Optimal Sizing and Placement of Solar Cell Distributed Generator Suitable for Integrated Power System Environment

A novel fuzzified Clustered Gravitational Search Algorithm (CGSA) has been employed for solving multi-objective problem formulated for solar based distributed generation. Optimal sizing and placement of solar distributed generation is considered. High solar penetration can lead to high-risk level in power system reliability. In order to maintain the system reliability, solar power dispatch is usually restricted based on the reliability level of the system. Two conflicting objective functions such as power loss and reliability level of the system are also considered for solving optimal placement of solar distributed generation (SDG). Binary coded CGSA is employed for solving optimal placement of SDG and sizing is determined using real coded CGSA. The fuzzy membership function for each objective is designed and multi-objective optimal placement problem has been presented. The proposed method is validated on IEEE standard 69-bus radial distribution networks. The efficiency of the proposed optimization technique is validated by comparing the results with other results available in the existing articles

Electricity distribution network for low and medium voltages based on evolutionary approach optimization

The optimum planning of distribution systems consists of the optimum placement and size of new substations, feeders, capacitors, distributed generation and other distribution components in order to satisfy the future power demand with minimum investment and operational costs and an acceptable level of reliability. This thesis deals with the optimization of distribution network planning to find the most affordable network design in terms of total power losses minimization and voltage profiles improvement. The planning and operation of distribution networks are driven by several important factors of network designing. The optimum placement and sizing of the capacitor banks into existing distribution networks is one of the major issues. The optimum placement and sizing of the new substations and distribution transformers with adequate feeder connections with minimum length and maximum functionality are vital for power system as well as optimum placement and sizing of the distributed generators into the existing grid. This thesis commonly investigated the impacts of these factors on voltage profile and total power losses of the networks and aims to reduce the capital cost and operational costs of the distribution networks in both LV and MV levels. Optimum capacitor installation has been utilized in terms of reactive power compensation to achieve power loss reduction, voltage regulation, and system capacity release. The Particle Swarm Optimization (PSO) is utilized to find the best possible capacitor placement and size. The OpenDSS engine is utilized to solve the power flow through MATLAB coding interface. To validate the functionality of the proposed method, the IEEE 13 node and IEEE 123 node test systems are implemented. The result shows that the proposed algorithm is more cost effective and has lower power losses compare to the IEEE standard case. In addition, the voltage profile has been improved. Optimum placement of distribution substations and determination of their sizing and feeder routing is another major issue of distribution network planning. This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). The proposed algorithm has been evaluated on the two types of distribution network models which are the distribution network model with 500 customers that includes LV residential and commercial loads as well as MV distribution network, and 164 nodes in MV level. The test network is generated by fractal based distribution network generation model software tool. The results indicate that proposed algorithm has succeeded in finding a reasonable placement and sizing of distributed generation with adequate feeder path. Another sector of power system that is taken into account in this work is Distributed Generators (DGs). In power system, more especially in distribution networks, DGs are able to mitigate the total losses of the network which effectively has significant effects on environmental pollution. This thesis aims to investigate the best solution for an optimal operation of distribution networks by taking into consideration the DG. The PSO method has been used to solve the DG placement and sizing on the IEEE 34 and 123 nodes test systems, respectively. It has been utilized to demonstrate the effectiveness of the PSO method to improve the voltage profile and minimize the cost by mitigating the total losses of the network

Placement of Distributed Generation and Shunt Capacitor in Distribution Network using Cuckoo Search Algorithm

This work aims at reduction in active and reactive power loss reduction in distribution networks as well as to improve the voltage stability of the networks. Optimum Distributed Generation (DG) placement and sizing is carried out in conjunction with shunt capacitor placement and sizing to determine the appropriate sizes of DG units and Capacitor banks to be placed in the networks so as not to violate certain constraints. The optimal sizes of the DG units and capacitor banks were obtained on application of a Cuckoo Search Optimization Algorithm while computations for Voltage stability was performed using the Voltage Stability Index (VSI). The obtained optimal sizes of DG units and Capacitors were individually and simultaneously placed on the distribution networks to ascertain the behaviour of the networks prior to and after their placements. The performance factors considered are power loss and voltage stability. A comparison of these performance factors under separate and simultaneous placement method was demonstrated using IEEE 33 and 69 test buses. Result show that power loss (active and reactive) reduced by 63.29% and 59.38% respectively for 33 bus system, with a 74.29% and 79.19% reduction on 69 bus system. Voltage stability also increased by 7.89% and 3.79% respectively for 33 and 69 bus system relative to values obtained for base case and separate DG and shunt capacitor placement. Keywords: Distributed generation, shunt capacitor, Cuckoo Search Algorithm (CSA), power loss and voltage stability

MITIGATE THE REAL POWER LOSSES IN RADIAL DISTRIBUTED NETWORK USING DG BY ABC ALGORITHM

Recently, integration of Distributed generation (DG) in distribution system has increased to high penetration levels. The impact of DG on various aspects of distribution system operation, such as reliability and energy loss depend highly on DG location in distribution feeder .Optimal DG placement plays an important role . This project presents a new methodology using Artificial Bee Colony  algorithm (ABC) to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses .The proposed technique is tested on standard IEEE-33 bus test system

Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm

The deployment of utility-scale energy storage systems (ESSs) can be a significant avenue for improving the performance of distribution networks. An optimally placed ESS can reduce power losses and line loading, mitigate peak network demand, improve voltage profile, and in some cases contribute to the network fault level diagnosis. This paper proposes a strategy for optimal placement of distributed ESSs in distribution networks to minimize voltage deviation, line loading, and power losses. The optimal placement of distributed ESSs is investigated in a medium voltage IEEE-33 bus distribution system, which is influenced by a high penetration of renewable (solar and wind) distributed generation, for two scenarios: (1) with a uniform ESS size and (2) with non-uniform ESS sizes. System models for the proposed implementations are developed, analyzed, and tested using DIgSILENT PowerFactory. The artificial bee colony optimization approach is employed to optimize the objective function parameters through a Python script automating simulation events in PowerFactory. The optimization results, obtained from the artificial bee colony approach, are also compared with the use of a particle swarm optimization algorithm. The simulation results suggest that the proposed ESS placement approach can successfully achieve the objectives of voltage profile improvement, line loading minimization, and power loss reduction, and thereby significantly improve distribution network performance

Coordinated planning in improving power quality considering the use of nonlinear load in radial distribution system

Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method

Optimized Solar Photovoltaic Generation in a Real Local Distribution Network

Remarkable penetration of renewable energy in electric networks, despite its valuable opportunities, such as power loss reduction and loadability improvements, has raised concerns for system operators. Such huge penetration can lead to a violation of the grid requirements, such as voltage and current limits and reverse power flow. Optimal placement and sizing of Distributed Generation (DG) are one of the best ways to strengthen the efficiency of the power systems. This paper builds a simulation model for the local distribution network based on obtained load profiles, GIS information, solar insolation, feeder and voltage settings, and define the optimization problem of solar PVDG installation to determine the optimal siting and sizing for different penetration levels with different objective functions. The objective functions include voltage profile improvement and energy loss minimization and the considered constraints include the physical distribution network constraints (AC power flow), the PV capacity constraint, and the voltage and reverse power flow constraints.Comment: To be published (Accepted) in: Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference (ISGT), Washington D.C., USA, 201

Network reconfiguration under normal and fault condition with the presence of distributed generation in a distribution system / Zuhaila Mat Yasin

This thesis presents the implementation of network reconfiguration in radial distribution system with the presence of distributed generation to improve the distribution system performance in terms of loss minimisation and voltage profile improvement. The network reconfiguration is performed by altering the topological structure of distribution feeders. During normal operating condition, networks are reconfigured to reduce the system real power losses. The optimal sectionalising - tie switch pairs were determined by the TOPO application available in the power system simulation programme for planning, design and analysis of distribution system (PSS/Adept). This application determines optimal sectionalizing - tie switch pairs based on minimum losses configuration and at the same time, all nodes are assured for the supply. The introduction of distributed generation into the distribution system can significantly impact the distribution system depending on the system operating condition, distributed generation characteristic, location and sizing. Therefore, a proper placement plays a very important role. In this thesis, the suitable location for distributed generator was predetermined using the previously developed sensitivity indices derived from voltage stability improvement with respect to changes in injected active and reactive power at a bus. The optimal capacity sizing of the distributed generation was pre-determined using the Evolutionary Programming (EP) optimisation technique. Various locations and sizes of distributed generation were tested in order to realize the effect of location and sizing of distributed generation in terms of loss minimisation and voltage improvement during network reconfiguration. In order to study the effect of location and sizing of distributed generation to the power losses and voltage profile during network reconfiguration for service restoration, a three phase fault is applied at an identified location. The network is reconfigured after the fault is isolated. The study was implemented on the IEEE 69-bus test system. The studies also compare the network performance in terms of loss minimization and voltage profile improvement achieved by optimal network reconfiguration when compensating capacitor present in the system