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

Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed

Improving the data recovery for short length LT codes

Luby Transform (LT) code is considered as an efficient erasure fountain code. The construction of the coded symbols is based on the formation of the degree distribution which played a significant role in ensuring a smooth decoding process. In this paper, we propose a new encoding scheme for LT code generation. This encoding presents a deterministic degree generation (DDG) with time hoping pattern which found to be suitable for the case of short data length where the well-known Robust Soliton Distribution (RSD) witnessed a severe performance degradation. It is shown via computer simulations that the proposed (DDG) has the lowest records for unrecovered data packets when compared to that using random degree distribution like RSD and non-uniform data selection (NUDS). The success interpreted in decreasing the overhead required for data recovery to the order of 25% for a data length of 32 packets

Optimum distributed generation allocation using PSO in order to reduce losses and voltage improvement

The technology advancement in Distributed Generations (DG) has significantly influenced the environmental pollution. In power system, more especially in distribution networks, DGs can able to mitigate the total losses of the network which effectively has significant effects on environmental pollution. Optimal location and size of DG in distribution networks is one of the important issues of the power system. This paper aims to investigate the best solution for optimal operation of distribution networks by taking into consideration of DG. The optimal allocation of DG can be considered as an integer problem that can be formulated by met heuristic methods. In this paper, the Particle Swarm Optimization (PSO) algorithm has been used to solve the DG placement and sizing. The IEEE 34 bus test system has been utilized to demonstrate the effectiveness of the PSO algorithm on herein mentioned problem. The result illustrates the losses minimization and voltage profile improvement

Optimum MV Feeder Routing and Substation siting and rating in Distribution Network

A distribution network planning consists of several complexity aspects due to the multiple decision variables. The main objective of the distribution system planning is to find the optimum number of substation, location, size and feeders routing. This paper proposes an evolutionary algorithm to determine the optimum distribution substation placement and sizing by using the particle swarm optimization algorithm and optimum feeder routing using modified minimum spanning tree algorithm. The proposed algorithm evaluates on the distribution network case with 164 load blocks. The results showed the effectiveness of the proposed algorithm to find the acceptable location and sizing of distribution substations with a proper routing of the feeder

Optimum distributed generation allocation using PSO in order to reduce losses and voltage improvement

The technology advancement in Distributed Generations (DG) has significantly influenced the environmental pollution. In power system, more especially in distribution networks, DGs can able to mitigate the total losses of the network which effectively has significant effects on environmental pollution. Optimal location and size of DG in distribution networks is one of the important issues of the power system. This paper aims to investigate the best solution for optimal operation of distribution networks by taking into consideration of DG. The optimal allocation of DG can be considered as an integer problem that can be formulated by met heuristic methods. In this paper, the Particle Swarm Optimization (PSO) algorithm has been used to solve the DG placement and sizing. The IEEE 34 bus test system has been utilized to demonstrate the effectiveness of the PSO algorithm on herein mentioned problem. The result illustrates the losses minimization and voltage profile improvement

Optimum Distributed Generation Allocation Using PSO in order to Reduce Losses and Voltage Improvement

The technology advancement in Distributed Generations (DG) has significantly influenced the environmental pollution. In power system, more especially in distribution networks, DGs can able to mitigate the total losses of the network which effectively has significant effects on environmental pollution. Optimal location and size of DG in distribution networks is one of the important issues of the power system. This paper aims to investigate the best solution for optimal operation of distribution networks by taking into consideration of DG. The optimal allocation of DG can be considered as an integer problem that can be formulated by met heuristic methods. In this paper, the Particle Swarm Optimization (PSO) algorithm has been used to solve the DG placement and sizing. The IEEE 34 bus test system has been utilized to demonstrate the effectiveness of the PSO algorithm on herein mentioned problem. The result illustrates the losses minimization and voltage profile improvement

A global system for mobile communications-based electrical power consumption for a non-contact smart billing system

This paper proposes a cheap solution to be a starting point for building smart electrical power billing systems. Electrical power has many challenges issues in Iraq, one of these challenges and the most important is the Billing system. The smart power meter uses an Arduino Uno as the core for controlling the sensed data and transmits it to the electrical power unit for billing services. The system is constructed with two parts: the transmitting unit measures the current, voltage, power and power factor through the compact new sensor PZEM-004T. The data sensed and processed by the microcontroller which displayed the KWh on (2*16 LCD) display. This data also transmitted to the electrical power company unit via the global system for mobile communications (GSM) module (SIM900A) which is a dual band GSM/GPRS-general packet radio service modem. The receiving part is mainly dedicated for collecting the required consumed power data via the same (SIM900A) module and also can display it using (2*16 LCD) display. For the sake of saving these data, the receiver part uses SD ram for such purposes. With such proposed system the electrical power company can control and collect their fees monthly without loss and with minimum cost

Optimum Feeder Routing and Distribution Substation Placement and Sizing using PSO and MST

A long term distribution network planning consists of several complexity aspects due to the multiple decision variables in objective functions. Optimum placement of distribution substations and determination of their sizing and feeder routing is one of major issues of distribution network planning. This paper proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified MST. The proposed algorithm has been evaluated on the distribution network case with 500 consumers which are consisting of residential and commercial loads. The test network is generated by fractal based distribution network generation model software tool. The results indicate the proposed algorithm has been succeeded to find the reasonable placement and sizing of distributed generation with adequate feeder path

Optimal Capacitor Allocation in Distribution System using Particle Swarm Optimization

In distribution networks, capacitor installation is one of the commonly used methods for reactive power compensation. Capacitor placement and sizing in power system can be applied in multiple objectives and reasons. In this paper, the optimum capacitor placement and sizing has been applied in the distribution network in terms of power losses minimization and voltage profile improvement. The maximum and minimum bus voltage and maximum possible capacitor size are the constraints of optimum capacitor placement and sizing problem which considered as a penalty factor in the objective function. In order to solve the obtained objective function, the Particle Swarm Optimization (PSO) is utilizes to find the best possible capacitor placement and size. The OpenDSS software has been utilized to solve the power flow through Matlab coding interface. To validate the functionality of the proposed method, the IEEE 13-bus test system is implemented and the obtained results have been compared with IEEE standard case and without capacitor case. 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, accordingly