Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm

A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network

A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation

Power loss reduction can be considered as one of the main purposes for distribution system operators. Reconfiguration is an operation process used for this optimisation by means of changing the status of switches in a distribution network. Recently, all system operators tried their best in order to obtain well-balanced distribution systems to decrease the operation cost, improve reliability and reduce power loss. This study presents an efficient method for solving the multi-objective reconfiguration of radial distribution systems with regard to distributed generators. The conventional distribution feeder reconfiguration (DFR) problem cannot meet the reliability requirements, because it only considers loss and voltage deviation as objective functions. The proposed approach considers reliability, operation cost and loss simultaneously. By adding the reliability objective to the DFR problem, this problem becomes more complicated than before and it needs to be solved with an accurate algorithm. Therefore this study utilises an Enhanced Gravitational Search Algorithm called EGSA which profits from a special mutation strategy in order to reduce the processing time and improve the quality of solutions, particularly to avoid being trapped in local optima. The proposed approach has been applied to two distribution test systems including IEEE 33 and 70-node test systems.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2013.0117

Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost

Reconfiguration of radial distribution networks is becoming a viable solution for improving the performance of distribution networks. Configurations may be varied with manual or automatic switching operations so that all of the loads are supplied and reduce power loss, increase system security, and enhance power quality. Reconfiguration also relieves the overloading of the network components. The change in the network configuration is performed by opening sectionalizing (normally closed) and closing tie (normally open) switches of the network. These switchings are performed in such a way that the radiality of the network is maintained and all of the loads are energized. Several researchers have attempted to solve the power distribution network reconfiguration problem using various techniques. This paper presents a comprehensive survey on network reconfiguration to bring out a clear idea for future research.

A comprehensive review on power distribution network reconfiguration

Distribution system reconfiguration using a modified Tabu Search algorithm

This paper introduces the Particle Swarm Optimization (PSO) algorithm to solve the optimal network reconfiguration problem for power loss reduction. The PSO is a relatively new and powerful intelligence evolution method for solving optimization problems. It is a population-based approach. The PSO was inspired from natural behavior of the bees on how they find the location of most flowers. The proposed PSO algorithm is introduced with some modifications such as using an inertia weight that decreases linearly during the simulation. This setting allows the PSO to explore a large area at the start of the simulation. A modification in the number of iterations and the population size is also presented. To verify the effectiveness of the proposed PSO algorithm, comparative studies are conducted on two test distribution systems. The obtained results are compared with those obtained using other approaches in the previous work to examine the performance.

A modified particle swarm Algorithm for distribution systems reconfiguration

The subject of petroleum storage tank fires has gained a great deal of attention due to the high cost of petroleum, and the consequent disruption of petroleum production; therefore, much of the current research has focused on petroleum storage tank fires. Also, the number of petroleum tank fires is oscillating between 15 and 20 fires per year. About 33% of all tank fires are attributed to lightning. Floating roof tanks (FRT’s) are especially vulnerable to lightning. To minimize the likelihood of a fire, the API RP 545 recommends three major modifications to floating roof tanks. This paper was inspired by a stroke of lightning that ignited a fire in a crude oil storage tank belonging to an Egyptian oil company, and is aimed at providing an efficient lightning protection system to the tank under study, in order to avoid the occurrence of such phenomena in the future and also, to give valuable recommendations to be applied to floating roof tank projects. Keywords—Crude oil, fire, floating roof tank, lightning protection system.

/pdf/protection-of-floating-roof-petroleum-storage-tanks-against-38ghhshdsa.pdf

F.M. Mohamed

Papers

Distribution system reconfiguration using a modified Tabu Search algorithm

A modified particle swarm Algorithm for distribution systems reconfiguration

Protection of Floating Roof Petroleum Storage Tanks against Lightning Strokes