A Cascade Multilevel Z-Source Inverter for Photovoltaic System

This paper describes a multilevel Z-source inverter for solar photovoltaic applications. The conventional power conversion topology performs either buck or boost the input voltage for non linear load depending upon duty ratio and modulation index in a multiple stage conversion with the help of impedance source passive network (L and C), which is usually known as Z-Source, which couples the n level source with input to the power source and increase the power efficiency. The multilevel z network capabilities of inverter are operated in the shoot through state of duty cycle and it acts as a filter to reduces the level of harmonics, stabilize power factor and to increase the output AC voltage range of inverter. To overcome further harmonics, multilevel level operation z source inverter compensates the fundamental level of harmonic in renewable. Proposed work as a whole involves the simulation part to design multilevel inverter. The output of the simulation is obtained by Simulink model using MATLAB.

Cost Analysis of Hybrid Restructuration for Distribution System to Improve Voltage and Minimize Losses

<p>Current situation in Iraq had led to extensive blackouts which needs an expansion in generation capacity. On the other hand the government has reduced the budget allocated for energy resource development and it seems this situation will sustain for the coming years. So the fulfilment of the load demand is the biggest challenge for the ministry of electricity with limited budget. In this paper the authors have proposed a method to reduce the power losses and therefore improve the voltage profile for low voltage (LV) distribution system that results in reduction of blackouts. The method involves the repositioning of the distribution transformer (DTR) from the existing location and the replacement of the overhead conductor cross section area for an existing low voltage distribution system (LVDS). This method has been applied to a 20-node low voltage radial distribution network in the general directorate of north distribution electricity (GDNDE), Iraq, where voltage profile and losses are unsatisfactory. Results demonstrate the effectiveness of the proposed method also in terms of the economic feasibility. It is observed that the system average voltage profile is improved by 15%, tail end voltage enhanced by 19.7% and losses are reduced by 78% for existing the LVDS.</p>

Optimal Coordination of Overcurrent and Distance Relays Using Cuckoo Optimization Algorithm

The duty of protective systems is the timely detection of fault and removing it from the power network. The accuracy of the results and reducing the execution time of the optimizing algorithm are two crucial elements in selecting optimizing algorithms in protective functions. The most important protective elements that are used in power networks are distance and overcurrent relays. In this article, a new algorithm is presented to solve the optimization problem of coordination of overcurrent and distance relays by using Cuckoo Optimization Algorithm which considers the non-linear model overcurrent relays at all stages of setting. The proposed method is tested on a standard 8-bus power system network. Also the results obtained have been compared with other evolutionary algorithms. The results show that the proposed approach can be provide more effective and practical solutions to minimize the time function of the relays and achieving optimal coordination in comparison with previous studies on optimal coordination of overcurrent and distance relays in power system networks.

A Controller Design Researh Based on the Cloud Model

A novel control structure model is proposed based on cloud model for the first time．The structure model is a nonlinear model in nature, and it can be composed of a group of uncertain reasoning rules easily．NonIinear mapping characteristics of cloud model is analysed in this sudy, and the design method of the intelligent controller is presented based on the structure model, and some simulation examples are showed．

Layer Recurrent Neural Network based Power System Load Forecasting

This paper presents a straight forward application of Layer Recurrent Neural Network (LRNN) to predict the load of a large distribution network. Short term load forecasting provides important information about the system’s load pattern, which is a premier requirement in planning periodical operations and facility expansion. Approximation of data patterns for forecasting is not an easy task to perform. In past, various approaches have been applied for forecasting. In this work application of LRNN is explored. The results of proposed architecture are compared with other conventional topologies of neural networks on the basis of Root Mean Square of Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). It is observed that the results obtained from LRNN are comparatively more significant.

Prototyping a Dedicated Photovoltaic System Datalogger

Solar power is a renewable energy seen as one of the primary sources for electricity production in order to meet our daily needs. The conversion operation is sensitive and non-fault tolerant that can occur during operation of the system that affects its overall performance. We propose in this present paper a compact, low power and low-cost datalogger for the control and the monitoring based on a survey measures of five important physical parameters in the management and monitoring of the functioning of an electric system based on solar panels. These measures will be carried out at regular intervals, configurable through a PIC18F4520 microcontroller and stored in a large capacity memory type SD card.

A New Algorithm for Protection of Small Scale Synchronous Generators Against Transient Instability

Today, installation of small generators has been increased because of their considerable benefits in distribution systems in distributed generation. One of the most important problems for transient stability is the effects of the faults of system. Small scale generators have low constant inertia and protection relays have slow performance in distribution systems. Therefore transient instability is a probable phenomenon for the systems with these generators. In this paper, dynamic response of generator has been studied in different fault conditions and then by introducing the concept of " critical fault clearing time ", the sensitivity of this time to the fault type and also fault location parameters have been studied. Then a new protection scheme has been proposed to prevent of transient instability for small scale generator. This protection scheme uses a new evolutionary algorithm based on the active power of generator and critical fault clearing time. The proposed relay can prevent of wrong and unwanted performance. Furthermore it can disconnect the generator from the system in three phase fault near of the bus-bar before its instability. Simulation results show reliable performance of the proposed relay against system transients.

Tissue-like P system based DNA-GA for clustering

In recent years, DNA GA algorithm is drawing attention from scholars. The algorithm combines the DNA encoding and Genetic Algorithm, which solve the premature convergence of genetic algorithms, the weak local search capability and binary Hamming cliff problems effectively.How to design a more effective way to improve the performance of DNA-GA algorithm is more worth studying. As is known to all,the tissue-like P system can search for the optimal clustering partition with the help of its parallel computing advantage effectivel. This paper is under this premise and presents DNA-GA algorithm based on tissue-like P systems (TPDNA-GA) with a loop structure of cells, which aims to combine the parallelism and the evolutionary rules of tissue-like P systems to improve performance of the DNA-GA algorithm. The objective of this paper is to use the TPDNA-GA algorithm to support clustering in order to find the best clustering center.This algorithm is of particular interest to when dealing with large and heterogeneous data sets and when being faced with an unknown number of clusters. Experimental results show that the proposed TPDNA-GA algorithm for clustering is superior or competitive to classical k-means algorithm and several evolutionary clustering algorithms.

A Novel Protective Logic for Optimal Coordination of Overcurrent Relays

Usually coordination of overcurrent relays is done by taking into account the specific structure of the system which does not show the real state of the system. On the other hand, dynamic changes in network can occur due to short circuit conditions, the malfunctioning relays, development, operation and repairs on any part of the power system. Also the most of the new protective schemes are based on a communication channel, which cannot be guaranteed in practice. Therefore, solving the problem of relay coordination is extremely difficult in case of dynamic changes in the network structure and the absence of communication links between some relays. In this article, a novel protective logic based on phasor measurement units (PMUs) data is proposed for optimal coordination of overcurrent relays. In this method, by using the PMU measurements, phasor information can be obtained continuously at any node where PMUs are installed in the power grid. For this purpose, in the first the Optimal PMU placement is determined for full network observability. Then, the dynamic changes of network will be observe by using wide area measurements based on PMUs data. Finally this information is sent via communication links PMUs for the optimal coordination of overcurrent relays. The use of PMU for the coordination of overcurrent relays improve the decision making capability and performance of protective relays and help them to form a reliable and robust protection system. The proposed method is tested on IEEE 8-bus and 14-bus standard networks.

Optimized Operation-Planning of a Microgrid with Renewable Sources and Vehicle to Grid

<p>The microgrid with renewable sources possess stability issues. During the grid-connected mode, these issues are taken care by the external grid. However in case of islanding, the distributed generators within the microgrid, have to take care of these issues independently. It needs additional backup like diesel generation or battery storage, which increases the overall capital and operation costs. With the intervention of the V2G storage, these costs can be saved to some extent. However similar to the renewable sources like wind and solar, the power from V2G is also fluctuating which may lead the microgrid towards an uneconomical operation. Therefore an extensive operation-planning is needed to deal with these uncertainties, for the microgrid to be economically viable. In this context, the stochastic programming has been applied to achieve the optimum results. The stochastic scenarios for wind speed, solar radiation, V2G power and load fluctuation have been generated using the Markov chain Monte Carlo method. The optimized operation-planning aims to minimize the total net present cost, size of the fixed storage and fossil fuel emissions subject to constraints. The simulations have been performed using Matlab/Simulink, HOMER and Excel. The simulation results show that the V2G technology substantially decrease the total net present cost. Moreover for such a microgrid the total net present cost and fossil fuel emissions conflict with each other.</p>