Combination of the information technology and the power engineering is the feature of next-generation grid. Depending on bidirectional communications, demand side management (DSM) aims at optimizing the electricity usage pattern of customers to improve energy efficiency and alleviate environmental impact. In this study, a DSM optimization algorithm is designed, which can perform load shifting on a household level based on the Time-of-Use strategy. Several flexible appliances, plug-in hybrid electric vehicle (EV) charging and rooftop photovoltaic (PV), are considered. Results show that the daily electricity cost has declined by 19% after the optimization. A 12% reduction of the domestic carbon emission is also achieved from the variation of grid carbon intensity and energy provided by rooftop PV. It is validated that with the growing penetration rate of EVs and renewable energy generation, smart scheduling of household load can greatly benefit grid stability and energy efficiency.

Microgrid is playing an increasingly important role in making the utility grid more intelligent and efficient, since it can make better use of the renewable energy resources to simultaneously relieve the grid supply pressure and reduce carbon emissions. Innovations in electric technologies, information and communication technologies can facilitate better management of the power transmission and distribution in the microgrid. This paper proposes an optimization strategy, which considers distributed generations, photovoltaics and wind turbines, based on particle swarm optimization for the management of the microgrid. Simulation results demonstrate that with the optimal generation resources management and the effective use of demand side management in the microgrid, the proposed strategy can reduce electricity costs by 29.283% and 32.158% on weekdays and weekends, respectively.

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