Measurements at the level of active distribution networks can be classified into three major groups. Data collection and transmission involve the time interval of several seconds for the first category, several minutes to 24 h for the second category, and finally, several weeks to several months for the third category. Considering this three-level classification of the measurements, state estimation by these data should deal with three kinds of heterogeneous data, but it has undesirable effects on the state estimation process, such as lower accuracy of the results. Despite the existence of heterogeneous data and different time rates, this study presents a state estimation model for updating measurement devices in each of the categories, aiming at establishing coordination among the measured data and increasing the accuracy of the estimation. The opportunities and limitations of the proposed model are compared to those of the conventional models. To illustrate the effectiveness of the proposed method, two IEEE standard systems 34-bus and 123-bus, have been used. The experimental network includes various load patterns, as well as distributed generation sources whose uncertainty is considered in the proposed model. 1Various measurement devices are currently installed on distribution networks. They are compared in Table 1.

In this paper, a novel high step-up direct current (DC)-DC converter, using switchedcapacitor (SC) cells, is proposed. Upon turning a set of switches in this converter on/off, the capacitors are connected to each other in a circuit configuration, and charged through the source. Then, the capacitors are reconnected in a different configuration by turning the switches off/on, and generate high output voltage. This modular converter is able to produce flexible, high output voltage from low input voltage sources. The proposed converter is accordingly studied and analysed. To verify the operation of the given converter, it is simulated via the MATLAB-based Simulink software, and an experimental prototype is subsequently implemented on a laboratory scale.