This paper presents a new method to solve the network reconfiguration problem in the presence of distributed generation (DG) with an objective of minimizing real power loss and improving voltage profile in distribution system. 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 location s for installation of DG units. Different scenarios of DG placement and reconfiguration of network are considered to study the performance of the proposed method. The constraints of voltage and branch current carrying capacity are included in the evaluation of the objective function. The method has been tested on 33-bus and 69-bus radial distribution systems at three different load levels to demonstrate the performance and effectiveness of the proposed method. The results obtained are encouraging.

Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation

The loss minimum reconfiguration problem in the open loop radial distribution system is basically one of complex combinatorial optimization, since the normal open sectionalizing switches must be determined appropriately. The genetic algorithm was successfully applied to the loss minimum reconfiguration problem. In the proposed algorithm, strings consist of sectionalizing switch status or radial configurations, and the fitness function consists of the total system losses and penalty value of voltage drop and current capacity violations. The loss minimum reconfiguration problem is formulated as a mixed integer programming problem. The essential components of the genetic algorithm are briefly described. A detailed solution methodology by the use of genetic algorithm is outlined. Numerical examples demonstrate the validity and effectiveness of the proposed methodology. >

Implementation of genetic algorithm for distribution systems loss minimum re-configuration

This paper proposes analytical expressions for finding optimal size and power factor of four types of distributed generation (DG) units. DG units are sized to achieve the highest loss reduction in distribution networks. The proposed analytical expressions are based on an improvement to the method that was limited to DG type, which is capable of delivering real power only. Three other types, e.g., DG capable of delivering both real and reactive power, DG capable of delivering real power and absorbing reactive power, and DG capable of delivering reactive power only, can also be identified with their optimal size and location using the proposed method. The method has been tested in three test distribution systems with varying size and complexity and validated using exhaustive method. Results show that the proposed method requires less computation, but can lead optimal solution as verified by the exhaustive load flow method.

Analytical Expressions for DG Allocation in Primary Distribution Networks

The authors recommend standard load models for power flow and dynamic simulation programs. The goal of this paper is to promote better load modeling and advanced load modeling, and to facilitate data exchange among users of various production-grade simulation programs. Flexibility of modeling is an important consideration. For transient stability, longer-term dynamics, and small-disturbance stability programs, the authors recommend the structure of multiple load types connected to a load bus. Load types are static including discharge lighting, induction motors, synchronous motors, and transformer saturation. For each load type, multiple models may be connected to the bus. For longer-term dynamics programs, a model for LTC transformers is also recommended.

Standard load models for power flow and dynamic performance simulation

This paper presents a new genetic approach for solving the economic dispatch problem in large-scale power systems. A new encoding technique is developed. The chromosome contains only an encoding of the normalized system incremental cost in this encoding technique. Therefore, the total number of bits of chromosome is entirely independent of the number of units. The salient feature makes the proposed genetic approach attractive in large and complex systems which other methodologies may fail to achieve. Moreover, the approach can take network losses, ramp rate limits, and prohibited zone avoidance into account because of genetic algorithm's flexibility. Numerical results on an actual utility system of up to 40 units show that the proposed approach is faster and more robust than the well-known lambda-iteration method in large-scale systems.

Large-scale economic dispatch by genetic algorithm

A multi-term distribution system expansion planning method is proposed. Many mathematical programming approaches have been proposed in this area. However, because of the complexity of the problem or the limitations of a computational time and memory size, these methods can only be applied to a small-scale system. To solve large-scale problems, the authors propose a new decomposition algorithm based on the branch exchange method. A n-years planning problem is decomposed into n one-year planning problems, and one-year results are coordinated through what can be called the forward/backward path. The validity and effectiveness of the algorithm are ascertained by applying it to real-scale numerical examples. >

Multi-year expansion planning for distribution systems

The authors investigate the voltage stability problem based on singular perturbation theory. Possible voltage instability patterns are classified into four types (I, II-1, II-2S, and II-2D) according to the mechanism causing voltage instability. Several features of each type of instability are studied as well as their analysis methods. Voltage instability tends to begin with type I and then leads to one of the remaining types. The load flow Jacobian can be an effective index to approximately assess type I and II-2S instabilities, while types II-1 and II-2D require direct nonlinear analyses and eigenvalue analyses, respectively. The validity of the classification proposed has been verified through numerical simulations and theoretical analyses which take into account dynamic characteristics of generating units, loads, and tap-changing transformers. >

An investigation of voltage instability problems

The authors present a multistage branch exchange algorithm for solving expansion planning problems in distribution systems. Since it is formulated as a combinatorial optimization problem, it is difficult to solve such a large-scale problem accurately. Therefore, in order to find a solution quickly, the authors have developed a method based on the branch exchange technique which is able to find an approximate solution. To obtain a more accurate solution, the multistage branch exchange algorithm is introduced. The validity and effectiveness of the proposed algorithm are demonstrated by applying it to a 59-node, 69-branch numerical example system. >

Distribution systems expansion planning by multi-stage branch exchange

This paper investigates the dynamic behaviour of tap changing operations in tap change under load (TCUL) transformers. Interactions among multiple TCUL controls cause oscillatory behaviour in tap changing actions, which unnecessarily increases tap operations before they reach equilibrium. Sufficient conditions for stability are derived and features of the phenomena are examined through theoretical analysis as well as through numerical simulation.

Interaction among multiple controls in tap change under load transformers

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Minoru Kitagawa

Author Tools

Chat about Author