Evaluation of FIT impacts on market clearing price in the restructured power market

The development of intermittent wind firms in the restructured power market has required the entry of several creative approaches in evaluating the market clearing price in the restructured power market. This study proposes a model to investigate the seasonal market clearing price by considering the hybrid wind-heat firm. In this article, fixed and variable Feed in Tariff (FIT) is considered and compared as two regulatory policies for wind generation units. Wind resources modeled by using the scenario based technique. Furthermore, strategic behavior of other investors is considered based on the game theory concepts. The Cournot game concept has been applied to determine the Nash equilibrium for each state of stochastic programming. This model has been implemented on a test system. The effects of the fixed and variable FIT and the variations of electricity price cap have been investigated on the profit of each firm in the restructured power market. Moreover, the market clearing price offered for each season and load level

Analysis and design of a high efficiency bidirectional DC-DC converter for battery and ultracapacitor applications

This paper presents a high efficiency non-isolated bidirectional converter which can be employed as an interface circuit between ultracapacitors or batteries and DC bus voltage. All semiconductor devices in the proposed converter are soft switched while the control circuit remains PWM. So, the energy conversion through the converter is highly efficient. The proposed converter acts as a zero-voltage transition (ZVT) buck to charge an ultracapacitor or battery and acts as a ZVT boost to discharge an ultracapacitor or battery. The performance of the proposed converter with respect to abrupt load and operating mode change is shown through computer simulation results. The results confirm the aforementioned advantages and features of the proposed converter

Review of fault location methods for distribution power system

For the past fifty years, electric power systems have rapidly grown. This has resulted in a large increase of the number of lines in op eration an d their total length. These lines experience faults which are caused by storms, lightning, snow, freezing rain, insulation breakdown and short circuits caused by birds and other external objects. In most cases, electrical faults manifest in mechanical damage, which must be repaired before returning the line to service. The restoration can be expedited if the location of the fault is either known or can be estimated with reasonable accuracy. Speedy an d precise fault location plays an important role in accelerating system restoration, reducing outage time and significantly improving system reliability. This paper provides a comprehensive review of the conceptual aspects as well as recent algorithmic developments for fault location on distribution system. Several fundamentally different approaches are discussed in the paper together with the factors affecting the assumptions of the underlying concepts and the various criteria used in the different approaches are reviewed

Comparative analysis of probabilistic neural network, radial basis function, and feed-forward neural network for fault classification in power distribution systems

This article presents a classification methodology based on probabilistic neural networks. To automatically select the training data and obtain the performance evaluation results, the “K-fold” cross-validation method is used. Then, the probabilistic neural network is compared with the feed-forward neural network and the radial basis function network. The goal is to propose a classifier that is capable of recognizing 11 classes of three-phase distribution system faults to solve the complex fault (three-phase short-circuit) classification problem for reducing the multiple-estimation problem to estimate the fault location in radial distribution systems. The data for the fault classifier is produced by DigSilent Power Factory, Integrated Power System Analysis Software on an IEEE 13-node test feeder. A selection of features or descriptors obtained from voltages and currents measured in the substation are analyzed and used as input of the probabilistic neural network classifier. It is shown that the probabilistic neural network approach can provide a fast and precise operation for various faults. The simulation results also show that the proposed model can successfully be used as an effective tool for solving complicated classification problems

A proposed genetic algorithm to optimize service restoration in electrical networks with respect to the probability of transformers failure

Power system reliability, stability and efficiency are the most important issues to insure continuously feeding of customers. However in process of time, system will be age and the probability of failures will increase and faults inevitably will occur. When a fault occurs, the first reaction is isolation of the faulty area, then with aid of software and/or skillful person quick restoration is essentially needed. To minimize the out-of-service area and activity time of restoration many methods are suggested depend on objectives and constraints of restoration strategy. In many researches a Genetic Algorithm is employed as a powerful tool to solve this multi-objective, multi-constraint optimization problem. Out-of-service area minimization, reduce the number of switching operation and minimizing the minimum electrical power loss in restored system are the prior objectives of restoration plan. In this paper, as transformers are the most expensive and more effective equipments in the electrical network, failure probability increasing is introduced as a new constraint in genetic algorithm by authors. Expected results of this new algorithm should lead to a new plan of restoration in permissible ranges of transformer loading in respect of their age, previous experienced faults and condition monitoring

Optimal penalty method in distribution service restoration using genetic algorithm

As an efficient scheme for service restoration in distribution systems has a vital role in improving reliability of the system and also satisfactory of customers, significant efforts assigned in solving the problem. The major challenge is to reduce computation burden while covering all the possible answers in reasonable time and effort. Furthermore, restoration is a multi-objective, multi-constraint optimization problem. The considered restoration objective functions in this study include the minimization of outage area, minimizing of power loss and minimizing of number of switching whilst considering the technical constraints. This study presents a new approach of supply restoration service using the Genetic Algorithm (GA). A new hybrid Genetic Algorithm is proposed for reducing the search space. The proposed technique is implemented to improve the penalty strategy to enhance the performance of algorithm and reduce the convergence iteration. The effectiveness of the proposed method is demonstrated by testing on a 33-bus test system. Comparisons show the improvements in reducing of number of iteration after restoration. Findings through comparisons are shown that the proposed method will be able to do full restoration and energize all loads

Effects of Temperature and Cooling Modes on Yield, Purity and Particle Size Distribution of Dihydroxystearic Acid Crystals

Abstract An investigation into the effects of temperature and two different cooling modes (i.e. controlled and natural) on the solvent crystallization of dihydroxystearic acid (DHSA) was carried out. The effects of operating temperature and the time on the crystal size distribution (CSD), purity and yield of crystallized DHSA were studied. The crystal purity and average crystal particle size increased with temperature, but the crystal yield decreased as the temperature increased. The controlled cooling crystallization process initially resulted in better crystal properties compared to natural cooling crystallization. However, towards the end of the crystallization process, only marginal differences in terms of crystal properties were observed. Effects of Temperature and Cooling Modes on Yield, Purity and Particle Size Distribution of Dihydroxystearic Acid Crystals 47

A fully soft switched two quadrant bidirectional soft switching converter for ultra capacitor interface circuits

This paper describes a two quadrant bidirectional soft switching converter for ultra capacitor interface circuits. The total efficiency of the energy storage system in terms of size and cost can be increased by a combination of batteries and ultra capacitors. The required system energy is provided by a battery, while an ultra capacitor is used at high load power pulses. The ultra capacitor voltage changes during charge and discharge modes, therefore an interface circuit is required between the ultra capacitor and the battery. This interface circuit must have good efficiency while providing bidirectional power conversion to capture energy from regenerative braking, downhill driving and the protecting ultra capacitor from immediate discharge. In this paper a fully soft switched two quadrant bidirectional soft switching converter for ultra capacitor interface circuits is introduced and the elements of the converter are reduced considerably. In this paper, zero voltage transient (ZVT) and zero current transient (ZCT) techniques are applied to increase efficiency. The proposed converter acts as a ZCT Buck to charge the ultra capacitor. On the other hand, it acts as a ZVT Boost to discharge the ultra capacitor. A laboratory prototype converter is designed and realized for hybrid vehicle applications. The experimental results presented confirm the theoretical and simulation results

Analysis and design of a fully soft-switched buck-boost converter for ultra-capacitor and battery combined interface circuit

A fully soft switched bidirectional converter to interface an ultra capacitor (UC) and a battery is proposed. The proposed converter acts as a Buck ZCT to charge the UC and acts as a Boost ZVT to discharge the UC. The ZVT and ZCT techniques guarantees soft switching condition for all power switches. The proposed converter has high efficiency (above 95%), requires fewer components and has small footprint. The analysis of the switching technique is validated by simulation. In addition, a 100W experimental converter is constructed. The results from simulation and experiment are in good agreement with each other