A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems

The unscheduled power flow problem needs to be minimized or controlled as soon as possible in a deregulated power system since the transmission systems are mostly operated at their power-carrying limits or very close to it. The time spent for simulations to determine the current states of all the system and control variables of the interconnected power system is important. Taking necessary action in case of any failure of equipment or any other occurrence of an undesired situation could be critical. Using supercomputing facilities and parallel computing techniques together decreases the computation time greatly. In this study, a parallel implementation of a multiobjective optimization approach based on both genetic algorithms and fuzzy decision making to manage unscheduled flows is presented. Parallel computation techniques are applied using supercomputers (high-performance computers). The proposed method is applied to the IEEE 300 bus test system. Two different cases for some parameters of GA are considered to see the power of parallel computation technique. Then the simulation results are presented

The effects of prenatal and neonatal exposure to electromagnetic fields on infant rat myocardium

Introduction: Electromagnetic fields (EMF) have adverse effects as a result of widespread use of electromagnetic energy on biological systems. The aim of this study was to investigate the effects of prenatal exposure to EMF on rat myocardium by biochemical and histopathological evaluations

A Preventive Control Approach for Power System Vulnerability Assessment and Predictive Stability Evaluation

Early detection of cascading failures phenomena is a vital process for the sustainable operation of power systems. Within the scope of this work, a preventive control approach implementing an algorithm for selecting critical contingencies by a dynamic vulnerability analysis and predictive stability evaluation is presented. The analysis was carried out using a decision tree with a multi-parameter knowledge base. After the occurrence of an initial contingency, probable future contingencies are foreseen according to several vulnerability perspectives created by an adaptive vulnerability search module. Then, for cases identified as critical, a secure operational system state is proposed through a vulnerability-based, security-constrained, optimal power flow algorithm. The modular structure of the proposed algorithm enables the evaluation of possible vulnerable scenarios and proposes a strategy to alleviate the technical and economic impacts due to prospective cascading failures. The presented optimization methodology was tested using the IEEE-39 bus test network and a benchmark was performed between the proposed approach and a time domain analysis software model (EMTP). The obtained results indicate the potential of analysis approach in evaluating low-risk but high-impact vulnerabilities in power systems

The Effect of the Types of Network Topologies on Non-Technical Losses in Secondary Electric Distribution Systems

IEEE/Industry-Applications-Society (IAS) 52nd Industrial and Commercial Power Systems Technical Conference (I and CPS) -- MAY 01-05, 2016 -- Detroit, MIWOS: 000383222500002A portion of generated electrical power is lost in transmission and distribution systems while serviced to endusers. These losses are called technical and non-technical losses in electricity distributions systems. With privatization processes taken place over the world, huge debate arose regarding nontechnical losses. In this study, information about types of losses in distribution systems, privatization process in Turkish electricity distribution network and current loss percentages are given. Possible alterations in distribution network topology to decrease non-technical losses are examined using analytical methods. Best methodology against non-technical losses is determined for different network topologies and customer characteristics, using AHP method. Choosing a pilot network, in which losses are considerably high, a case study is conducted. Cost-benefit analysis is performed within the scope of case study. Results of the case study indicate substantial potential for reducing non-technical losses by just altering network topology, where 1.6% reduction in overall T& L rates is estimated.IEEE, Ind Applicat So

Development and Field Demonstration of a Gamified Residential Demand Management Platform Compatible with Smart Meters and Building Automation Systems

Demand management is becoming an indispensable part of grid operation with its potential to aid supply/demand balancing, reduce peaks, mitigate congestions and improve voltage profiles in the grid. Effective deployments require a huge number of reliable participators who are aware of the flexibilities of their devices and who continuously seek to achieve savings and earnings. In such applications, smart meters can ease consumption behavior visibility, while building automation systems can enable the remote and automated control of flexible loads. Moreover, gamification techniques can be used to motivate and direct customers, evaluate their performance, and improve their awareness and knowledge in the long term. This study focuses on the design and field demonstration of a flexible device-oriented, smart meter and building automation system (BAS) compatible with a gamified load management (LM) platform for residential customers. The system is designed, based on exploratory surveys and systematic gamification approaches, to motivate the customers to reduce their peak period consumption and overall energy consumption through competing or collaborating with others, and improving upon their past performance. This paper presents the design, development and implementation stages, together with the result analysis of an eight month field demonstration in four houses with different user types in Istanbul, Turkey