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A novel comprehensive approach to solve a distribution systems' planning problem and to determine the optimal size, location, and technology of the distributed generation (DG) units with respect to the reliability of the system is presented in this paper. The objective functions of this optimization problem are power losses, DGs installation and operation costs, the DG owner's and the Distribution Company's profits as economic objectives. In the proposed method, new indices are defined to evaluate the reliability of the system. These indices calculate energy not supplied and volt ampere reactive not supplied due to active and reactive power shortages. Also, the average interruption frequency (AIF) and average interruption duration (AID) have been considered be minimized during optimization problem. The last two (AIF and AID) are modeled by the adequacy transition rate of DGs among states and are combined as a new objective function. To handle several objective functions, an adaptive fuzzy interactive multi-objective optimization method is used. The results on the IEEE 34-bus and 69-bus power distribution system showed the efficiency of proposed indices for reliability assessment of distribution system planning.

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Conventional methods for solving distribution systems planning (DSP) problem are related to the expansion of distribution systems such as substation reinforcement and feeder replacement. Nowadays, distributed generations (DGs) in various types are a new option for DSP. This paper presents a new approach to solve the DSP problem including DGs with respect to the reliability of the system. The impact of different types of DGs in order to improve the system reliability are modeled and studied by the adequacy transition rate using the Markov model. The objective functions of this optimization problem are power losses, DGs installation and operation cost, reliability indices such as energy not supplied, average interruption frequency, and average interruption duration. Since this optimization problem has a nonlinear complex nature, classical mathematical methods cannot guarantee to achieve the global optimum solution. To solve this problem, a fuzzy interactive multi-objective particle swarm optimization is developed based on Pareto solutions. The model resolves decision variables as follows: location, size, and type of the DG units. The results on IEEE 34-bus distribution system show the effectiveness of the proposed method rather than previous works for reliability assessment.