What is the best method that can be adopted for finding DG PLACEMENT in radial network ?
Amir,
Difficult to point out a method that is "the best" !! There are various considerations...
Why don't you look up the literature available on the IEEE Digital Library ??
With best wishes.
-Sanjay
There are so many methods available for placement i.e. loss sensitivity factor , voltage stability index concept, and the location is also found out directly by analytical approaches and nature inspired algorithms. But specifically we cannot said this the best method, each method has its own advantages and disadvantages.
There is nothing like best method ever because every method will have its own limitations and assumptions. But some of the popularly known methods are bus voltage sensitivity analysis, loss sensitivity analysis etc., You can use any online algorithms also. Please find the attachment it may be useful to you.
There are many indicators such as Loss sensitivity factor, power loss index, etc... However, to find location using your optimization method will be better. Let algorithm search for Optimal location.
Hello Amir,
I did a comparison between optimization and analytical method on placement and sizing of DG. My conclusions and suggestions can be referred from the following publication:
https://www.researchgate.net/publication/284550417_Optimal_Allocation_and_Sizing_of_Distributed_Generators_in_Autonomous_Microgrids_based_on_LSF_and_PSO
Conference Paper Optimal Allocation and Sizing of Distributed Generators in A...
Hi Amir,
If you do not want to have a contribution on your solution method, I suggest you for linearizing your model (formulations) and then use a Mixed-Integer Linear Programming (MILP) solver like CPLEX (in GAMS). So, you can compare the results in different cases easily without concerning about solution errors.
I suggest you to have a look on "Comparison of optimal DG allocation methods in radial distribution systems based on sensitivity approaches" by V V S N Murty and Ashwani Kumar.
It was published under International Journal of Electrical Power & Energy Systems 53, 450-467.
In this journal, they compared with different existing methods and proved that proposed method is better one than existing.
first you must decide your objective function to minimize or maximize certain performance such as power losses, voltage improvement, stability improvement, or cost, then you can obtain the best location and size according to these functions using optimization algorithms such as particle swarm, bat inspired, genetic algorithm, etc
Particle Swarm Optimization technique is used to identify the optimum generation capacity of the DG and its location to provide maximum power quality improvement bus test system, because It does not require a good initial solution to start its iteration process
Hi Amir,
It totally depends to your objective function. I mean it depends on what you want to consider: Loss, Minimum power generation cost, Voltage constraint, Transmission line congestion and e.t.c.
After specifying the objective function, you can select the best method in regards to the function.
hi
Actually, this problem is an optimization problem, so, any optimization algorithm can be used to solve it
Estimado Amir Hossein Valipour
Gracias por la invitación, voy a estar al tanto de la evolución de esta red de discusión y afán argumento para aprender más sobre él.
En lo personal no tengo suficiente práctica y experiencia tecnológica en el campo de la ingeniería para hacer contribuciones significativas.
Saludos
El Dr. José Luis García Vigil
Dear Amir Hossein Valipour
Thank you for your invitation, I will be aware of the evolution of this network of discussion and argument eagerness to learn more about it.
Personally I do not have enough practice and technological expertise in the field of engineering to make significant contributions.
regards
Dr. Jose Luis Garcia Vigil
Hi , I attach the optimal point -to-point network deep network of distributed generation , where we have the highest voltage drop in the distribution network. Distributed generation network describes the probing attachments that help you
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