Sharif Digital Repository

In recent years, the pace of increment in electrical energy consumption is getting faster. Establishing new power-plants to keep a balance between generation and consumption not only has a high investment cost but also is a time consuming procedure. Thus, several studies have focused on the demand side management. Residential consumers possess remarkable portion of total electricity consumption. Accordingly, at first, the appropriate residential demand response program is selected based on presented experimental criteria. In the next step, since the network reliability is an important issue to the operators, the impact of implementation of the demand response program is studied on the... 

This study investigates consumers’ response to changing the household electricity meter from single stroke case to three stroke case. Existence of different prices in different hours during the day is the advantage of three stroke electricity meters compared to single stroke ones. Electricity bill data of 19,742 subscribers, in Tehran Interior Region 2, during the period 1387 to 1393, has been used to evaluate this policy. Subscribers who always use only single stroke electricity meters or three stroke ones are considered as the control group; and subscribers who have experienced electricity meter change during the period are considered as the experimental group. Changing electricity meters... 

Residential demand response is an appropriate control tool for improving system reliability. This project intends to establish a model to activate residential demand response to improve distribution network reliability. Two centralized and decentralized models are proposed. The models aim at minimizing the damage cost imposed by load curtailments following unexpected events. In the models, it is supposed that distribution system operator (DSO) and responsive customers already signed a contract authorizing the DSO alters the operation of responsive appliances whenever system reliability is jeopardized. In centralized framework, Responsive customers deliver the technical data of their... 

According to increasing energy demand in Iran and the world, the role of natural gas as a relatively clean and cost-effective source has received more attention. Given the high share of the residential sector in the country's natural gas consumption, providing a model for forecasting the demand of this sector is of great importance for policy makers and decision makers in this field. In the present study, we employ three popular methods of machine learning, support vector regression, artificial neural network and decision tree to predict the consumption of natural gas in the residential sector in Tehran according to meteorological parameters (including temperature, precipitation and wind... 

Distribution companies typically use ADMD and coincidence factors to calculate aggregated loads. However, these factors have a significant impact on the selection of the optimal capacity of distribution network equipment; But so far, comprehensive studies at the level of single customers have not been implemented on the calculation of these factors. In this work, a comprehensive study has been conducted on residential customers in Tehran and the consumption data of 2121 residential customers, which were recorded during the summer of 2020, are used. The data were collected in two separate sets to investigate the effect of two factors: the type of cooling load and the welfare level of...