Electricity theft is always a ticklish problem faced by utilities around the world. To mitigate and detect energy theft, utilities are leveraging on the consumers' energy consumption dataset obtained from advanced metering infrastructure to identify anomalous consumption patterns. However, real energy theft sample as well as the distribution station smart meter readings do not exist in Malaysia because smart grid is not fully implemented. Therefore, we design and construct a small-scaled advanced metering infrastructure test rig in the laboratory to evaluate the performance and reliability of our previously proposed linear regression-based detection schemes for energy theft and defective meters in small grid environment. Simulations and electrical tests are conducted and the results show that the proposed algorithms can successfully detect all the fraudulent consumers and discover faulty smart meters in smart grids.

This paper focuses on the load scheduling problem in both demand-side management and supply-side management for household users in a smart grid. Linear programming models have been developed either to minimize the energy cost in demand-side scheduling, or to maximize the load factor for supply-side scheduling. The proposed models provide various flexibilities to the end users by allowing them to define multiple time intervals for the operations of intended appliances, and to pre-set if an appliance should be operated with or without interruption. Simulations performed on the load scheduling of one individual household give promising and convincing results. The proposed model in its linear programming form promises a fast and convergent solving process with a guaranteed exact solution. These added features make the proposed load scheduling framework more practical and realistic for real world applications.

In the present work, the Crank-Nicolson implicit scheme for the numerical solution of nonlinear Schrodinger equation with variable coefficient is introduced. The Crank-Nicolson scheme is second order accurate in time and space directions. The stability analysis for the Crank-Nicolson method is investigated and this method is shown to be unconditionally stable. The numerical results obtained by the Crank-Nicolson method are presented to confirm the analytical results for the progressive wave solution of nonlinear Schrodinger equation with variable coefficient.