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CARBON REDUCTION POTENTIAL WITH INTELLIGENT CONTROL OF POWER SYSTEMS

IFAC Proceedings Volumes 2008年第2期41卷 13952-13957页

作者： Ganesh K. Venayagamoorthy Gabriele Braband Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 USA Simmons & Simmons Dusseldorf Germany

Climate change caused by anthropogenic greenhouse gas (GHG) emissions such as carbon dioxide (CO 2 ) is now widely accepted as a real condition that has potentially serious consequences for human society and industries need to factor this into their strategic plans. One salient planning assumption is that energy - essential for every activity - will become more expensive relative to other inputs. Economic growth does not have to be linked to an increase of GHG emissions and can be attained in addition to the usage of renewable energy sources by using energy efficiency technologies for power system generation, transmission, and distribution. The development of intelligent energy-efficient control technologies will both soften negative effects of the climate change on the economy and enhance energy security. This paper outlines the significant carbon reduction potential with intelligent control and optimization techniques applied to power system generation and transmission systems with and without wind farms.

关键词： Intelligent control Economics Emissions Optimization Power systems

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Implementation of a PSO based online design of an optimal excitation controller

Implementation of a PSO based online design of an optimal ex...

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IEEE Swarm Intelligence Symposium, SIS

作者： Chuan Yan Ganesh K. Venayagamoorthy Keith A. Corzine Real-time Power and Intelligent systems (RTPIS) laboratory in the Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Real-timePower and Intelligent systems (RTPIS) laboratory in the Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

The Navypsilas future electric ships will contain a number of pulsed power loads for high-energy applications such as radar, railguns, and advanced weapons. This pulse energy demand has to be provided by the ship energy sources, while not impacting the operation of the rest of the system. It is clear from studies carried out earlier that disturbances are created at the generator ac bus. This paper describes an online design and laboratory hardware implementation of an optimal excitation controller using particle swarm optimization (PSO) to minimize the effects of pulsed loads. The PSO algorithm has been implemented on a digital signal processor. laboratory results show that the PSO designed excitation controller provides an effective control of a generatorpsilas terminal voltage during pulsed loads, restoring and stabilizing it quickly.

关键词： Optimal control Marine vehicles Laboratories Voltage control Radar applications Railguns Weapons AC generators Hardware Particle swarm optimization

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Economic load dispatch using bacterial foraging technique with particle swarm optimization biased evolution

Economic load dispatch using bacterial foraging technique wi...

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IEEE Swarm Intelligence Symposium, SIS

作者： Ahmed Y. Saber Ganesh K. Venayagamoorthy Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology MO USA

This paper presents a novel modified bacterial foraging technique (BFT) to solve economic load dispatch (ELD) problems. BFT is already used for optimization problems, and performance of basic BFT for small problems with moderate dimension and searching space is satisfactory. Search space and complexity grow exponentially in scalable ELD problems, and the basic BFT is not suitable to solve the high dimensional ELD problems, as cells move randomly in basic BFT, and swarming is not sufficiently achieved by cell-to-cell attraction and repelling effects for ELD. However, chemotaxis, swimming, reproduction and elimination-dispersal steps of BFT are very promising. On the other hand, particles move toward promising locations depending on best values from memory and knowledge in particle swarm optimization (PSO). Therefore, best cell (or particle) biased velocity (vector) is added to the random velocity of BFT to reduce randomness in movement (evolution) and to increase swarming in the proposed method to solve ELD. Finally, a data set from a benchmark system is used to show the effectiveness of the proposed method and the results are compared with other methods.

关键词： Microorganisms Particle swarm optimization Power generation economics Space technology USA Councils Power system economics Optimization methods Gradient methods Neural networks Hopfield neural networks

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Particle Swarm Optimization with Quantum Infusion for the design of digital filters

Particle Swarm Optimization with Quantum Infusion for the de...

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IEEE Swarm Intelligence Symposium, SIS

作者： Bipul Luitel Ganesh Kumar Venayagamoorthy The Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla MO USA Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

In this paper, particle swarm optimization with quantum infusion (PSO-QI) has been applied for the design of digital filters. In PSO-QI, Global best (gbest) particle (in PSO star topology) obtained from particle swarm optimization is enhanced by doing a tournament with an offspring produced by quantum behaved PSO, and selecting the winner as the new gbest. Filters are designed based on the best approximation to the ideal response by minimizing the maximum ripples in passband and stopband of the filter response. PSO-QI, as is shown in the paper, converges to a better fitness. This new algorithm is implemented in the design of finite impulse response (FIR) and infinite impulse response (IIR) filter.

关键词： Particle swarm optimization Digital filters Finite impulse response filter IIR filters Algorithm design and analysis Chebyshev approximation Frequency Passband Signal processing algorithms Band pass filters

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Network-centric localization in MANETs based on particle swarm optimization

Network-centric localization in MANETs based on particle swa...

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IEEE Swarm Intelligence Symposium, SIS

作者： Raghavendra V. Kulkarni Ganesh K. Venayagamoorthy Ann Miller Cihan H. Dagli Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Department of Systems Engineering and Engineering Management Missouri University of Science and Technology Rolla MO USA

There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is proposed in this paper for network-centric target localization in MANETs that are enhanced by mobile robots. Simulation study of two application scenarios is conducted. While one scenario focuses on quick target localization, the other aims at convergence of MANET nodes around the target. Reduction of swarm size during PSO search is proposed for accelerated convergence. The results of the study show that the proposed algorithm is effective in network-centric collaborative navigation. Emergence of converging behavior of MANET nodes is observed.

关键词： Particle swarm optimization Mobile ad hoc networks Collaboration Navigation Centralized control Biological system modeling Convergence Energy efficiency Birds Mobile robots

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MIMO beam-forming with neural network channel prediction trained by a novel PSO-EA-DEPSO algorithm

MIMO beam-forming with neural network channel prediction tra...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chris Potter Ganesh K. Venayagamoorthy Kurt Kosbar Electrical Engineering at the Missouri University of Science and Technology Rolla MO USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Electrical Engineering Missouri University of Science and Technology Rolla MO USA

A new hybrid algorithm based on particle swarm optimization (PSO), evolutionary algorithm (EA), and differential evolution (DE) is presented for training a recurrent neural network (RNN) for multiple-input multiple-output (MIMO) channel prediction. The hybrid algorithm is shown to be superior in performance to PSO and differential evolution PSO (DEPSO) for different channel environments. The received signal-to-noise ratio is derived for un-coded and beam-forming MIMO systems to see how the RNN error affects the performance. This error is shown to deteriorate the accuracy of the weak singular modes, making beam-forming more desirable. Bit error rate simulations are performed to validate these results.

关键词： MIMO Recurrent neural networks Prediction algorithms Artificial neural networks Signal to noise ratio Manganese Training

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Online drift correction in wireless sensor networks using spatio-temporal modeling

Online drift correction in wireless sensor networks using sp...

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International Conference on Information Fusion

作者： Maen Takruri Sutharshan Rajasegarar Subhash Challa Christopher Leckie Marimuthu Palaniswami Centre for Real-Time Information Networks (CRIN) University of Technology Sydney Australia Department of Electrical and Electronic Engineering ARC Special Research Center for Ultra-Broadband Information Networks Australia Victoria Research Laboratory NICTA Australia Department of Computer Science and Software Engineering University of Melbourne Australia

Wireless sensor networks are deployed for the purpose of sensing and monitoring an area of interest. Sensors in the sensor network can suffer from both random and systematic bias problems. Even when the sensors are properly calibrated at the time of their deployment, they develop drift in their readings leading to erroneous inferences being made by the network. The drift in this context is defined as a slow, unidirectional, long-term change in the sensor measurements. In this paper we present a novel algorithm for detecting and correcting sensors drifts by utilising the spatio-temporal correlation between neigbouring sensors. Based on the assumption that neighbouring sensors have correlated measurements and that the instantiation of drift in a sensor is uncorrelated with other sensors, each sensor runs a support vector regression algorithm on its neigbourspsila corrected readings to obtain a predicted value for its measurements. It then uses this predicted data to self-assess its measurement and detect and correct its drift using a Kalman filter. The algorithm is run recursively and is totally decentralized. We demonstrate using real data obtained from the Intel Berkeley laboratory that our algorithm successfully suppresses drifts developed in sensors and thereby prolongs the effective lifetime of the network.

关键词： Support vector machines Mathematical model Temperature measurement Equations Kalman filters Training time measurement

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Artificial Immune System Based DSTATCOM Control for an Electric Ship Power System

Artificial Immune System Based DSTATCOM Control for an Elect...

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39th IEEE Power Electronics Specialists Conference (PESC 2008), vol.2

作者： Pinaki Mitra Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

Distribution Static Compensator (DSTATCOM) is a shunt compensation device which is generally used to solve power quality problems in distribution systems. In an all-electric ship power system, these power quality problems mainly arise due to the pulsed loads, which causes the degradation of the entire system performance. This paper presents the application of DSTATCOM to improve the power quality in a ship power system during and after pulsed loads. The control strategy of the DSTATCOM plays an important role in maintaining the voltage at the point of common coupling. A novel adaptive control strategy for the DSTATCOM based on artificial immune system (AIS) is proposed. The optimal parameters of the controller are first found using particle swarm optimization. This provides a sort of innate immunity to common system disturbances. For unusual system disturbances, these optimal parameters are modified online, thus providing adaptive immunity in the control system. To evaluate the performance of the DSTATCOM and the AIS adaptive controller, a ship power system is developed in the MATLAB/SIMULINK environment. The effectiveness of the DSTATCOM and the AIS controller is examined for pulsed loads of different magnitudes and durations.

关键词： Immune system Voltage control Marine vehicles Inverters Regulators Power systems Adaptive systems

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Energy-aware scheduling with deadline and reliability constraints in wireless networks

Energy-aware scheduling with deadline and reliability constr...

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International Conference on Broadband Networks (BroadNets)

作者： G. Sudha Anil Kumar G. Manimaran Z. Wang Real Time Computing and Networking Laboratory Department of Electrical and Computer Engineering Iowa State University Ames IA USA

ISBN: (纸本)9781424414321

In this paper, we address the problem of scheduling a set of periodic real-time messages in a wireless network with the objective of minimizing the total energy consumption while meeting deadline and reliability constraints. We formally prove that this problem is NP-hard and solve it in two stages. First, we consider a simple model that assumes that the wireless channel is completely reliable and the network is fully provisioned. Using the technique of employing multiple hop-by-hop transmissions instead of a single direct hop transmission as the basis, we prove that the strategy of choosing the hop distances such that they are equidistant is optimal in terms of energy consumption under the deadline constraint. Based on the intuition provided by the optimal strategy, we present heuristic scheduling algorithms for a more realistic wireless channel model and network condition. Our simulation results show that the proposed scheduling algorithms provide significant energy savings over the baseline algorithms

关键词： Wireless networks Energy consumption Scheduling algorithm Wireless application protocol Throughput Access protocols Streaming media Resource management Processor scheduling computer network reliability

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Energy-Aware Scheduling of real-time Tasks in Wireless Networked Embedded Systems

Energy-Aware Scheduling of Real-Time Tasks in Wireless Netwo...

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real-time Systems Symposium (RTSS)

作者： G. Sudha Anil Kumar G. Manimaran Z. Wang Real-Time Computing and Networking Laboratory Department of Electrical and Computer Engineering Iowa State University Ames IA USA

Recent technological advances have opened up several distributed real-time applications involving battery-driven embedded devices with local processing and wireless communication capabilities. Energy management is the key issue in the design and operation of such systems. In this paper, we consider a single-hop networked real-time embedded system where each node supports both dynamic voltage scaling (DVS) and dynamic modulation scaling (DMS) power management techniques to tradeoff time for energy savings. In this model, we address the problem of scheduling periodic complex tasks where each task consists of several precedence constrained message passing sub-tasks. Our contributions towards this problem are twofold. First, we analyze the system level energy-time tradeoffs considering both the computation and communication workloads by defining a novel energy gain metric. We then present static (centralized) and dynamic (distributed) energy gain based slack allocation algorithms which reduce the total energy consumption, while guaranteeing the ready time, deadline and precedence constraints. We compare the performance of the proposed algorithms with several baseline algorithms through simulation studies. Our results show that the proposed algorithms perform significantly better than the baseline algorithms for the simulated conditions. Finally, we identify several interesting energy-aware research problems in the area of networked real-time embedded systems.

关键词： real time systems Embedded system Energy management Wireless communication Dynamic voltage scaling Voltage control computer network management Power system management Power system modeling Processor scheduling

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