Loss Minimization Algorithm Research Articles

Online Efficiency Optimization of a Fuzzy-Logic-Controller-Based IPMSM Drive

This paper presents an online loss-minimization algorithm (LMA) for a fuzzy-logic-controller (FLC)-based interior permanent-magnet synchronous-motor (IPMSM) drive to yield high efficiency and high dynamic performance over a wide speed range. LMA is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency, the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector-control purpose, FLC is used as a speed controller, which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. In order to test the performance of the proposed drive in real time, the complete drive is experimentally implemented using DSP board DS1104 for a prototype laboratory 5-hp motor. The performance of the proposed loss-minimization-based FLC for IPMSM drive is tested in both simulation and experiment at different operating conditions. A performance comparison of the drive with and without the proposed LMA-based FLC is also provided. It is found from the results that the proposed LMA and FLC-based drive demonstrates higher efficiency and better dynamic responses over FLC-based IPMSM drive without LMA.

Network Reconfiguration Using PSAT for Loss Reduction in Distribution Systems

Network reconfiguration in distribution system is realized by changing the status of sectionalizing switches, and is usually done for the purpose of loss reduction. Loss reduction can result in substantial benefits for a utility. Other benefits from loss reduction include increased system capacity, and possible deferment or elimination of capital expenditures for system improvements and expansion. There is also improved voltage regulation as a result of reducing feeder voltage drop. Research work included by this paper focuses on using branch exchange method to minimize losses and solve the problems over different radial configuration. Solution's algorithm for loss minimization has been developed based on two stages of solution methodology. The first stage determines maximum loss-reduction loop by comparing the size of circles for every loop. In a distribution system, a l oop i s associated b y a t ie-line and hence there are several l oops i n t he s ystem. T o o btain t he maximum loss-reduction loop, size of modified zero loss-change circles are compared, and the loop within the largest circle is identified for maximum loss-reduction. The second stage determines the switching operation to be executed in that loop to reach a minimum loss network configuration by comparing the size of the loop circle for each branch-exchange. The smallest circle is to be identified for the best solution; the size of the loop circle is reduced when the losses are minimized. The performance of the proposed branch exchange method is tested on 16-bus distribution systems.

Efficiency Optimization of Induction Motor Drive Using Soft Computing Techniques

This paper presents a new approach that minimizes copper & iron losses and optimizes the efficiency of a variable speed Induction motor drive. This method is based on a simple induction motor field oriented control model includes iron losses uses only conventional IM parameters. In literature, Fuzzy logic and Genetic Algorithms have been used for efficiency optimization of induction motor drives. This paper proposes integration of Fuzzy model identification and PSO algorithm for loss minimization. An improvement of efficiency is obtained by adjusting the magnetizing current component with respect to the torque current component to give the minimum total copper and iron losses. The whole circuit is simulated using MATLAB 7.6. The proposed method is compared with other soft computing techniques. The results obtained by Fuzzy PSO shows better results compared with other approaches. General Terms Algorithms, Performance, Verification

Efficiency Optimization Control of IPMSM Drive using Multi AFLC

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning controller(AFLC). In order to optimize the efficiency the loss minimization algorithm is developed based on motor model and operating condition. The d-axis armature current is utilized to minimize the losses of the IPMSM in a closed loop vector control environment. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC. Also, this paper proposes speed control of IPMSM using AFLC1, current control of AFLC2 and AFLC3, and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled AFLC, the operating characteristics controlled by efficiency optimization control are examined in detail.

Development of a Nonlinear and Model-Based Online Loss Minimization Control of an IM Drive

Among the numerous loss minimization algorithms, a loss-model-based approach offers a fast response without torque pulsations. However, it requires the accurate loss model and the knowledge of the motor parameters. Therefore, a technical difficulty in deriving the loss-model-based controller (LMC) lies in the complexity of the full loss model and the online motor parameter adaptation. In an effort to overcome the drawbacks of LMC, this paper presents a new strategy for inverter-fed induction motors drives aiming for both high efficiency and high dynamic performance. A new LMC incorporating the effect of the leakage inductance and an adaptive-backstepping-based nonlinear controller are designed and combined with each other. Thus, online parameter adaptation of LMC can be obtained with no extra effort. The proposed control scheme is implemented in real time using digital signal processor board DS 1104. The simulation and experimental results demonstrate the effectiveness of the proposed scheme.

New Online Loss-Minimization-Based Control of an Induction Motor Drive

This paper presents a new loss-model-based controller for an induction motor drive. Among the many loss minimization algorithms (LMA) for an induction motor, a loss-model-based approach has the advantages of fast response and high accuracy. However, the performance of the loss-model controller (LMC) depends on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a tradeoff between accuracy and complexity. This paper presents a new LMC to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested LMC is simple, but leakage inductances are not omitted. The complete closed loop vector control of the proposed LMC-based IM drive is successfully implemented in real-time using digital signal processor board DS 1104 for a laboratory 1/3 hp motor. The effectiveness of the proposed scheme is demonstrated through simulation and experimental results.

A New Optimal Routing Algorithm for Loss Minimization and Voltage Stability Improvement in Radial Power Systems

This paper presents an optimal routing algorithm (ORA) for minimizing power loss and at the same time maximizing the voltage stability in radial power systems. In the proposed ORA, a voltage stability index (VSI) for real-time assessment is introduced based on the conventional critical transmission path framework. In addition, the algorithm can automatically detect the critical transmission paths that will result in voltage collapse when additional real or reactive loads are added. To implement effective ORA, an improved branch exchange (IBE) method has been developed based on a loss calculation index and tie-branch power flows that is suited for real-time applications. The proposed algorithm has been tested in the IEEE 32- and 69-bus systems as well as in a large-scale Korea Electric Power Company 148-bus system to show its effectiveness and efficiency

Energy model based loss‐minimized speed control of induction motor with a full‐order observer

In this paper, a loss-minimization algorithm is developed to achieve maximum efficiency in terms of slip frequency. The optimal value of slip frequency can be obtained by minimizing all controllable losses of the induction motor (IM). The ratio of magnetic energy converted to torque (WT) to magnetic energy stored in the rotating field (Wq) is defined in terms of slip frequency to obtain an error function that is used to design a controller to achieve the desired speed. Since the energy model of the IM can be expressed by the multi-input and multi-output (MIMO) system, an MIMO optimal regulator is proposed to achieve the desired speed with maximum efficiency. To design an optimal regulator, it is necessary to measure all state quantities. But WT and Wq cannot be measured directly. Therefore, a full-order observer is proposed to estimate these state quantities. The gains of the observer system are calculated by using the pole placement technique. Consequently, the observer system becomes stable. The performance of the proposed controller and observer system are verified by using simulation. With regard to the simulation results, it can be concluded that the desired speed can be achieved by using the proposed controller and the unknown state quantities can be estimated properly by using the proposed observer system. © 2006 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Efficiency Enhancement of Permanent-Magnet Synchronous Motor Drives by Online Loss Minimization Approaches

In this paper, a new loss minimization algorithm for inverter-fed permanent-magnet synchronous motors (PMSMs), which allows for the reduction of the power losses of the electric drive without penalty on its dynamic performance, is analyzed, experimentally realized, and validated. In particular, after a brief recounting of two loss minimization strategies, namely, the search control and the control, both a new modified dynamic model of the PMSM (which takes into account the iron losses) and an innovative loss-model strategy are presented. Experimental tests on a specific PMSM drive employing the proposed loss minimization algorithm have been performed, aiming to validate the actual implementation. The main results of these tests confirm that the dynamic performance of the drive is maintained, and in small motors enhancement up to 3.5% of the efficiency can be reached in comparison with the PMSM drive equipped with a more traditional strategy.

An efficient simulated annealing algorithm for network reconfiguration in large-scale distribution systems

This paper presents an efficient algorithm for loss minimization by using an automatic switching operation in large-scale distribution systems. Simulated annealing is particularly well suited for a large combinatorial optimization problem since it can avoid local minima by accepting improvements in cost. However, it often requires meaningful cooling schedule and a special strategy, which makes use of the property of distribution systems in finding the optimal solution. In this paper, we augment the cost function with the operation condition of distribution systems, improve the perturbation mechanism with system topology, and utilize the polynomial-time cooling schedule, which is based on the statistical calculation during the search. The validity and effectiveness of the proposed methodology is demonstrated in the Korea Electric Power Corporation's distribution system.

An Efficient Simulated Annealing Algorithm for Network Reconfiguration in Large-Scale Distribution Systems

This paper presents an efficient algorithm for loss minimization by using an automatic switching operation in large-scale distribution systems. Simulated annealing is particularly well suited for a large combinatorial optimization problem since it can avoid local minima by accepting improvements in cost. However, it often requires meaningful cooling schedule and a special strategy, which makes use of the property of distribution systems in finding the optimal solution. In this paper, we augment the cost function with the operation condition of distribution systems, improve the perturbation mechanism with system topology, and utilize the polynomial-time cooling schedule, which is based on the statistical calculation during the search. The validity and effectiveness of the proposed methodology is demonstrated in the Korea Electric Power Corporation's distribution system.

LOSS REDUCTION IN DISTRIBUTION NETWORKS USING NEW NETWORK RECONFIGURATION ALGORITHM

ABSTRACT Network reconfiguration is an operation task, and consists in the determination of the switching operations such to reach the minimum loss conditions of the distribution networks. In this paper, a general formulation of the network reconfiguration for loss minimization is given for the optimization of distribution loss reduction and a solution approach is presented. The solution employs a search over different radial configurations, created by considering branch exchange type switches. The solution algorithm for loss minimization has been developed based on the two stage solution methodology. The first stage of this solution algorithm finds a loop which gives the maximum loss reduction in the network. For this purpose a simple-to-use formula, called loop loss reduction formula, has been developed. To find a branch exchange, which results in the maximum loss reduction in the loop, the second stage applies a proposed technique called distance-center technique. Therefore, the solution algorithm of the proposed method can identify the most effective branch exchange operations for loss reduction, with a minimum computational efforts. The solution algorithm of the proposed method has been tested, with very promising results, on a 69-bus radial distribution system. Test results prove that, via proposed network reconfiguration for loss minimization, real power loss is reduced significantly, and that the voltage profile of the network is considerably improved. As compared to the established methods the proposed method eliminates the need to run numerous load flows.