As the load steadily rises in a distribution system (DS), electrical power generation is improved. Inserting Distributed Generation (DG) unit in a DS has benefits such as enhancement in voltage profile and decreased power losses. In combination with optimal size, these advantages can be obtained to inject DG in the optimal location. Reconfiguration is another framework for optimizing the voltage profile and reduction of energy loss. Furthermore, reconfiguring the distribution network and installing the DG would ultimately improve system efficiency, which is undoubtedly challenging task. In this paper, equilibrium optimizer (EO) is explored to find out how to reconfigure the distribution network and how best DG can be positioned. For the IEEE-33 bus. Reliability Analysis is also done. The suggested method is implemented in MATLAB R2020A platform software. Outcomes of the suggested Technique based on the EO is compared with the existing techniques. There is Substantial improvement in voltage profile in addition to the decline in loss of power and reliability indexes (EENS, SAIFI, and SAIDI) for different cases of System with DG placement and System.

Enhancement of Voltage Profile in the Distribution system by Reconfiguring with DG placement using Equilibrium Optimizer

Installation of distribution generation (DG) in the distribution system gains many technical benefits. To obtain more benefits, the location and size of DG must be selected with the appropriate values. This paper presents a method for optimizing location and size of DG in the distribution system based on enhanced sunflower optimization (ESFO) to minimize power loss of the system. In which, based on the operational mechanisms of the original sunflower optimization (SFO), a mutation technique is added for updating the best plant. The calculated results on the 33 nodes test system have shown that ESFO has proficiency for determining the best location and size of DG with higher quality than SFO. The compared results with the previous methods have also shown that ESFO outperforms to other methods in term of power loss reduction. As a result, ESFO is a reliable approach for the DG optimization problem.

/pdf/enhanced-sunflower-optimization-for-placement-distributed-4o94tvjfia.pdf

Enhanced sunflower optimization for placement distributed generation in distribution system

Due to the unequal loads in phases and different customer consumption, the distribution network is unbalanced. Unbalancing in the distribution network, in addition to increasing power losses, causes unbalancing in voltages and increases operating costs. To reduce this unbalancing, various methods and algorithms have been presented. In most studies and even practical projects due to lack of information about the network loads, load models such as constant power model, constant current or constant impedance are used to model the loads. Due to the changing and nonlinear behaviours of today's loads, these models cannot show results in accordance with reality. This paper while introducing an optimal phase-balancing method, discusses the effect of load modelling on phase balancing studies. In this process the re-phasing method for balancing the network and the harmony search algorithm for optimizing the phase displacement process have been used. The simulation was carried out on an unbalanced distribution network of 25 buses. The results show well the effect of this comprehensive modelling on phase balancing studies. It also shows that in the re-phasing method for balancing the network and in the absence of a real load model, the use of which model offers the closest answer to optimal solutions.

http://ijece.iaescore.com/index.php/IJECE/article/download/12965/11968

The effect of load modelling on phase balancing in distribution networks using search harmony algorithm

Wireless Mesh Networks (WMN) consists of wireless stations that are connected with each other in a semi-static configuration. Depending on the configuration of a WMN, different paths between nodes offer different levels of efficiency. One areas of research with regard to WMN is cost minimization. A Modified Binary Particle Swarm Optimization (MBPSO) approach was used to optimize cost. However, minimized cost does not guarantee network performance. This paper thus, modified the minimization function to take into consideration the distance between the different nodes so as to enable better performance while maintaining cost balance. The results were positive with the PDR showing an approximate increase of 17.83% whereas the E2E delay saw an approximate decrease of 8.33%.

/pdf/improvement-at-network-planning-using-heuristic-algorithm-to-3qr9i8v6ga.pdf

Improvement at Network Planning using Heuristic Algorithm to Minimize Cost of Distance between Nodes in Wireless Mesh Networks

Power distribution feeders is one of the key contributors of technical losses (TL) as it is typically large in numbers and scattered over large geographic areas. Traditional approach using classical formulation or time series load flow simulations to determine TL in each and every feeder and feeder sections in all distribution network require is an expensive exercise as it requires extensive modelling of the feeders and voluminous data. This paper presents a simple analytical approach to estimate monthly TL of a radial distribution feeder using analytical approach. TL for each feeder sections are evaluated on a monthly basis based on estimation of the load profile of the load points, peak power loss characteristics and loss factor. Total feeder TL are then estimated as the sum of all TL contributed by each feeder section. The developed models and procedure have been demonstrated through case studies performed on three (3) typical and representative feeders characterized by the different area served, number of feeder sections, load distribution and feeder length. The results shows close agreement (less than 5% differences) when compared with time series load flow simulations. With this model, the approach could be extended and applied to estimate TL of any radial distribution feeders of different configurations and characteristics

/pdf/a-new-methodology-for-technical-losses-estimation-of-radial-1bnjfo26fn.pdf

A new methodology for technical losses estimation of radial distribution feeder

Due to dynamic nature of loads, total system load is more than its generation capacity that makes relieving of load on the feeders not possible and hence voltage profile of the system will not be improved to the required level. In order to meet required level of load demand, Reconfiguration & DG units are integrated in distribution network to improve voltage profile, to provide reliable and uninterrupted power supply and also to achieve economic benefits such as minimum power loss, energy efficiency and load leveling. This work proposes minimization of real power losses and improvement of voltage profile using network reconfiguration in the presence of distributed generation. Generally distributed generations (DG) are preferred with objective of minimizing real power loss and improving voltage profile in distribution system. In this work A meta heuristic Harmony Search Algorithm (HSA) is used to simultaneously reconfigure and identify the optimal locations for installation of DG units in a distribution network. Sensitivity analysis is used to identify optimal locations for installation of DG units. The proposed method has tested in MATLAB for 33-bus and 69- Bus radial distribution systems at three different load levels and the analysis is presented for loss minimization.

https://beei.org/index.php/EEI/article/download/509/346

B Gurusekhar

Papers

Reconfiguration with Simultaneous DG installation to Improve the Voltage Profile in Distribution Network using Harmony Search Algorithm