IOT-based social-economic management of distribution system with the high penetration of renewable energy sources

Abstract

• A new internet of things frame work is developed for smart power grids with high data measure accuracy and low control latency. • A stochastic framework based on the point estimate approach (PEA) is developed which can handle the uncertainty effects through some limited concentration points. • Social-economic analysic of distribution systems with renewable sources. • Deploying IoT to monitor the system and minimize the cost. • Introducing the modified CSA for solving the problem in the stochastic environment. This paper investigates the social and economic aspects of the distribution system in the presence of different types of renewable energy sources. It suggests an internet-of-thing (IoT) based framework to monitor and measure the distribution system data with higher accuracy and controllability with very low latency. The proposed multi-objective framework considers the cost objective function as the economic index and the total customer interruption costs as the social index. A min-max fuzzy multi-objective framework is designed to optimize the objective functions using the modified clonal selection algorithm (CSA). In order to enhance the social-economic aspects of the distribution system, optimal reconfiguration is analyzed as a useful tool for the operator. A stochastic framework based on the point estimate approach (PEA) is developed which can handle the uncertainty effects through some limited concentration points. The appropriate performance of the proposed model is assessed on the IEEE 69-bus distribution system.