This thesis report is an attempt to identify the causes and probable solution of voltage profile issues in the Terai part of Nepal, specifically focused on Laukahi feeder. This radial feeder, Laukahi, is approximately 65km and distributed with 11KV system voltage where the inception point is Inaruwa sub-station and terminates with various parts of Sunsari district, Nepal.
Currently, many villages farther than this substation are getting extremely poor voltages with frequent interruption of the power supply. Irrigation projects and grinding mills located at these places are unable to operate at its optimum capacity. In addition, small consumers are unable to run electrical appliances all the time in a day, not even an electric fan in hot season. To analyze this problem, identical system has been developed in MATLAB, and possible solutions are recommended.
Solar PV and Capacitor banks are using as an active and a reactive power generating sources have to penetrate at suitable buses of the system in order to improve the voltage profile of the feeder and to reduce the branch loss as well. Suitable size and location of the DG sources has been identified by using Ant Colony Optimization techniques. After integrating the active sources and reactive sources, branch losses of the system have been significantly reduced and the voltage profile has been improved at permissible level. IEEE 33 bus and IEEE 10 bus system has been adopted to validate the test results.
Table of Contents
CHAPTER 1 INTRODUCTION
1.1 Background
1.2 Statement of problem
1.3 Significance of the study
1.4 Objectives
1.5 Limitations of the study
1.6 Organization of dissertation work
CHAPTER 2 LITERATURE REVIW
2.1 Electrical distribution system
2.2 Load Flow
2.3 Distributed Generation (DG):
2.3.1 Solar PV as a DG source
2.3.2 Capacitor Bank as a reactive power source
2.4 Optimization Techniques
2.4.1 Ant Colony Optimization (ACO)
CHAPTER 3 METHODOLOGY
3.1 Data collection
3.2 Load flow analysis using Forward/ Backward sweep algorithm
3.2.1 Backward sweep algorithm
3.2.2 Forward sweep algorithm
3.3 Branch loss calculation
3.4 Estimation of DG sizes
3.5 Location of DG penetration
3.5.1 Generating size and number of ants
3.5.2 Flow chart of Load flow (Forward/ Backward sweep algorithm)
3.5.3 Flow chart of ACO
3.6 Financial analysis of the proposed system
CHAPTER 4 DESCRIPTION OF EXISTING SYSTEM
4.1 Introduction
4.1.1 Inaruwa DCS
4.1.2 Laukahi feeder
CHAPTER 5 RESULTS AND DISCUSSION
5.1 IEEE 10 bus system
5.1.1 Load flow of IEEE 10 bus system
5.1.2 Implementation of ACO techniques in IEEE 10 bus system
5.1.3 DG integration in IEEE 10 bus
5.2 IEEE 33 bus test system
5.2.1 Load flow of IEEE 33 bus system
5.2.2 ACO technique implementation on IEEE 33 bus system
5.2.3 DG integration on IEEE 33 bus
5.2.4 ACO and PSO comparison in IEEE 33 bus system
5.2.5 Summary of Results for IEEE test Radial Distribution System
5.3 Laukahi feeder
5.3.1 Load flow of Laukahi feeder using FBSA
5.3.2 Implementation of ACO in Laukahi feeder
5.3.3 DG integration in Laukahi feeder
5.4 Economic analysis of Laukahi feeder
5.4.1 Revenue generation from the proposed system
CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusions
6.2 Recommendations
6.3 Future work
Research Objectives and Topics
The primary research objective is to improve the voltage profile of the Laukahi distribution feeder within permissible limits while simultaneously reducing branch power losses using optimized placement of Solar PV and capacitor banks. The research utilizes computer simulations in MATLAB to analyze the existing system and apply optimization strategies.
- Voltage profile improvement in radial distribution feeders
- Application of Ant Colony Optimization (ACO) for Distributed Generation (DG) placement
- Technical analysis of branch power losses in electrical distribution systems
- Financial viability and economic assessment of renewable energy integration
Excerpt from the Book
3.2 Load flow analysis using Forward/ Backward sweep algorithm
Substation has been considered as bus 1 (reference bus) having voltage 1∠0 throughout the calculation. In the distribution line where a transformer is getting supplied from, has been considered as bus. Line connecting two bus has been considered as branch. Each branch is having finite resistance and reactance (R & X) values. Further, capacity of the transformer (kVA rating) is denoted by apparent power S.
In a large distribution network, it is challenging to identify the start node and end node of a branch. Each bus, branch and transformer loading should be numbered accordingly, otherwise the result will mislead the general assumption. Initially, the data of the network has been collected and tabulated as in Table 3. For proper identification of a bus, branch and load (active and reactive), a BraBus matrix has been created having size of [Branch number x Bus number]. In this matrix, starting bus and end bus has been denoted by ‘1’ & ‘-1’ respectively, rest of the element will be zero. For the network in Figure 3.2, associated BraBus matrix will be as shown in Table 4. Each column number depicts the bus number having bus voltage and loading of the network. Any column having multiple ‘1’ value reflects the branching bus. In Table 4, bus number ‘2’ is having two ‘1’ denotes the branching bus as shown in Figure 3.2. Every row will have single ‘1’ and ‘-1’, i.e. branch and the corresponding row number is known as branch number. Each branch is holding a current, impedance, and branch loss data [20].
Summary of Chapters
CHAPTER 1 INTRODUCTION: This chapter provides a background on electrical power distribution systems, discusses the statement of the problem regarding voltage profile issues, and outlines the research objectives and scope.
CHAPTER 2 LITERATURE REVIW: This section reviews existing literature on distribution systems, load flow analysis methods, Distributed Generation (DG), and various optimization techniques like Ant Colony Optimization.
CHAPTER 3 METHODOLOGY: The chapter details the data collection process and explains the implementation of the forward/backward sweep algorithm and ACO technique for DG placement in MATLAB.
CHAPTER 4 DESCRIPTION OF EXISTING SYSTEM: This chapter describes the Inaruwa distribution consumer service and the specific Laukahi feeder chosen for the case study.
CHAPTER 5 RESULTS AND DISCUSSION: This chapter presents the simulation results obtained from the IEEE 10 and 33 bus systems and the Laukahi feeder, comparing the performance before and after DG integration.
CHAPTER 6 CONCLUSIONS AND RECOMMENDATIONS: This final chapter summarizes the research findings regarding voltage improvement and loss reduction, and provides recommendations for future work.
Keywords
Voltage Profile, Laukahi Feeder, Capacitor Bank, Solar PV, Distributed Generation, Ant Colony Optimization, Load Flow Analysis, Branch Loss, Distribution System, Renewable Energy, MATLAB, Power Stability, Electrical Network, Distribution Losses, Optimization Techniques.
Frequently Asked Questions
What is the core focus of this research?
This thesis focuses on analyzing and improving the voltage profile and branch power losses in the radial Laukahi distribution feeder in Nepal, particularly in areas suffering from low voltage issues.
What are the primary themes investigated in this study?
The core themes include electrical distribution system modeling, the integration of distributed generation (specifically Solar PV and capacitor banks), power loss reduction, and financial analysis of the proposed grid upgrades.
What is the ultimate research objective?
The main goal is to improve the voltage profile of the Laukahi feeder to stay within permissible limits (0.95-1.05 pu) and minimize branch losses through the strategic placement of active and reactive power sources.
Which scientific methods are employed for analysis?
The study utilizes the Forward/Backward Sweep Algorithm (FBSA) for load flow analysis and the meta-heuristic Ant Colony Optimization (ACO) algorithm for determining the optimal size and location of DG sources.
What content is covered in the main section of the dissertation?
The main section covers the existing system layout, development of mathematical models for load flow and optimization, simulation results on standard IEEE test systems (10 and 33 bus) for validation, and the final implementation on the actual Laukahi feeder.
Which keywords characterize this work?
Key terms include Voltage Profile, Laukahi Feeder, Capacitor Bank, Solar PV, Distributed Generation, Ant Colony Optimization, Load Flow, Branch Loss, and Distribution System.
How does the Ant Colony Optimization (ACO) algorithm work in this context?
ACO is used to find the optimal location and sizing for solar PV and capacitor banks by simulating "ants" that leave "pheromones" on paths; branches with higher potential for loss reduction receive higher pheromone intensity, guiding the selection of the best installation points.
Why was the Laukahi feeder selected for this study?
It was selected because it is a long-distance radial feeder that currently experiences significant voltage drops, frequent power interruptions, and operational challenges for small consumers and mills due to inadequate grid performance.
- Citation du texte
- Biswas Babu Pokharel (Auteur), 2019, Voltage Profile Improvement Analysis of Laukahi Feeder Using Capacitor Bank and Solar PV, Munich, GRIN Verlag, https://www.grin.com/document/465349
