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.
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:
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.
Many factors to consider before concluding "best" method. For instance, the application (long-term or short-term planning, dynamic or static system modeling .., etc.), the ownership, and the objective. These are just some of the examples of the different considerations before choosing your appropriate methodology.
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
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.
Dear Amir , I guess formulation of the problem with inclusive parameters as constraints is the first step. Second , the network can be reconfigured (rather than fixed) depending on load . Since I like graphs , this would be interesting
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