Agent Based Load Management System for a Smart Power Distribution System

Inherently, electric power system is exceptionally complex as far its planning, construction and operation is concerned. Adding to that, advancement in the way the electric power is consumed and ascending electrical power demand makes the traditional electric power system.s planning, monitoring and control an uphill struggle. This thesis work is focused on the improvement of power distribution system. Improvement in the control system, information system, and management system of power distribution system is transforming the grounds on which the most of the traditional power system has been operated.;The present thesis work has been motivated to be a part of an attempt to make the electric power grid smarter. Smart Grid initiative by various power industrial units around the globe is a revolutionary attempt to impart intelligence and robust technology into the existing electric grid to make it highly reliable with effective capacity utilization. This thesis work presents a novel approach to accommodate distributed generation resources in the power distribution system helping to reduce the peak power demand by 15 percent.;Demand dispatch method which is a novel approach to demand response is implemented in this thesis. Demand dispatch is the capability to aggregate and precisely control individual loads on command. The dispatch algorithm makes use of controllable loads which can be turned on and off with unnoticeable interruption. The load is forecasted and it is dispatched accordingly using distributed generation resources and controllable loads there-by helping to reduce peak demand.;Multi-agent system is adopted to manage the demand dispatch simulation. Multi-agents are collection of agents which are capable of perceiving the environment in which they are located and act on it by communicating with each other to achieve the goals. Load is forecasted in MATLAB and multi-agents programmed in JADE utilize the forecasted load data to dispatch the load in such a way so as to reduce the peak demand. Agents are located at demand aggregator level, zone level and DG level. These agents communicate and negotiate to dispatch the load appropriately based on resources and load availability