Research Specifications

Optimal planning of electric distribution networks is a complicated multi-objective and multi-constraint problem. This context will be more challenging, regards to the constraints rising from the nature of smart grids. Optimal planning in such a network needs advanced strategies which consider both technical and economical aspects. Distributed generation (DG) and Capacitor banks have attracted a great attention due to their ability in power loss reduction; voltage profile adjustment; voltage stability improvement and emissions reduction. Ever increasing use of electricity imposes a need to enhance the accountability of the power system and improve the system performance parameters. In the literatures, the optimal sizing and siting of several combinations of DGs and/or capacitors have been studied considering different objective functions. The differences are mainly in the problem formulation, methodology and constraints. In this paper, a new approach for optimal allocation of DGs and Capacitor banks, separately and simultaneously, is proposed. The proposed scheme evaluates both the technical and economical aspects with considering several objective functions. The proposed method can easily be expanded with more objectives to cover all the network planners’ preferences. The proposed scheme is the combination of an intelligent algorithm and data envelopment analysis (DEA). So, in this paper firstly intelligent algorithm is applied to the sitting and sizing problem, and then the obtained optimal solutions are prioritized by DEA. The significant advantage of using DEA is that, there is no need to impose the decision maker's idea into the model. And ranking is done, based on the efficiencies of the optimal solutions. The most efficient solution is the one which has improved network parameters considerably and has lowest costs. So, using DEA gives a realistic view of solutions and the provided results are for all, not for a specific decision maker. The proposed scheme is