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Development of smart grid technology provides an opportunity to various consumers in context for scheduling their energy utilization pattern by themselves. The main aim of this whole exercise is to minimize energy utilization and reduce the peak to average ratio (PAR) of power. The two way flow of information between electric utilities and consumers in smart grid opened new areas of applications. The main component is this management system is energy management controller (EMC), which collects demand response (DR) i.e. real time energy price from various appliances through the home gateway (HG). An optimum energy scheduling pattern is achieved by EMC through the utilization of DR information. This optimum energy schedule is provided to various appliances via HG. The rooftop photovoltaic system used as local generation micro grid in the home and can be integrated to the national grid. Under such energy management scheme, whenever solar generation is more than the home appliances energy demand, extra power is supplied back to the grid. Consequently, different appliances in consumer premises run in the most efficient way in terms of money. Therefore this work provides the comprehensive review of different smart home appliances optimization techniques, which are based on mathematical and heuristic one.

With the development of smart grid technology, residents can schedule their power consumption pattern in their home to minimize electricity expense, reducing peak-to-average ratio (PAR) and peak load demand. The two-way flow of information between electric utilities and consumers in smart grid opened new areas of applications. In this chapter, the general architectures of the home energy management systems (HEMS) are introduced in a home area network (HAN) based on the smart grid scenario. Efficient scheduling methods for home power usage are discussed. The energy management controller (EMC) receives the demand response (DR) information indicating the Time-of use electricity price (TOUP) through the home gateway (HG). With the DR signal, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG.

With the development of smart grid technology, residents can schedule their power consumption pattern in their home to minimize electricity expense, reducing peak-to-average ratio (PAR) and peak load demand. The two-way flow of information between electric utilities and consumers in smart grid opened new areas of applications. In this chapter, the general architectures of the home energy management systems (HEMS) are introduced in a home area network (HAN) based on the smart grid scenario. Efficient scheduling methods for home power usage are discussed. The energy management controller (EMC) receives the demand response (DR) information indicating the Time-of use electricity price (TOUP) through the home gateway (HG). With the DR signal, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG.

With the advancement of technology, the dependency on the electrical energy has been increased greatly. Computer and telecommunication networks, railway network banking, post offices, and life support systems are a few applications that cannot function without electricity. At the same time, these applications demand qualitative energy. However, the quality of power supplied is affected by various internal and external factors of the power system. Harmonics, voltage, and frequency variations deteriorate the performance of the system. Voltage sag/dip is the most frequent problem and there are many methods to overcome this problem. The use of FACT devices is an efficient one. This chapter discusses an overview of the FACT device known as dynamic voltage restorer (DVR) in mitigating voltage sag. The strategy to control this device is also presented. The proposed control strategies are simulated in MATLAB SIMULINK environment and analyzed. The method is utilized and discussed briefly.