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Comparison of Two Optimal Control Strategies for a Grid Independent Photovoltaic System

Comparison of Two Optimal Control Strategies for a Grid Inde...

引用

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

作者： Richard L. Welch Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

This paper presents two optimal control strategies for a grid independent photovoltaic system consisting of a PV collector array, a storage battery, and loads (critical and non-critical loads). The first strategy is based on action dependent heuristic dynamic programming (ADHDP), a model-free adaptive critic design (ACD) technique which optimizes the control performance based on a utility function. ADHDP critic network is used in a PV system simulation study to train an action neural network (optimal neurocontroller) to provide optimal control for varying PV system output energy and loadings. The second optimal control strategy is based on a fuzzy logic controller with its membership functions optimized using the particle swarm optimization. The emphasis of the optimal controllers is primarily to supply the critical base load at all times, thus requiring sufficient stored energy during times of less or no solar insulation. Simulation results are presented to compare the performance of the proposed optimal controllers with the conventional priority control scheme. Results show that the ADHDP based controller performs better than the optimized fuzzy controller, and the optimized fuzzy controller performs better than the standard PV-priority controller

关键词： Optimal control Photovoltaic systems Fuzzy control Batteries Dynamic programming Programmable control Adaptive control Design optimization Neural networks Neurocontrollers

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real-time Implementation of a Dual Function Neuron based Wide Area SVC Damping Controller

Real-Time Implementation of a Dual Function Neuron based Wid...

引用

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

作者： Sandhya R. Jetti Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

The use of wide area measurements for power system stabilization is recently given a lot of attention by researchers and the power industry to avoid cascading failures and blackouts such as the August 2003. This paper presents the design of a nonlinear external damping controller based on wide area measurements as inputs to a dual function neuron (DFN). This DFN controller is specifically designed to enhance the damping characteristics of a power system considering the nonlinearity in the system. The major advantage of the DFN controller is that it is simple in structure with less development time and hardware requirements for real-time implementation. The DFN controller is implemented on a digital signal processor and its performance is evaluated on the IEEE 12 bus FACTS benchmark power system implemented on a real time platform - real time digital simulator (RTDS). Experimental results show that the DFN controller provides better damping than a conventional linear controller

关键词： Neurons Static VAr compensators Damping Wide area measurements Power system measurements Power system simulation real time systems Power industry Power system faults Power system protection

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Bio-inspired Algorithms for the Design of Multiple Optimal Power System Stabilizers: SPPSO and BFA

Bio-inspired Algorithms for the Design of Multiple Optimal P...

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

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

Power system stabilizers (PSSs) provide stabilizing control signals to excitation systems to damp out inter-area and intra-area oscillations. The PSS must be optimally tuned to accommodate the variations in the system dynamics. Designing multiple optimal PSSs is a challenging task for researchers. This paper presents the comparison between two bio-inspired algorithms: a small population based particle swarm optimization (SPPSO) and the bacterial foraging algorithm (BFA) for the simultaneous tuning of a number of PSSs in a multi-machine power system. The cost function to be optimized by both algorithms takes into consideration the time domain transient responses. The effectiveness of the algorithms is evaluated and compared for damping the system oscillations during small and large disturbances. The robustness of the optimized PSSs in terms of damping is shown using the matrix pencil analysis

关键词： Algorithm design and analysis Power systems Power system dynamics Power system transients Damping Power system control Control systems Particle swarm optimization Microorganisms Tuning

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Assessment of Distributed Generation Based on Voltage Profile Improvement and Line Loss Reduction

Assessment of Distributed Generation Based on Voltage Profil...

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IEEE PES Transmission and Distribution Conference and Exposition

作者： Iyer Ray Ramakumar Engineering Energy Laboratory Department of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA Real-Time Power and Intelligent Systems Laboratory Electrical and Computer Engineering department University of Missouri Rolla MO USA

This paper proposes a combined voltage profile improvement and line loss reduction index (VILRI) to assess the impact of distributed generation (DG) on a distribution system. Two different voltage profile improvement indices are employed to arrive at two alternatives for the combined index. Results of simulation studies carried out on a 33-bus radial system in MATLAB are presented and discussed. Primal-dual interior point (PDIP) method is used to identify the optimal locations for DG units based on the proposed index

关键词： Distributed control Voltage Power generation Reactive power Student members Power supplies Stability Renewable energy resources Fuel cells Wind energy generation

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Empirical Study of an Unconstrained Modified Particle Swarm Optimization

Empirical Study of an Unconstrained Modified Particle Swarm ...

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Congress on Evolutionary Computation

作者： P.W. Moore G.K. Venayagamoorthy The Real-Time Power and Intelligent Systems (RTPIS) Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

In this paper, an unconstrained modified particle swarm optimization (UMPSO) algorithm is introduced and studied empirically. Four well known benchmark functions, with asymmetric initial position values, are used as testing functions for the UMPSO algorithm. The UMPSO is a variation of the canonical PSO in which the velocity and position is unconstrained, an additional strategic component is added, and the social component term has been modified. The strategy component is used instead of varying parameters or mutation to enhance diversity in the swarm during the search. The UMPSO algorithm is then compared to results obtained from the constrained canonical PSO (CPSO) and the unconstrained canonical PSO (UPSO). The results show that UMPSO algorithm with no maximum velocity and position, and no minimum velocity and position value that performs better than the CPSO and the UPSO for the Sphere, Rosenbrock, Rastrigrin, and Griewank benchmark functions.

关键词： Particle swarm optimization Birds Marine animals Genetic mutations Benchmark testing Cultural differences Educational institutions Pulse width modulation Equations Genetic algorithms

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Optimal STATCOM Sizing and Placement Using Particle Swarn Optimization

Optimal STATCOM Sizing and Placement Using Particle Swarn Op...

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IEEE/PES Transmission and Distribution Conference and Exposition: Latin America

作者： Y. del Valle J. C. Hernandez G. K. Venayagamoorthy R. G. Harley Department of Electrical and Computer engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory University of Missouri-Rolla MO USA

Heuristic approaches are traditionally applied to find the size and location of flexible AC transmission systems (FACTS) devices in a small power system. Nevertheless, more sophisticated methods are required for placing them in a large power network. Recently, the particle swarm optimization (PSO) technique has been applied to solve power engineering optimization problems giving better results than classical methods. This paper shows the application of PSO for optimal sizing and allocation of a static compensator (STATCOM) in a power system. A 45 bus system (part of the Brazilian power network) is used as an example to illustrate the technique. Results show that the PSO is able to find the best solution with statistical significance and a high degree of convergence. A detailed description of the method, results and conclusions are also presented

关键词： Automatic voltage control Power systems Particle swarm optimization Flexible AC transmission systems Power system simulation Evolutionary computation Power engineering Power generation STATCOM Optimization methods

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Density Estimation Using a Generalized Neuron

Density Estimation Using a Generalized Neuron

引用

International Conference on Information Fusion

作者： Raveesh Kiran Ganesh K. Venayagamoorthy Marimuthu Palaniswami Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA Department of Electrical and Electronic Engineering University of Melbourne VIC Australia

ISBN: (纸本)1424409535

Neural networks have been shown to be useful tools for density estimation. However, the training of neural network structures is time consuming and requires fast processors for practical applications. A new method with a generalized neuron (GN) for density estimation is presented in this paper. The GN is trained with the particle swarm optimization algorithm which is known to have fast convergence than the standard backpropagation algorithm. Results are presented to show that the GN can estimate the density functions for distribution functions with different means and variances. This density estimation method can also be applied to the multi-sensor data fusion process

关键词： Neurons Neural networks Density functional theory Particle swarm optimization Backpropagation algorithms Probability distribution Function approximation Convergence Distribution functions Neural network hardware

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Adaptive critic designs based coupled neurocontrollers for a static compensator

Adaptive critic designs based coupled neurocontrollers for a...

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IEEE International Conference on computer-Aided Design

作者： Salman Mohagheghi Ganesh K. Venayagamoorthy Ronald G. Harley 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 MO USA

A novel nonlinear optimal neurocontroller for a static compensator (STATCOM) connected to a power system, using artificial neural networks, is presented in this paper. The heuristic dynamic programming (HDP) method, a member of the adaptive critic designs (ACD) family, is used for the design of the STATCOM neurocontroller. The proposed controller is a nonlinear optimal controller that provides coupled control for the line voltage and the dc link voltage regulation loops of the STATCOM. An action dependent approach is used, in which the controller is independent of a model of the network. Moreover, a proportional-integrator approach allows the neurocontroller to deal with the actual signals rather than the deviations. Simulation results are provided to show that the proposed ACD based neurocontroller is more effective in controlling the STATCOM compared to finely tuned conventional PI controllers.

关键词： Neurocontrollers STATCOM Automatic voltage control Voltage control Optimal control Power system dynamics Power systems Artificial neural networks Dynamic programming Couplings

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Intelligent optimal control of excitation and turbine systems in power networks

Intelligent optimal control of excitation and turbine system...

引用

IEEE General Meeting Power& Energy Society

作者： G.K. Venayagamoorthy R.G. Harley Real-Time Power and Intelligent Systems (RTPIS) Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of excitation and turbine systems. The crucial factors affecting the modern power systems today is voltage control and system stabilization during small and large disturbances. Simulation studies and real-time laboratory experimental studies carried out are described and the results show the successful control of the power system excitation and turbine systems with adaptive and optimal neurocontrol approaches. Performances of the neurocontrollers are compared with the conventional PI controllers for damping under different operating conditions for small and large disturbances

关键词： Intelligent control Intelligent networks Optimal control Turbines Power system simulation Power system control Power system modeling Power systems Power grids Voltage control

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real-time Implementation of a STATCOM on a Wind Farm Equipped with Doubly Fed Induction Generators

Real-Time Implementation of a STATCOM on a Wind Farm Equippe...

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

作者： Wei Qiao Ganesh K. Venayagamoorthy Ronald G. Harley 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

Voltage stability is a key issue to achieve the uninterrupted operation of wind farms equipped with doubly fed induction generators (DFIGs) during grid faults. A static synchronous compensator (STATCOM) is applied to a power network which includes a DFIG driven by a wind turbine, for steady state voltage regulation and transient voltage stability support. The control schemes of the DFIG rotor-side converter, grid-side converter and the STATCOM are suitably designed and coordinated. The system is implemented in real-time on a real-time Digital Simulator (RTDSreg). Results show that the STATCOM improves the transient voltage stability and therefore helps the wind turbine generator system to remain in service during grid faults

关键词： Automatic voltage control Wind farms Induction generators Stability Wind turbines real time systems Steady-state Voltage control Rotors Mesh generation

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