smart Energy Hub’’. Supporting real time, two-way communication between utility companies and smart energy hubs, and allowing intelligent infrastructures at both ends to manage power consumption necessitates large-scale real-time computing capabilities to handle the communication and the storage of huge transferable data. To manage communications to large numbers of endpoints in a secure, scalable and highly-available environment, in this paper we provide a cloud computing framework for a group of smart energy hubs. Then, we use game theory to model the demand side management among the smart energy hubs. Simulation results confirm that at the Nash equilibrium, peak to average ratio of the total electricity demand reduces significantly and at the same time the hubs will pay less considerably for their energy bill.
A New Battery Charger for Plug-in Hybrid Electric Vehicle Application using Back to Back Converter in a Utility Connected Micro-grid
The major drawbacksرایگان!
The major drawbacks of the most battery chargers for plug-in hybrid electric vehicle (PHEV) are high volume and weight, low power, long charging time, deleterious harmonic effects on the electric utility distribution systems and low flexibility and reliability. This paper proposes a new battery charger structure for PHEV application using back to back (B2B) converter in a utility connected micro-grid. In the proposed structure, an AC micro-grid, based on the typical household circuitry configuration, is connected to the grid via a B2B converter; and the DC link is used for battery charging. In fact, the B2B converter can provide an isolated, low cost, simple and reliable connection with power-flow management between the grid, micro-grid and battery. This proposed structure, depending on the power requirement of the vehicle, can run in four different modes: battery charging mode from the grid (G2V) or microgrid (M2V), vehicle to grid mode (V2G) and vehicle to micro-grid mode (V2H). The feasibility of the proposed scheme has been validated in the simulation study for various operating conditions.
A self-organized structure for mobility management in wireless networks
The objective of thiرایگان!
The objective of this work is to analyse performance of unstable mobile nodes with selforganization structures in Delay Tolerant Networks (DTN). This process enables the nodes to utilize their power fairly, and ensures that the links are established between nodes and used to improve the connectivity. In this paper two approaches are proposed: 1. Self-Healing (SH) and 2. Unstable Topology Structure (UTS) approaches based on localized computations. The proposed work is proven with simulations by analysing node degree, coverage area and Quality of Service (QoS) parameters. The performance of the work is analysed in a network simulator with mathematical models.
A simple power factor calculation for electrical power systems
The accurately and fرایگان!
The accurately and fast estimation of Phase Difference (PD) is required between the voltage and current of an AC electrical power system to calculate the Power Factor (PF) for defining how effectively the electrical energy is converted into the useful form. Many complex methods based on difficult mathematical equations are presented by the researchers to estimate the PD. In this study, a new and simple algorithm derived by using the trigonometric functions is proposed for PD estimation to calculate PF of a power system. With this method, the fast-time and unaffected by distorted sinusoids of PD estimation are carried out by decreasing the number of mathematical equations. The performance of the proposedmethod is evaluated under the various system conditions by performing the simulation case studies. The results of these studies are given to verify its effectiveness under the distorted system conditions.
An energy efficient approach to extend network life time of wireless sensor networks
The energy consumptiرایگان!
The energy consumption in wireless sensor networks is a significant matter and there are many ways to conserve energy. The use of mobile sensors is of great relevance to minimize the total energy dissipation in communication and overhead control packets. In a WSN, sensor nodes deliver sensed data back to the sink via multi hopping. The sensor nodes near the sink will usually consume more battery power than others; consequently, these nodes will quickly drain out their battery energy and decrease in the network lifetime of the WSN. The presence of mobilesinks causes increased energy reduction in their proximity, due to more relay load under multi hop communication. Moreover, node deployment technique can also be used to improve the life time of the network. Performance comparisons have been done by simulations between different routing protocols and our approach show efficient results.
An improved PSO-based charging strategy of electric vehicles in electrical distribution grid
Driven by the desireرایگان!
Driven by the desire to reduce environmental impacts and achieve energy independence, electric vehicles (EVs) are poised to receive mass acceptance from the general public. However, simultaneously connecting to electric distribution grid and charging with large number of EVs bring the necessity of optimizing the charging and discharging behaviors of EVs, due to the security and economy issue of the grid operation. To address this issue, we propose a novel EV charging model in this paper. The model concerns with following aspects, including optimal power flow (OPF), statistic characteristics of EVs, EV owners’ degree of satisfaction (DoS), and the power grid cost. An improved particle swarm optimization (PSO) algorithmis proposed for the model optimization. To evaluate our proposed optimal EV charging strategy, a 10-bus power distribution system simulation is performed for performance investigation. Simulation resultsshow that the proposed strategy can reduce the operational cost of the power grid considerately, while meeting the EV owner’s driving requirement. Also, better performance on the global search capability and optimal result of the improved particle swarm optimization algorithm is verified.
An SVM-Based Solution for Fault Detection in Wind Turbines
Research into faultرایگان!
Research into fault diagnosis in machines with a wide range of variable loads and speeds, such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by wind turbines for the diagnosis of mechanical faults in their mechanical transmission chain is insufficient. A successful diagnosis requires the inclusion of accelerometers to evaluate vibrations. This work presents a multi-sensory system for fault diagnosis in wind turbines, combined with a data-mining solution for the classification of the operational state of the turbine. The selected sensors are accelerometers, in which vibration signals are processed using angular resampling techniques and electrical, torque and speed measurements. Support vector machines (SVMs) are selected for the classification task, including two traditional and two promising new kernels. This multi-sensory system has been validated on a test-bed that simulates the real conditions of wind turbines with two fault typologies: misalignment and imbalance. Comparison of SVM performance with the results of artificial neural networks (ANNs) shows that linear kernel SVM outperforms other kernels and ANNs in terms of accuracy, training and tuning times. The suitability and superior performance of linear SVM is also experimentally analyzed, to conclude that this data acquisition technique generates linearly separable datasets.
Automated Demand Response From Home Energy Management System Under Dynamic Pricing and Power and Comfort Constraints
This paper presentsرایگان!
This paper presents a comprehensive and general optimization-based home energy management controller, incorporating several classes of domestic appliances includingdeferrable, curtailable, thermal, and critical ones. The operations of the appliances are controlled in response to dynamic price signals to reduce the consumer’s electricity bill whilst minimizing the daily volume of curtailed energy, and therefore considering the user’s comfort level. To avoid shifting a large portion of consumer demand toward the least price intervals, which could create network issues due to loss of diversity, higher prices are applied when the consumer’s demand goes beyond a prescribed power threshold. The arising mixed integer nonlinear optimization problem is solved in an iterative manner rolling throughout the day to follow the changes in the anticipated price signals and the variations in the controller inputs while information is updated. The results from different realistic case studies show the effectiveness of the proposed controller in minimizing the household’s daily electricity bill while preserving comfort level, as well as preventing creation of new least-price peaks.
Capacity withholding equilibrium in wholesale electricity markets
This paper is a quanرایگان!
This paper is a quantitative study of the capacity withholding incentives in the deregulated wholesale electricity markets and resulting price spikes. For the analysis we used an N-player Nash equilibrium model based on marginal cost functions of the generating firms assuming completely inelastic industry demand and complete information. The current results show that in the case of continuous marginal costs the withholding incentive always exists and the total withholding increases with the increase of the curvature of marginal cost functions and the extent of heterogeneity of the generating firms. The discrete form of real marginal cost functions imposes certain restrictions on the withholding. The analysis shows that there exists a threshold level of market demand below which no withholding occurs and above which the withholding becomes beneficial. The curvature and heterogeneity of marginal cost functions also affect the level of this threshold. The model is applied to the power generation in California ISO area.
Co-UWSN: Cooperative Energy-Efficient Protocol for Underwater WSNs
Sensor networks featرایگان!
Sensor networks feature low-cost sensor devices with wireless network capability, limited transmit power, resource constraints, and limited battery energy. Cooperative routing exploits the broadcast nature of wireless medium and transmits cooperatively using nearby sensor nodes as relays. It is a promising technique that utilizes cooperative communication to improve the communication quality of single-antenna sensor nodes. In this paper, we propose a cooperative transmission scheme for underwater sensor networks (UWSNs) to enhance the network performance. Cooperative diversity has been introduced to combat fading. Cooperative UWSN (Co-UWSN) is proposed, which is a reliable, energy-efficient, and high throughput routing protocol for UWSN. Destination and potential relays are selected that utilize distance and signal-to-noise ratio computation of the channel conditions as cost functions. This contributes to sufficient decrease in path losses occurring in the links and transferring of data with much reduced path loss. Simulation results show that Co-UWSN protocol performs better in terms of end-to-end delay, energy consumption, and network lifetime. Selected protocols for comparison are energy-efficient depth-based routing (EEDBR), improved adaptive mobility of courier nodes in threshold-optimized depth-based routing (iAMCTD), cooperative routing protocol for UWSN, and cooperative partner node selection criteria for cooperative routing Coop (Re and dth).
Demand Response Management via Real-Time Electricity Price Control in Smart Grids
This paper proposesرایگان!
This paper proposes a real-time pricing scheme that reduces the peak-to-average load ratio through demand response management in smart grid systems. The proposed scheme solves a two-stage optimization problem. On one hand, each user reacts to prices announced by the retailer and maximizes its payoff, which is the difference between its quality-of-usage and the payment to the retailer. On the other hand, the retailer designs the real-time prices in response to the forecasted user reactions to maximize its profit. In particular, each user computes its optimal energy consumption either in closed forms or through an efficient iterative algorithm as a function of the prices. At the retailer side, we develop a Simulated-Annealing-based Price Control (SAPC) algorithm to solve the non-convex price optimization problem. In terms of practical implementation, the users and the retailer interact with each other via a limited number of message exchanges to find the optimal prices. By doing so, the retailer can overcome the uncertainty of users’ responses, and users can determine their energy usage based on the actual prices to be used. Our simulation results show that the proposed realtime pricing scheme can effectively shave the energy usage peaks, reduce the retailer’s cost, and improve the payoffs of the users.
Design and Development of Single Switch High Step-Up DC-DC Converter
In this paper, a newرایگان!
In this paper, a new single switch high step-up dc-dc converter with high voltage gain is proposed. The proposed topology is developed by combining boost and SEPIC converter with diode – capacitor circuit to reduce the stress across the semiconductor devices. The proposed converter produces low switching voltage and hence it improves its efficiency. The operating principle and the steady state performance analysis are discussed. The performance of the converter is validated by developing a prototype circuit with input voltage of 30 V, output voltage of 300 V and output power rating of 250 W. The theoretical analysis and experimental results concludes the proposed converter is suitable for high voltage applications.