In this paper, the Gray Wolf Optimization Algorithm (GWO) will be used for planning a hybrid AC/DC distribution network, and results from the economical and technical point of view will be compared to those of conventional methods, such as Genetic Algorithm (GA). In the proposed model, the objective function is to minimize the Net Present Value (NPV) of the optimal solution. The planning will be done for an empty area, which already doesn’t have any distribution network, at the LV level. In the proposed method, the buses and feeders of the network could be AC or DC. Also, there are AC and DC load points and Distributed Generations (DGs) in the planning area. It should be mentioned that in this paper, the uncertainty of load demand and production of DGs has been regarded. Finally, after planning the distribution network as a pure AC and a hybrid AC/DC configuration for a 14-bus test network, NPV, loss of system and the convergence time of the GWO algorithm will be compared to ones from GA, and advantages of the prior will be shown. تفاصيل المقالة

In recent years, due to developments in the electricity industry, the use of smart meters has increased worldwide. Smart meters allow the collection of large amounts of microdata on power consumption. The data collected by smart meters can be used in various cases. Since the load duration curve is of great importance in the study of power systems in this paper, the purpose is to obtain the load duration curve of consumer groups using raw smart meter data. The data collected by smart meters reflects the behavior of subscribers, so by categorizing this data, the behavior of subscribers can be categorized, and thus the continuous load curve can be calculated. However, due to challenges such as being raw data collected from smart meters, the presence of anomalous data, and the presence of lost data, the data collected by smart meters need to be pre-processed and corrected. This paper presents an approach for pre-processing and modification of raw data received from smart meters and using them to calculate the load duration curve and other uses. First, the preprocessing and modification of smart meter data on two data sets collected from Alborz Power Distribution Company is done based on the presented method; Then these data are clustered based on the k-means clustering algorithm, and finally, load duration curve is obtained for each cluster. تفاصيل المقالة