As home energy use is increasing and renewable energy systems are deployed, home energy management system (HEMS) needs to consider both energy consumption and generation simultaneously to minimize the energy cost. This paper proposes a smart HEMS architecture that considers both energy consumption and generation simultaneously. ZigBee-based energy measurement modules are used to monitor the energy consumption of home appliances and lights. A PLC-based renewable energy gateway is used to monitor the energy generation of renewable energies. The home server gathers the energy consumption and generation data, analyzes them for energy estimation, and controls the home energy use schedule to minimize the energy cost. The remote energy management server aggregates the energy data from numerous home servers, compares them, and creates useful statistical analysis information. By considering both energy consumption and generation, the proposed HEMS architecture is expected to optimize home energy use and result in home energy cost saving.

As energy consumption in residential areas is rising, residential homes have deployed a photovoltaic (PV) system to save energy cost. The PV system needs to be continuously monitored to maintain its appropriate performance. In addition, it is desirable to monitor each PV module because one abnormal PV module affects the whole PV system. In this paper, the power line communication (PLC) compliant with HomePlug is adopted to monitor each PV module. The system architecture is composed of three components: PLC modem, renewable energy gateway (REG), and smart device application. The PLC modems are deployed on each PV module and monitor it. The REG aggregates and stores the monitored data from the PLC modems and the inverter. The smart device application retrieves the stored data from the REG to inform users of the status of the PV system. Users can browse and figure out the PV system performance in detail. The proposed system is installed in the field that is composed of sixteen 210W PV modules and a 3kW inverter. This scheme will maintain the performance of a PV system and contribute to enhancing home energy management system.

Geographic routing has been considered as an efficient, simple and scalable routing protocol for wireless sensor networks, since it exploits pure location information instead of global topology information to route data packets towards a static sink. Recently, a number of research works have shown that mobile sinks can achieve high energy efficiency and load balance than static ones. In order to receive data packets continuously, a mobile sink must update its location to the source frequently. However, frequent location updates of mobile sinks may lead to both rapid energy consumption of the sensor nodes and increased collisions in wireless transmissions. The authors propose a novel geographic routing for mobile sinks to address this issue. The proposed scheme takes advantage of wireless broadcast transmission nature of wireless sensor nodes. When a sink moves, the new location information is propagated along the reverse geographic routing path to the source during data delivery. Analysis and simulation results indicate that elastic routing is superior to other protocols in terms of control overhead, data delivery delay and energy consumption.

A photovoltaic (PV) system has been widely deployed in residential areas to reduce energy cost. However, it is not monitored in detail or managed in a user-friendly manner in many cases. Therefore, a PV monitoring system needs to provide both detailed monitoring of each PV module and a user-friendly way of access to the monitored data. In addition, the PV monitoring system needs to be low-cost to be widely deployed. To achieve these needs, this paper proposes a user-friendly PV monitoring system based on a low-cost power line communication (PLC). For cost reduction, the PLC module is developed without a communication modem. For detailed monitoring, the PLC modules are installed at each PV module; the data logger aggregates the monitored data of each PV module and the PV inverter. For userfriendly access, a smart app is used to show the aggregated data graphically. In the field test, the developed PV monitoring system is installed at a real PV system composed of sixteen 400 W PV module; users can figure out the status of the whole PV system through a smart device. This scheme is expected to reduce energy cost in residential areas by maintaining a PV system performance.

This paper describes smart home energy management system (HEMS) that includes both energy consumption and renewable energy generation. ZigBee is used to measure and transfer the power and energy of home appliances at the outlets and the lights. Power line communication is adopted to monitor solar panels. By considering both energy consumption and generation simultaneously, the proposed HEMS can optimize home energy use and result in energy cost saving.

Panel-level photovoltaic (PV) monitoring localizes abnormal PV panels, enables easy repair, and helps maintain the performance of the PV system. Panel-level PV monitoring system needs to be low-cost so that it can be widely deployed. Synchronization of monitoring time between PV panels is also needed to compare them under the same conditions. Simple fault detection scheme is needed to decide which PV panel is abnormal. For low-cost modules, this paper proposes a low-cost power line communication (PLC) module to monitor four PV panels simultaneously. It can reduce the cost of monitoring modules down to nearly one fourth according to the cost analysis. For time synchronization, a measurement and query scheme is proposed. At the measurement phase, the states of PV panels are measured simultaneously; at the query phase, the measured data are transferred one by one. For fault detection, the mean voltage of PV panels and voltage drop threshold are used. Voltages below the mean by the threshold are considered as abnormal. The proposed system was tested in the real field; it found and localized an abnormal PV panel. The proposed scheme is expected to widely spread the panel-level PV monitoring and help maintain the PV system performance.