Multi-Stage Planning of Distribution Networks with Application of Multi-Objective Algorithm Accompanied by DEA Considering Economical, Environmental and Technical Improvements

The regards to widespread impact of distribution networks and ever increasing demand for electricity, some strategies must be devized in order to well operate the distribution networks. In this paper, to enhance the accountability of the power system and to improve the system performance parameters, simultaneous placement of renewable energy generation (REG) sources (e.g., wind, solar and dispatchable distributed generators (DGs)) and capacitors are investigated in a modified radial distribution network with considering ZIP loads. To enhance all network parameters simultaneously to the best possible condition multi-objective functions are proposed and solved using non-dominated sorting genetic algorithm (NSGA II). The employed objectives contain all economical, environmental and technical aspects of distribution network. One of the most important advantages of the proposed multi-objective formulation is that it obtains non-dominated solutions allowing the system operator (decision maker) to exercise his/her personal preference in selecting each of those solutions based on the operating conditions of the system and the costs. It is clear that the implementation of each non-dominated solution needs related costs according to the technology used and the system performance characteristics. However, there is a paucity of objective methodologies for ranking the obtained non-dominated solutions considering economical, environmental and technical aspects. So, in this paper, data envelopment analysis (DEA) is suggested for this purpose. In other words, in this paper, first NSGA II is applied to the siting and sizing problem, and then the obtained non-dominated 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 non-dominated 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. To validate the effectiveness of the proposed scheme, the simulations are carried out on a modified test case 33-bus radial distribution network.

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