Hardware Implementation of an AIS-Based Optimal Excitation Controller for an Electric Ship

The operation of high energy loads on Navy\u27s future electric ships, such as directed energy weapons, will cause disturbances in the main bus voltage and impact the operation of the rest of the power system when the pulsed loads are directly powered from the main dc bus. This paper describes an online design and laboratory hardware implementation of an optimal excitation controller using an artificial immune system (AIS) based algorithm. The AIS algorithm, a clonal selection algorithm (CSA), is used to minimize the effects of pulsed loads by improved excitation control and thus, reduce the requirement on energy storage device capacity. The CSA is implemented on the MSK2812 DSP hardware platform. A comparison of CSA and the particle swarm optimization (PSO) algorithm is presented. Hardware measurement results show that the CSA optimized excitation controller provides effective control of a generator\u27s terminal voltage during pulsed loads, restoring and stabilizing it quickly

Optimal excitation controllers, and location and sizing of energy storage for all-electric ship power system

The Navy\u27s future all-electric ship power system is based on the integrated power system (IPS) architecture consisting of power generation, propulsion systems, hydrodynamics, and DC zonal electric distribution system (DC-ZEDS). To improve the power quality, optimal excitation systems, and optimal location and sizing of energy storage modules (ESMs) are studied. In this dissertation, clonal selection algorithm (CSA) based controller design is firstly introduced. CSA based controller design shows better exploitation ability with relatively long search time when compared to a particle swarm optimization (PSO) based design. Furthermore, \u27optimal\u27 small population PSO (SPPSO) based excitation controller is introduced. Parameter sensitivity analysis shows that the parameters of SPPSO for regeneration can be fined tuned to achieve fast optimal controller design, and thus exploiting SPPSO features for problem of particles get trapped in local minima and long search time. Furthermore, artificial immune system based concepts are used to develop adaptive and coordinated excitation controllers for generators on ship IPS. The computational approaches for excitation controller designs have been implemented on digital signal processors interfaced to an actual laboratory synchronous machine, and to multimachine electric ship power systems simulated on a real-time digital simulator. Finally, an approach to evaluate ESM location and sizing is proposed using three metrics: quality of service, survivability and cost. Multiple objective particle swarm optimization (MOPSO) is used to optimize these metrics and provide Pareto fronts for optimal ESM location and sizing --Abstract, page iv

Real Time Implementation of an Artificial Immune System Based Controller for a DSTATCOM in an Electric Ship Power System

A new adaptive control strategy based on artificial immune system (AIS) for a DSTATCOM in an electric ship power system is presented in this paper. DSTATCOM is a shunt compensation device, which can be used to improve the power quality during the pulse power requirements in a naval shipboard system. The role of DSTATCOM controller is very important to meet this objective. In this paper, the DSTATCOM controller parameters are first tuned by particle swarm optimization (PSO) technique, so that it can provide innate immunity to common system disturbances. Then, these optimum parameters are modified online by an artificial immune system (AIS), which provides adaptive immunity to unusual system disturbances. To evaluate the performance of the proposed control strategy, a simplified model of the ship system consisting of a 45 MVA main generator, a 5 MVA auxiliary generator and a 36 MW propulsion motor is simulated in a real-time environment. The effectiveness of the PSO and AIS based adaptive controller is demonstrated on a real time digital simulator based test system for pulsed loads of different magnitudes and durations

A transition from manual to Intelligent Automated power system operation -A Indicative Review

This paper reviews the transition of the power system operation from the traditional manual mode of power system operations to the level where automation using Internet of Things (IOT) and intelligence using Artificial Intelligence (AI) is implemented. To make the review paper brief only indicative papers are chosen to cover multiple power system operation based implementation. Care is taken there is lesser repeatation of similar technology or application be reviewed. The indicative review is to take only a representative literature to bypass scrutinizing multiple literatures with similar objectives and methods. A brief review of the slow transition from the traditional to the intelligent automated way of carrying out power system operations like the energy audit, load forecasting, fault detection, power quality control, smart grid technology, islanding detection, energy management etc is discussed .The Mechanical Engineering Perspective on the basis of applications would be noticed in the paper although the energy management and power delivery concepts are electrical

Wide Area Signals Based Damping Controllers for Multimachine Power Systems

Nowadays, electric power systems are stressed and pushed toward their stability margins due to increasing load demand and growing penetration levels of renewable energy sources such as wind and solar power. Due to insufficient damping in power systems, oscillations are likely to arise during transient and dynamic conditions. To avoid undesirable power system states such as tripping of transmission lines, generation sources, and loads, eventually leading to cascaded outages and blackouts, intelligent coordinated control of a power system and its elements, from a global and local perspective, is needed. The research performed in this dissertation is focused on intelligent analysis and coordinated control of a power system to damp oscillations and improve its stability. Wide area signals based coordinated control of power systems with and without a wind farm and energy storage systems is investigated. A data-driven method for power system identification is developed to obtain system matrices that can aid in the design of local and wide area signals based power system stabilizers. Modal analysis is performed to characterize oscillation modes using data-driven models. Data-driven models are used to identify the most appropriate wide-area signals to utilize as inputs to damping controller(s) and generator(s) to receive supplementary control. Virtual Generators (VGs) are developed using the phenomena of generator coherency to effectively and efficiently control power system oscillations. VG based Power System Stabilizers (VG-PSSs) are proposed for optimal damping of power system oscillations. Herein, speed deviation of VGs is used to generate a supplementary coordinated control signal for an identified generator(s) of maximum controllability. The parameters of a VG-PSS(s) are heuristically tuned to provide maximum system damping. To overcome fallouts and switching in coherent generator groups during transients, an adaptive inter-area oscillation damping controller is developed using the concept of artificial immune systems - innate and adaptive immunity. With increasing levels of electric vehicles (EVs) on the road, the potential of SmartParks (a large number of EVs in parking lots) for improving power system stability is investigated. Intelligent multi-functional control of SmartParks using fuzzy logic based controllers are investigated for damping power system oscillations, regulating transmission line power flows and bus voltages. In summary, a number of approaches and suggestions for improving modern power system stability have been presented in this dissertation

Large Space Antenna Systems Technology, 1984

Mission applications for large space antenna systems; large space antenna structural systems; materials and structures technology; structural dynamics and control technology, electromagnetics technology, large space antenna systems and the Space Station; and flight test and evaluation were examined

Simulasi Sistem Eksitasi Untuk Kondensator Sinkron Pada Pembangkit Listrik Tenaga Angin

Tejo Sukmadi, in paper a model of wind energy power generation excitation system will be simulated. The focuse was on the modelling and parameters optimization of the DC1A type excitation systems for synchronous condenser as voltage regulation on the power plant. Excitation system optimization is made by using genetic algorithms method. The parameters optimization should have the optimal combination and the voltage regulation of wind energy power plants model find the best vale when there is a change in the wind speed. The simulation and analysis found that systems with excitation system parameterized combination of genetic algorithms experiment using crossovers opportunities 0.6 and mutations opportunities 0.032, which Ka = 297.2350, Ke = 0.6162, Kf = 0.01, Ta = 0.01, Te = 0.01 and Tf = 0.6278 is the best combination of excitation parameters obtained. By generating the 115.6604 ITAE value, over shoot 1,54%, steady state 0,44 s, the smallest voltage value after wind speed change is 0.9957 pu and the largest voltage value after wind speed change is 1.0025 pu

Optimum Distribution System Architectures for Efficient Operation of Hybrid AC/DC Power Systems Involving Energy Storage and Pulsed Loads

After more than a century of the ultimate dominance of AC in distribution systems, DC distribution is being re-considered. However, the advantages of AC systems cannot be omitted. This is mainly due to the cheap and efficient means of generation provided by the synchronous AC machines and voltage stepping up/down allowed by the AC transformers. As an intermediate solution, hybrid AC/DC distribution systems or microgrids are proposed. This hybridization of distribution systems, incorporation of heterogeneous mix of energy sources, and introducing Pulsed Power Loads (PPL) together add more complications and challenges to the design problem of distribution systems. In this dissertation, a comprehensive multi-objective optimization approach is presented to determine the optimal design of the AC/DC distribution system architecture. The mathematical formulation of a multi-objective optimal power flow problem based on the sequential power flow method and the Pareto concept is developed and discussed. The outcome of this approach is to answer the following questions: 1) the optimal size and location of energy storage (ES) in the AC/DC distribution system, 2) optimal location of the PPLs, 3) optimal point of common coupling (PCC) between the AC and DC sides of the network, and 4) optimal network connectivity. These parameters are to be optimized to design a distribution architecture that supplies the PPLs, while fulfilling the safe operation constraints and the related standard limitations. The optimization problem is NP-hard, mixed integer and combinatorial with nonlinear constraints. Four objectives are involved in the problem: minimizing the voltage deviation (ΔV), minimizing frequency deviation (Δf), minimizing the active power losses in the distribution system and minimizing the energy storage weight. The last objective is considered in the context of ship power systems, where the equipment’s weight and size are restricted. The utilization of Hybrid Energy Storage Systems (HESS) in PPL applications is investigated. The design, hardware implementation and performance evaluation of an advanced – low cost Modular Energy Storage regulator (MESR) to efficiently integrate ES to the DC bus are depicted. MESR provides a set of unique features: 1) It is capable of controlling each individual unit within a series/parallel array (i.e. each single unit can be treated, controlled and monitored separately from the others), 2) It is able to charge some units within an ES array while other units continue to serve the load, 3) Balance the SoC without the need for power electronic converters, and 4) It is able to electrically disconnect a unit and allow the operator to perform the required maintenance or replacement without affecting the performance of the whole array. A low speed flywheel Energy Storage System (FESS) is designed and implemented to be used as an energy reservoir in PPL applications. The system was based on a separately excited DC machine and a bi-directional Buck-Boost converter as the driver to control the charging/discharging of the flywheel. Stable control loops were designed to charge the FESS off the pulse and discharge on the pulse. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed

Aeronautical Engineering: A continuing bibliography, supplement 116

This bibliography lists 550 reports, articles, and other documents introduced into the NASA scientific and technical information system in November 1979

Coevolutionary particle swarm optimization using AIS and its application in multiparameter estimation of PMSM

In this paper, a coevolutionary particle-swarm-optimization (PSO) algorithm associating with the artificial immune principle is proposed. In the proposed algorithm, the whole population is divided into two kinds of subpopulations consisting of one elite subpopulation and several normal subpopulations. The best individual of each normal subpopulation will be memorized into the elite subpopulation during the evolution process. A hybrid method, which creates new individuals by using three different operators, is presented to ensure the diversity of all the subpopulations. Furthermore, a simple adaptive wavelet learning operator is utilized for accelerating the convergence speed of the pbest particles. The improved immune-clonal-selection operator is employed for optimizing the elite subpopulation, while the migration scheme is employed for the information exchange between elite subpopulation and normal subpopulations. The performance of the proposed algorithm is verified by testing on a suite of standard benchmark functions, which shows faster convergence and global search ability. Its performance is further evaluated by its application to multiparameter estimation of permanent-magnet synchronous machines, which shows that its performance significantly outperforms existing PSOs. The proposed algorithm can estimate the machine dq-axis inductances, stator winding resistance, and rotor flux linkage simultaneously. © 2013 IEEE