A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid

One of the most important aims of the sizing and allocation of distributed generators
(DGs) in power systems is to achieve the highest feasible efficiency and performance
by using the least number of DGs. Considering the use of two DGs in comparison to a single
DG significantly increases the degree of freedom in designing the power system. In this
paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network
have been investigated with three objective functions which are the reduction of network
losses, the improvement of voltage profiles, and cost reduction. In this way, by using the
backward-forward load distribution, the load distribution is performed on the 33-bus network
with the power summation method to obtain the total system losses and the average
bus voltage. Then, using the iterative search algorithm and considering problem constraints,
placement and sizing are done for two DGs to obtain all the possible answers and next,
among these answers three answers are extracted as the best answers through three methods
of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using
the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the
algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with
the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the
origin, three answers are extracted as the best answers. Finally, the answer which shows
the least difference among the responses of the iterative search algorithm is selected as the
best answer. The simulation results verify the performance and efficiency of the proposed
method.