A Novel Method for Frequency Estimation Considering Instrument Transient Effect

Large disturbances in power systems cause deviation in the frequency from the nominal value. Since the frequency is an important factor in the electrical network parameter measurements, it can cause malfunction of the protection system. In addition, Because of decaying DC and oscillatory components that introduced by CCVT in response of voltage variation during the fault occurrence, cause changes in the value of received voltage of primary side of CCVT. An improved least square method for estimating frequency is presented in this paper. In order to reduce the effect of this transient component, phasor estimation method has been improved by using the least square technique and utilizing knowledge of CCVT design. The capability of the proposed method was verified by several case studies generating signals in PSCAD/EMTDC. The results show the accuracy, speed and capability of the proposed metho

A Secure-Coordinated Expansion Planning of Generation and Transmission Using Game Theory and Minimum Singular Value

In this paper a novel method have been proposed for expansion planning of generation and transmission that considered static security of the system such as voltage security margin And loadability limit. In the same study of expansion planning Security constraints of the system are neglected. In this study at the first step minimum singular value technique is used to evaluate voltage security margin and loadabolity limit, in order to select best bus for load incrimination. After it, in order to Supply the load, coordinated expansion planning of generation and transmission is needed, therefor the strategic interaction between transmission company (TransCo) and generation company (GenCo) for Transmission expansion planning (TEP) and generation expansion planning (GEP) in a competitive electricity market is proposed using Game Theory (GT).DOI:http://dx.doi.org/10.11591/ijece.v4i6.668

A Novel method to estimate Economic Replacing Time of Transformer Using Monte Carlo Algorithm and ANN

A hybrid method for developing a more principled approach is presented to determine the life expectancy of transformers. The approach is constructed on an economic analysis of the transformers operational characteristics in combination  with the technical issues incorporated in the decision process. In this method, firstly life time of transformer is estimated using a hybrid method based on Monte Carlo algorithm and artificial neural network. Also Pareto distribution function is applied to consider health history of transformer and uncertainty in DP behavior of transformer. In the next step, a method is proposed in order to estimate economic replacement time of transformer. This method is based on the well-known bathtub failure model, containing repairs and scheduled maintenance, in order to achieve at a more economically aim  replacing decision. This aim is obtained in part by considering the uncertainty intrinsic in transformer failures and the corresponding discontinuations in power. In essence, this method organizes a decision support system for determination the life expectancy of a transformer. Simulation results show the high accuracy and functionality of the proposed approach in estimating economic replacing time of the Transformer

Simulation of a Stirling Engine Solar Power Generation System Using Simulink

In order to fully study a Stirling engine based solar power generation system, a detailed model that considers all thermal, mechanical, and electrical aspects of the system should be used. Research in the area of Stirling engine systems has been performed either without considering the electrical parts, or with a simple model for the electrical parts. Hence, the effects of interactions between electrical and mechanical components are neglected. In this paper, simulation of a solar powered Stirling engine system is proposed that considers all thermal, mechanical, and electrical aspects of the system. The system is mainly composed of two parts that are the mechanical and electrical parts. The mechanical part includes the Stirling engine that is modeled using thermal and mechanical equations in Matlab/Simulink environment. The electrical part consists of a synchronous generator, an ac/dc converter, a battery, and an electrical dc load that are simulated using Simulink blocks

Decentralized Multi-Objective Energy Management With Dynamic Power Electronic Converters and Demand Response Constraints

Energy management plays a pivotal role in enhancing the economic efficiency of power systems. However, it is noteworthy that a substantial number of microgrids (MGs) exhibit inherent unbalances that impose a range of critical issues, including voltage instability, elevated losses, power quality violations, safety concerns, and inefficiencies in energy management. Fast-acting power electronic converters present a relevant and efficacious solution for balancing such complex networks. This paper investigates the application of such converters within the realm of 3-phase unbalanced networks, wherein the proposed algorithm not only ameliorates network imbalances but also yields substantial reductions in operational costs, power losses, voltage deviations, and emissions. Demand response (DR) program has been applied to the model to enhance the system efficiency. The uncertainty about electric demand and renewable energy sources is considered in the simulation model for precise results. By implementing DR programs and penetrating distributed generators (DGs), the proposed model has been shown to reduce network losses and operation costs by 23% and 80%, respectively. Also, the total up-to-down voltage deviation of the voltage profile has been significantly reduced by 400%

Enhancing Transient Stability of Distribution Networks With Massive Proliferation of Converter-Interfaced Distributed Generators

High penetration of renewable energy sources and energy storage systems has considerably increased the flexibility in power distribution networks operation. However, employing converter-interfaced energy and storage sources may significantly reduce the mechanical inertia and as a result, the power grids may confront serious stability challenges during transient conditions. This article introduces a strategy for enhancing transient stability margin of active distribution networks with high penetration of electric vehicles (EVs). The proposed optimization strategy intends to control EVs contributions during transient stability conditions. The EVs contributions are controlled through a new index proposed based on the system's total corrected critical kinetic energy (TCCKE). The proposed procedure for TCCKE calculation is driven by a hybrid algorithm taking into account the equal area criterion and sensitivity analysis. The suggested procedure for TCCKE only depends on the during fault data and as a result, the proposed optimization strategy is useful to prevent transient instability in the case of first swing instability. The proposed optimization is applied and evaluated on the IEEE test systems. The results clearly demonstrate the applicability and efficacy during a multitude of fault and emergency conditions.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Load shedding frequency management of microgrids using hierarchical fuzzy control

Frequency control is one important issue in autonomous operating mode of Microgrids (MGs). In stand-alone microgrids, when generation power is not enough, it is inevitable to shed some parts of the load. This paper presents a decentralized fuzzy controller for optimal load shedding in MGs. The proposed controller which is separately installed for each load center uses a hierarchical fuzzy controller approach to make the optimal decision. Three inputs of the hierarchical fuzzy controller are the power of non-critical load, the load energy not supplied and its interruption frequency. From a specific time of the past, these inputs are calculated for all load centers, and updated periodically. The non-critical part of the loads which can be shed to survive network. Each decentralized controller of the loads has a bilateral communication with the microgrid central controller to transact some information, periodically. Simulation results on a typical microgrid with several load buses showing the effectiveness of the proposed method