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Daily increasing demand of electrical energy and also recent developments in technology of distributed generations (DGs) have created special interest in using these units. On the other hand, capacitor insertion in the distribution feeders has been implemented by distribution companies for several years to reduce power loss and improve the voltage profile. Hence, according to the joint role of distributed generation units and capacitors, their optimal allocation will be influenced by each other. Therefore, in order to achieve the maximum benefits, this paper has discussed the optimal siting and sizing of DG resources and capacitors. One of the characteristics of the proposed method is that all technical and economical factors associated with installation of DGs and capacitors will be priced. For this purpose, all effective factors in optimal allocation and sizing of DG resources and capacitors are extracted and priced. For example, for the first time, the factor of voltage profile has been priced by the number of tapping. Using this approach, weighting the objective function parameters would be no more required. One of the other features of this paper is presenting an algorithm to determine the optimum number of DGs and capacitors. With this algorithm, power companies can find the optimum number of DGs and capacitors in the network they cover. The proposed method in this paper is tested on the 97-bus network of Bakhtar Regional Electrical Company in Iran Country.

An important challenge in protection of a microgrid is the process of fault detection, considering the uncertainties in its topologies. Equally important is the evaluation of proposed methods as their incorrect performances could result in unreasonable power outages. In this paper, a new fault detection and characterization method is introduced and evaluated subject to the uncertainties of network topologies. The features of three-phase components together with the positive, negative and zero sequences of current and voltage waveforms are derived to detect the occurrence of a fault, its location, type and the engaged phases. The proposed method is independent of the microgrid topology. To evaluate the performance of the proposed method in various network topologies, a Monte Carlo scheme is developed. This is done by computing the expected energy not-supplied reliability index and the percentage of successful performance of the fault detection. Simulation results show that the proposed method can detect faults in various microgrid topologies with a very high degree of accuracy.

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