Showing 1–12 of 256 results
1Bit Sub Threshold Full Adders in 65nm CMOS Technology
In this paper a newرایگان!
In this paper a new full adder (FA) circuit optimized for ultra low power operation is proposed. The circuit is based on modified XOR gates operated in the subthreshold region to minimize the power consumption. Simulated results using 65nm standarad CMOS models are provided. The simulation esults show a 5% – 20% for frequency ranges from 1 KHz to 20MHz and supply voltages lower than 0.3V.
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 Combined Gate Replacement and Input Vector Control Approach for Leakage Current Reduction
Input vector controlرایگان!
Input vector control (IVC) is a popular technique for leakage power reduction. It utilizes the transistor stack effect in CMOS gates by applying a minimum leakage vector (MLV) to the primary inputs of combinational circuits during the standby mode. However, the IVC technique becomes less effective for circuits of large logic depth because the input vector at primary inputs has little impact on leakage of internal gates at high logic levels. In this paper, we propose a technique to overcome this limitation by replacing those internal gates in their worst leakage states by other library gates while maintaining the circuit’s correct functionality during the active mode. This modification of the circuit does not require changes of the design flow, but it opens the door for further leakage reduction when the MLV is not effective. We then present a divide-and- conquer approach that integrates gate replacement, an optimal MLV searching algorithm for tree circuits, and a genetic algorithm to connect the tree circuits. Our experimental results on all the MCNC91 benchmark circuits reveal that 1) the gate replacement technique alone can achieve 10% leakage current reduction over the best known IVC methods with no delay penalty and little area increase; 2) the divide-and-conquer approach outperforms the best pure IVC method by 24% and the existing control point insertion method by 12%; and 3) compared with the leakage achieved by optimal MLV in small circuits, the gate replacement heuristic and the divide-and-conquer approach can reduce on average 13% and 17% leakage, respectively.
A Computational Framework for Uncertainty Quantification and Stochastic Optimization in Unit Commitment With Wind Power Generation
We present a computaرایگان!
We present a computational framework for integrating a state-of-the-art numerical weather prediction (NWP) model in stochastic unit commitment/economic dispatch formulations that account for wind power uncertainty. We first enhance the NWP model with an ensemble-based uncertainty quantification strategy implemented in a distributed-memory parallel computing architecture. We discuss computational issues arising in the implementation of the framework and validate the model using real wind-speed data obtained from a set of meteorological stations. We build a simulated power system to demonstrate thedevelopments.
A fuzzy control system of diesel generator speed
Diesel generator, inرایگان!
Diesel generator, in which the generator is driven by the diesel engine to generate alternating current which frequency should keep stable and constant, is broadly used as mobile, urgent or field power sourc. The alternating current frequency is determined by the diesel speed. So the diesel speed should keep stable and constant too. This paper introduces two analogue control systems: rigid feedback and constant-speed feedback control system, and constructs a fuzzy control system of the diesel speed. Comparison of their control performances and practical applications indicate that the fuzzy control method is feasible and better than the others.
A fuzzy logic based multi-agents controller
This paper presentsرایگان!
This paper presents a fuzzy logic based controller (Multi-Agents System Controller (MASC)) which regulates the number of agents released to the network on a Multi-Agents Systems (MASs). A fuzzy logic (FL) model for the controller is as presented. The controller is a two-inputs-one- output system. The controllability is based on the network size (NTZ) and the available bandwidth (ABD) which are the inputs to the controller, the controller’s output is number of agents (ANG). The model was simulated using SIMULINK software. The simulation result is presented and it shows that ABD is the major constraint for the number of agents released to the network.
A hybrid multi-agent based particle swarm optimization algorithm for economic power dispatch
This paper presentsرایگان!
This paper presents a new multi-agent based hybrid particle swarm optimization technique (HMAPSO) applied to the economic power dispatch. The earlier PSO suffers from tuning of variables, randomness and uniqueness of solution. The algorithm integrates the deterministic search, the Multi-agent system (MAS), the particle swarm optimization (PSO) algorithm and the bee decision-making process. Thus making use of deterministic search, multi-agent and bee PSO, the HMAPSO realizes the purpose of optimization. The economic power dispatch problem is a non-linear constrained optimization problem. Classical optimization techniques like direct search and gradient methods fails to give the global optimum solution. Other Evolutionary algorithms provide only a good enough solution. To show the capability, the proposed algorithm is applied to two cases 13 and 40 generators, respectively. The results show that this algorithm is more accurate and robust in finding the global optimum than its counterparts.
A hybrid wavelet-ELM based short term price forecasting for electricity markets
Accurate electricity price forecasting is a formidable challenge for market participants and managers owing to high volatility of the electricity prices. Price forecasting is also the most important management goal for market participants since it forms the basis of maximizing profits. This study investigates the performance of a novel neural network technique called Extreme Learning Machine (ELM) in the price forecasting problem. Keeping in view the risk associated with electricity markets with highly volatile prices, relying on a single technique is not so profitable. Therefore ELM has been coupled with the Wavelet technique to develop a hybrid model termed as WELM (wavelet based ELM) to improve the forecasting accuracy as well as reliability. In this way, the unique features of each tool are combined to capture different patterns in the data. The robustness of the model is further enhanced using the ensembling technique. Performances of the proposed models are evaluated by using data from Ontario, PJM, New York and Italian Electricity markets. The experimental results demonstrate that the proposed method is one of the most suitable price forecasting techniques.
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 New Control Scheme for Hybrid Active Power Filter
That correcting poweرایگان!
That correcting power factors and eliminating harmonics current of network sides in supply systems is important, and it is always concerned by electric power users and electric power companies. In this paper, an advanced control techniques are advanced to realize the unified compensation of reactive power and harmonics. The new ideal advanced in this paper is to turn harmonics eliminations to harmonics suppressions, and it conduce stronger robustness of the controller to the disturbances caused by variation of load, parameter perturbations and unmodelled dynamics. The new control scheme can simplify the detection of harmonic current greatly. The method of suppression harmonics presented in the paper has strictly mathematical fundaments. In this paper a simulation example is given and the simulation results show the validity and the performance of the unified compensative method.
A New Control Strategy for a Multi-Bus MV Microgrid Under Unbalanced Conditions
This paper proposesرایگان!
This paper proposes a new control strategy for the islanded operation of a multi-bus medium voltage (MV) microgrid. The microgrid consists of several dispatchable electronically-coupled distributed generation (DG) units. Each DG unit supplies a local load which can be unbalanced due to the inclusion of singlephase loads. The proposed control strategy of each DG comprises a proportional resonance (PR) controller with an adjustable resonance frequency, a droop control strategy, and a negative-sequence impedance controller (NSIC). The PR and droop controllers are, respectively, used to regulate the load voltage and share the average power components among the DG units. The NSIC is used to effectively compensate the negative- sequence currents of the unbalanced loads and to improve the performance of the overall microgrid system. Moreover, the NSIC minimizes the negative-sequence currents in the MV lines and thus, improving the power quality of the microgrid. The performance of the proposed control strategy is verified by using digital time- domain simulation studies in the PSCAD/EMTDC software environment.