Distribution networks reconfiguration (DNR) is the process of changing the topology of distribution systems by altering the open/closed status of switches to transfer loads among the feeders. One objective of the feeder reconfiguration of distribution systems is to minimize the total power losses for a specific load. This book adopts two new efficient heuristic techniques for reconfiguration of electrical distribution systems; the real ants’-behavior-inspired Ant Colony Optimization (ACO) algorithm implemented in the Hyper Cube (HC) framework and the musicians’-behavior-inspired Harmony Search (HS) algorithm. To verify the effectiveness of the proposed algorithms, comparative studies are conducted on three test systems with encouraging results. The obtained results are compared with the results of other purely heuristic and AI-based approaches from literature to examine the performance. This book also emphasis the advantages of Insertion of Distributed Generation units (DGs) to the electrical distribution networks and the advantages of reconfiguration in presence of DGs on the total power loss reduction and bus voltage improvement.
It presents a basic meaning for the distribution networks in united systems including city power systems and their classification. All components are inserted & their logic is illustrated. Renewable energy support is proposed while most important factors are studied. Power factor, voltage drop, power loss and load curves (with harmonics) are analyzed however, the coding systems were presented in details. Two major examples as a project style have been investigated with results. LAN, fire fighting and Telephone wiring are accounted.
The electrification of the transportation sector is being regarded as an important measure to reduce the fossil fuel consumption and decrease the emission of greenhouse gases. Despite these benefits, the electricity demanded by Electric Vehicles (EV) will represent a major challenge for the electric power systems. The deployment of EV will change the power demand patterns, causing changes in the grids’ voltage profiles, power flows and energy losses, namely at the distribution level, where EV will be plugged-in for charging. This book is devoted to the integration of EV in distribution grids and it can be divided in three parts: In the first part, a comprehensive framework for EV integration in electrical power systems is presented, providing a holistic perspective of this new reality; The second part is dedicated to the evaluation of the impacts provoked by EV in distribution networks; Finally, appropriate management strategies for EV charging are presented in order to achieve several objectives, like flattening the network load diagrams or minimizing the renewable energy wasted in systems characterized by a large integration of intermittent renewable energy sources (e.g. wind).
This book presents an efficient meta-heuristic method for distribution systems reconfiguration for lower losses and better voltage profile. A modified Tabu Search (MTS) algorithm is used to reconfigure distribution systems so that active power losses are minimized with turning on/off sectionalizing switches. A new method to check the radial topology of the system is presented. Also, the reconfiguration problem is solved using the particle swarm optimizer (PSO), a member of the recently growing swarm intelligent-based algorithms. In most of the PSO publications, the algorithm is used for solving problems of unconstrained optimization. Consequently, to address the feeder reconfiguration problem, some modifications to the standard PSO are proposed to allow dealing with such highly constrained optimization problem. To verify the effectiveness of the proposed methods, comparative studies are conducted on four test systems with encouraging results. The proposed methods are applied to 16-node, 32-node, 69-node, and 119-node distribution systems. The obtained results are compared with results obtained using other approaches in the previous literature work to examine the performance.
Dynamic reconfiguration is one of the most important problems in the field of network management. In the case of some part of the network being damaged the system should maintain its operations, taking into account the new conditions. This can be achieved by using the reserve capacity of the system if it is available. To reorganize traffic by using new routes we should have a flexible routing system. The dynamic reconfiguration problem becomes more complicated if Service Level Agreements (SLAs) are taken into account. We consider the so-called Olympic service that provides three tiers of services: gold, silver and bronze with decreasing quality. When the failure occurs, the provider needs to reconfigure the transfer of the network as quickly as possible, attending firstly to the gold customers and once that is done to the silver customers and lastly, if there is any time left, to the bronze customers. We describe various linear programming problems that can be used for dynamical reconfiguration in the presence of SLA. In particular we discuss in detail approaches to reconfiguration with and without penalization.
Reliability of power system depends on the up to date knowledge of the system state for operation and control. Shifting from large conventional production units to small and/ or renewable DG connected in the distribution network means more control and monitoring system require for the Distributed System operator caused by active generation and reactive power consumption by DG. It is technically impossible to continuously model the distribution grid in real time because of tremendous number of nodes distribution and elements system.Therefore it is interesting to explore concepts in fast and scalable topology processors for monitoring and controlling applications such as state estimation, OPF and static and dynamic stability assessment in electrical distribution network the need is evident to validate with meshed network to analyze the overall performance of the proposed methodology Decentralized Topology Inference of Electrical Distribution Networks. The topology inference processor is require minimal prior knowledge of electrical network structure by taking a series of time-stamped process measurements from each bays of each substation in the network and determine the topology.
Proliferation of distributed energy resource units, including both generation and energy storage, at the power distribution voltage level has necessitates full reconsideration of control and operational practices in the power utility distribution system. These issues will be further compounded by integration of a large number of electric vehicles (EVs) in the future. The term active distribution network (ADN) is used to identify a distribution system which includes distributed energy resource units and provides an umbrella for a coordinated operation of the units and the host distribution system. This requires a set of comprehensive of mathematical models of the active distribution network building blocks to identify and analyze various electrical phenomena within the ADN. The analytical approaches and the corresponding production level software tools are not directly applicable to the ADN. The reasons are the inherently different characteristics of the ADN as compared to the bulk transmission systems. This book is an attempt to provide a systematic approach to mathematically formulate various components of the the ADN for steady-state and quasi-steady-state analysis.
This book covers the concept of peer to peer networks in detail including the different data distribution techniques. The book also includes the hierarchical approach for data distribution. and discuss what do you mean by static and dynamic databases. how we can change the data in the databases at different peers. the concept of master and slave have made the picture of all the above. how the throughput ,resource utilization of system varies with single master and then with one slave also/
Systematically introduces self-healing control theory for distribution networks, rigorously supported by simulations and applications• A comprehensive introduction to self-healing control for distribution networks• Details the construction of self-healing control systems with simulations and applications• Provides key principles for new generation protective relay and network protection• Demonstrates how to monitor and manage system performance• Highlights practical implementation of self-healing control technologies, backed by rigorous research data and simulations
This study gives a description about the development of a computer model, RealPipe, which relates genetic algorithm (GA) to the well known problem of least-cost design of water distribution network. GA methodology is an evolutionary process, basically imitating evolution process of nature. GA is essentially an efficient search method basically for nonlinear optimization cases. The genetic operations take place within the population of chromosomes. By means of various operators, the genetic knowledge in chromosomes change continuously and the success of the population progressively increases as a result of these operations. GA optimization is also well suited for optimization of water distribution systems, especially large and complex systems. The primary objective of this study is optimization of a water distribution network by GA. GA operations are realized on a special program developed by the author called RealPipe. RealPipe optimizes given water network distribution systems by considering capital cost of pipes only.
Power quality problem is common in utilities and distribution networks, which provide power to various sectors like factories. In many geographical areas there is no longer tightly coordinated control of power from generation through end-user load with regard to power quality problems. Equally the problem is apparent in connection to factories building in new areas that suddenly face unanticipated problems with the electricity supply due to, faults from supply systems or efforts to maximize their efficiency of utilizing power.
The reconfiguration process for Shipboard Power System reroutes the electric power in the power system in order to achieve certain objectives, The reconfiguration process can improve the survivability and reliability of the power system. Most of today's reconfiguration methodologies are centralized. In a Shipboard Power System’s centralized reconfiguration approach, a single point of failure may happen if the system lacks redundancy. The Multi Agent System (MAS) technology is recently applied to the applications in power systems. The MAS is composed of agents that are intelligent entities with the capability of problem solving. However, current MAS applications on power system reconfiguration methodologies are topology dependent. Additionally, No MAS based reconfiguration methodology has been proposed for mesh structured power system reconfiguration.In this book, a completely decentralized MAS based reconfiguration methodology is proposed for Shipboard Power Systems. In this approach, an MAS is proposed for the reasoning of the reconfiguration. Each agent works autonomously and independently and the MAS works in a completely decentralized manner.
Excellent reference outlining the technical basis and working principles of live-line working, with current application technology, tools and working methods Introduces live-line working technology for the operation and maintenance of medium and low voltage power distribution networks, covering both the methods and techniques of live-line working on distribution networks with O&M field practices and experiences Elaborates the technical basis and working principles of live-line working in detail, with current application technology, tools and working methods Combining theory and practice closely, it provides technical guidance and helpful references to technical personnel who are engaged in distribution operation management, as well as related academics and researchers Written by a team of authors with extensive experience in both industry and academic fields, providing first-hand testimony of the issues facing electricity distribution companies, and offering sound theoretical foundations and rich field experiences