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Methods of accurately determining the efficiency of motors in situ without costly plant downtime are required to implement online motor management strategies that can lead to energy and cost savings. An ideal method must perform in practical power system conditions where there is variation in the supply voltage. An improved non-intrusive compensated slip technique utilising vibration signature analysis has been proposed for accurately estimating induction motor efficiency. The performance of this technique is evaluated through experimental data under ideal and non-ideal supply voltage conditions. The proposed method of estimating motor efficiency is found to be accurate and easy to implement. The proposed technique is robust in under-voltage and over-voltage power supply conditions. [ABSTRACT FROM AUTHOR]

An adaptive real-time electricity pricing and optimal control system based on energy management of buildings is presented. This is made in the framework of a smart-grid according to energy demand and time-of-use (TOU) electricity tariff in conjunction with a model predictive control (MPC). The developed model is considered as a multiple single input single output MPC system that acts at a different rate of TOU- electricity tariffs (off-peak, standard and peak). A smart selective timer switching system links one to the other. The performance of the model design is expressed through the simulation results of the adaptive TOU-MPC for commercial buildings. [ABSTRACT FROM AUTHOR]

Smart grid technologies are a catalyst for the modernisation of the electrical system whilst satisfying all electrical power stakeholders. The application of intelligent systems results in more flexibility and reliability. This paper presents a dynamic energy management system for a microgrid connected to a grid for residential application. The system models a smart metering system to collect data from different components of the electrical system. A grid-tied photovoltaic and energy storage system model is optimally designed. The model uses the framework of a smart grid based on demand response and energy pricing to coordinate the energy flow of a home. Three optimal control scenarios are formulated, where the opportunity energy is considered to be injected to the main grid. These scenarios are two linear methods (open and closed-loop models) and a quadratic approach based on model predictive control. It was observed that the energy storage system plays an essential role in the context of energy-saving and gain from the demand side. The models provide benefits in terms of energy-saving and energy cost. The performance of dynamic modelling is validated with the experimental data from the smart metering system. • Formulates linear and quadratic model of smart home energy coordination for the intelligent microgrid application. • Designs optimal energy flow control strategies by the use of a smart metering system based on wireless communication. • Compares the dynamic performance of the energy management schemes based on demand response. • Provides the consumer with an opportunity of selling the energy to the utility for a microgrid connected to the main grid. • Applies system analysis on the energy components of a residential home. [ABSTRACT FROM AUTHOR]