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Making the power grid more intelligent

Making the power grid more intelligent

引用

iREP Symposium on Bulk Power System Dynamics and Control

作者： Salman Mohagheghi Ronald G. Harley Ganesh K. Venayagamoorthy School of Electrical and Computer Engineering Georgia Institute of Technology Intelligent Power Infrastructure Consortium Atlanta GA USA Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory University of Missouri Rolla MO USA

Summary form only given. This paper focuses on the applications of intelligent techniques for improving the performances of the power system controllers. Intelligent control techniques lay the foundation of the next generation of nonlinear controllers and have the advantage of further improving the controller's performance by incorporating heuristics and expert knowledge into its design. Most of these techniques are independent of any mathematical model of the power system, which proves to be a considerable advantage.

关键词： Power grids Power system modeling Control systems Power system dynamics Power system control Power systems Power system reliability Intelligent networks Humans Three-term control

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Optimal Control of Class of Non-linear Plants Using Artificial Immune Systems: Application of the Clonal Selection Algorithm

Optimal Control of Class of Non-linear Plants Using Artifici...

引用

IEEE International Symposium on Intelligent Control (ISIC)

作者： S.A. Panimadai Ramaswamy G.K. Venayagamoorthy S.N. Balakrishnan Department of Electrical and Computer Engineering University of Missouri Rolla MO USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA Department of Mechanical AeroSpace and Engineering Mechanics University of Missouri Rolla MO USA

The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diverse engineering problems have been solved in the recent past using AIS. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. The process of affinity maturation of the immune system is explicitly incorporated in this algorithm. This paper presents the application of AIS for the optimal control of a class of non-linear plants which are affine in control. The clonal selection algorithm is adapted for optimal control. A new mutation operator that operates on real values and one that aids in fast convergence is developed in this paper. AIS is used to obtain constant coefficient Kalman gain matrices. The validation and evaluation of the results thus obtained are carried out by comparing with standard and the widely used State Dependent Algebraic Riccati Equation (SDARE) method for the non-linear plants. In case of non-linear systems with hard state constraints, the SDARE formulation requires the use of mathematically involved expressions to incorporate these state constraints. However, the modified clonal selection algorithm developed in this paper has been used with hardly any changes to incorporate the hard state constraints and obtain the Kalman gain matrix.

关键词： Optimal control Artificial immune systems Immune system Kalman filters Riccati equations Protection Organisms Pathogens Computational intelligence Systems engineering and theory

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Adaptive Critic Design Based Neuro-Fuzzy Controller for a Static Compensator in a Multimachine Power System

Adaptive Critic Design Based Neuro-Fuzzy Controller for a St...

引用

IEEE General Meeting Power& Energy Society

作者： Salman Mohagheghi Ganesh K. Venayagamoorthy Ronald G. Harley School of Electrical and Computer Engineering Georgia Institute of Technology Intelligent Power Infrastructure Consortium Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Summary form only given. This paper presents a novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system, using artificial neural networks and fuzzy logic. The action dependent heuristic dynamic programming (ADHDP), a member of the adaptive critic designs (ACD) family, is used for the design of the STATCOM neuro-fuzzy controller. This neuro-fuzzy controller provides optimal control based on reinforcement learning and approximate dynamic programming, and can effectively perform in the presence of noise and uncertainties. Using a proportional-integrator approach the proposed controller is capable of dealing with actual rather than deviation signals. The STATCOM is connected to a multimachine power system in order to provide voltage support during the steady state performance of the power system and also improve the dynamic stability of the network during faults and disturbances. Two multimachine power systems are considered in this study: a 10-bus 2-generator system and a 45-bus 10-generator system, where the latter is a section of the Brazilian power grid. Simulation results are provided to show that the proposed controller outperforms a conventional PI controller in large scale faults as well as small disturbances.

关键词： Programmable control Adaptive control Control systems STATCOM Power systems Power system dynamics Power system stability Optimal control Automatic voltage control Power system faults

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Neural-network-based intelligent control for improving dynamic performance of FACTS devices

Neural-network-based intelligent control for improving dynam...

引用

iREP Symposium on Bulk Power System Dynamics and Control

作者： Wei Qiao Ronald G. Harley Ganesh K. Venayagamoorthy Intelligent Power Infrastructure Consortium School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Flexible AC transmission system (FACTS) devices are widely recognized as powerful controllers to improve the dynamic performance and stability of power systems. The standard FACTS controllers are linear controllers designed around a specific operating point from a linearized system model with fixed parameters. However, at other operating points their performance degrades. Neural-network-based nonlinear intelligent control offers an attractive approach to overcome the drawbacks of the linear controllers. This paper presents two different neural-network-based intelligent control architectures, i.e., indirect adaptive neurocontrol and adaptive critic design based optimal neurocontrol, for designing the external control of an SSSC FACTS device. Simulation studies are carried out to evaluate the proposed nonlinear intelligent controllers on single machine infinite bus as well as multi-machine power systems. Results show that the proposed intelligent controls improve the dynamic performance of the SSSC and the associated power network.

关键词： Intelligent control Power system dynamics Flexible AC transmission systems Power system stability Power system modeling Programmable control Adaptive control Power system simulation Control systems Nonlinear dynamical systems

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DHP-Based Wide-Area Coordinating Control of a Power System with a Large Wind Farm and Multiple FACTS Devices

DHP-Based Wide-Area Coordinating Control of a Power System w...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Wei Qiao Ganesh K. Venayagamoorthy Ronald G. Harley Intelligent Power Infrastructure Consortium (IPIC) in the School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory in the Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area monitor and wide-area coordinating neurocontroller (WACNC), based on wide-area measurements, for a power system with power system stabilizers, a large wind farm, and multiple flexible ac transmission system (FACTS) devices. The wide-area monitor is a radial basis function neural network (RBFNN) that identifies the input-output dynamics of the nonlinear power system. Its parameters are optimized through a particle swarm optimization (PSO) based method. The WACNC is designed by using the dual heuristic programming (DHP) method and RBFNNs. It operates at a global level to coordinate the actions of local power system controllers. Each local controller communicates with the WACNC, receives remote control signals from the WACNC to enhance its dynamic performance, and therefore helps improve system-wide dynamic and transient performance.

关键词： Power system control Control systems Power systems Wind farms Power system dynamics Power system measurements Monitoring Flexible AC transmission systems Power system transients Power industry

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Management of an intelligent argumentation network for a web-based collaborative engineering design environment

Management of an intelligent argumentation network for a web...

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International Symposium on Collaborative Technologies and Systems

作者： Xiaoqing Liu Man Zheng Ganesh K. Venayagamoorthy Ming Leu Department of Computer Science University of Missouri Rolla Rolla MO USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical & Computer Engineering University of Missouri Rolla Rolla MO USA Department of Mechanical and Aerospace Engineering University of Missouri Rolla Rolla MO USA

ISBN: (纸本)9781424433896;0978569911

Conflict resolution is one of the most challenging tasks in collaborative engineering design. In our previous research, a web-based intelligent collaborative system was developed to address this challenge based on intelligent computational argumentation. However, two important issues were not resolved in that system: priority of participants and self-conflicting arguments. In this paper, we develop two methods for incorporating priorities of participants into the computational argumentation network: 1) weighted summation and 2) re-assessment of strengths of arguments based on priority of owners of the argument using fuzzy logic inference. In addition, we develop a method for detection of self-conflicting arguments. Incorporation of priority of participants and detection of self-conflicting arguments have strengthen the capability of managing intelligent argumentation network for the web-based collaborative engineering design system developed in our previous research.

关键词： Collaboration Artificial intelligence Fuzzy sets Engines Input variables Robustness USA Councils

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Self-Healing Control with Multifunctional Gate Drive Circuits for Power Converters

Self-Healing Control with Multifunctional Gate Drive Circuit...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Peng Xiao Ganesh K. Venayagamoorthy Keith A. Corzine Robert Woodley Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla USA 21st Century Systems Inc. Fort Leonard Wood MO USA

Many commercial and military transport systems have fault diagnostic functions implemented to help protect the device when a severe fault occurs. However, most present systems do not contain prognostics capability which would allow operators to observe an unhealthy system component in its pre- fault condition. In industry applications, scheduled downtime can result in considerable cost avoidance. The next technology step is self-healing system components which observe not only potential problems, but can also take steps to continue operation under abnormal conditions - whether due to long-term normal wear-and-tear or sudden combat damage. In this paper, current and voltage information using the double-layer gate drive concept is fed to intelligent networks to identify the type of fault and its location. These intelligent networks are based on unsupervised and supervised learning networks (self-organizing maps and learning vector quantization networks respectively). The proposed concept allows the reconfiguration of the electric machinery system for continued normal operation of the machine. This paper presents an intelligent health monitoring and self-healing control strategy for a multi-phase multilevel motor drive under various types of faults.

关键词： Circuit faults Intelligent networks Power system protection Industry applications Job shop scheduling Costs Voltage Fault diagnosis Supervised learning Self organizing feature maps

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Differential Evolution Approach for Reactive Power Optimization of Nigerian Grid System

Differential Evolution Approach for Reactive Power Optimizat...

引用

IEEE General Meeting Power& Energy Society

作者： G. A. Bakare G. Krost G. K. Venayagamoorthy U. O. Aliyu Abubakar Tafawa Balewa University Bauchi Nigeria Electrical Power Systems Institute University of Duisburg-Essen Duisburg Germany Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

The goal of reactive power dispatch is to minimize the system losses and improve the system voltage profiles at all times. This is achieved by adjusting various generating units' excitation systems continuously, discrete tap positions of on-load tap changers of transformers as well as switching of correct doses of inductors or capacitors. This is a mixed integer non-linear optimization problem. In this paper, the differential evolution (DE), a novel evolutionary computation technique which was originally designed for continuous problems is applied to solve this problem. DE appears to ally qualities of established computational intelligence (CI) techniques with a more striking computational performance, thus suggesting the possibility of having the potential for on line applications in the control center; comparison work with other techniques is presently conducted. The developed tool was demonstrated on the Nigerian power system grid for three case scenarios preset on the power world simulator which was linked with DE for power flow calculation (fitness check of solutions). The results achieved revealed that DE procured a significant reduction of real power losses while simultaneously keeping the voltage profiles within the acceptable limits.

关键词： Reactive power Power system simulation On load tap changers Transformers Inductors Capacitors Evolutionary computation Computational intelligence Computational modeling Load flow

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Intelligent Local and Hierarchical Control of FACTS Devices

Intelligent Local and Hierarchical Control of FACTS Devices

引用

2007 IEEE Power engineering Society Conference and Exposition in Africa (IEEE PES PowerAfrica 2007), part 1

作者： Salman Mohagheghi Ganesh K. Venayagamoorthy Ronald G. Harley Intelligent Power Infrastructure Consortium Georgia Institute of Technology Atlanta GA USA Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA Department of Electrical and Computer Engineering University of Missouri-Rolla MO USA Emeritus University of Kwazulu-Natal South Africa

This paper presents an overview of the applications of intelligent control techniques on local and hierarchical control of FACTS devices. These control techniques are superior to the conventional linear/nonlinear control schemes in the sense that they are independent of any mathematical model of the power system to be controlled. In addition, they do not depend on the operating conditions and the configuration of the system to which the FACTS device is connected. A Static Compensator (STATCOM) is used as the example in order to compare the performances of the proposed intelligent controllers with those of their linear counterparts. Nevertheless, the ideas put forth in this paper are applicable to other shunt or series FACTS devices as well. Two different control schemes are evaluated: a fuzzy logic based local controller and a neuro-fuzzy hierarchical controller for a STATCOM in a multimachine power system.

关键词： Nonlinear control systems Control systems Power system control Power systems Automatic voltage control Intelligent control Mathematical model Power system modeling Control system synthesis STATCOM

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Dynamic Modeling of Wind Farms with Fixed-Speed Wind Turbine Generators

Dynamic Modeling of Wind Farms with Fixed-Speed Wind Turbine...

引用

2007 IEEE Power engineering Society General Meeting (PES 2007), vol.10

作者： Wei Qiao Ronald G. Harley Ganesh K. Venayagamoorthy Intelligent Power Infrastructure Consortium (IPIC) School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA University of KwaZulu-Natal Durban South Africa Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an important issue is to develop appropriate wind farm models to represent the dynamics of many individual WTGs. This paper presents various dynamic models, including a detailed model and three reduced-order equivalent models, of wind farms with fixed-speed WTGs. These models are developed and compared by simulation studies in the PSCAD/EMTDC environment under different wind velocity and fluctuation conditions as well as gird fault conditions. Concluding remarks are provided on how to choose an appropriate wind farm model for power system dynamic and transient studies.

关键词： Detailed model Equivalent model Fixed-speed wind turbine Squirrel-cage induction generator Wind farm

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