Madhavan, Adarsh2013-05-222013-05-222013-05-222013http://hdl.handle.net/10012/7554Although Voltage Varying (VV) strategies like Conservation Voltage Reduction (CVR) are widely used by utilities to reduce the overall energy consumption and peak power demand of distribution feeders, it is aberrant among industrial customers. This research proposes a Voltage Varying (VV) strategy for industrial customers that takes into account their complex characteristics and unique set of constraints. Unlike VV strategies for Local Distribution Companies (LDC), those for an industrial customers are far more complex, and require specific c load modelling and process estimation to infer the optimal operating voltage for the industrial load. The proposed VV technique referred to as Voltage Optimization (VO), is a generic and comprehensive framework that seeks to reduce the energy consumption of the industrial load vis-~a-vis the bus voltage. It utilizes a Neural Network (NN) model of the industrial load, trained using historical operating data, to estimate the real power consumption of the load, based on the bus voltage and overall plant process. This load model, is incorporated into the proposed VO model, whose objective is the minimization of the energy drawn from the substation and the switching operations of Load Tap Changers (LTC). The proposed VO framework is tested on load models developed using simulated and real data. Results suggest that the proposed technique can be successfully implemented by industrial customers or plant operators to improve their energy savings, in comparison to existing VV techniques.enVoltage optimizationindustrial loadsMaster ThesisElectrical and Computer Engineering