Feed-in Tariff (FIT) program has significantly contributed to the diffusion of photovoltaics (PV). Japanese FIT is unique in terms of the purchase rate structure in which only the surplus is sold at the higher price than grid electricity (net metering) while all the generated electricity does (gross metering) under FIT in many countries. This paper evaluates how the purchase rate structure alters the economic performance of PV owners. The result revealed that, under net metering FIT structure, the lower electricity demand during daytime households gain the higher economic benefit while energy demand of household does not influence the economic performance under gross metering FIT. In order to evaluate this purchase rate structure on the amount of surplus electricity and surcharge compensated by all electricity customers, we estimate them while assuming PV diffuses on a large scale in Kinki region from households with the highest economic performance. The result showed that the purchase rate structure significantly alters the amount of surplus and the surcharge per generated electricity.

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Discussed here is the experiment of power monitoring using new wireless sensor nodes in home, business, data-center, and commercial areas. From these experiments, we confirmed the ease of our monitoring system installation, and the stability of receiving data from a high number of sensor-nodes. The power “profile” of equipment obtained in several kinds of areas effectively presented the key features of equipment-usage. It would be possible to reduce the waste of power consumption by regularly observing the power “profile” every day and making comparisons between similar sites or equipment. The preference test for our monitoring system presented the possibility of our sensor-nodes being accepted in the home. However, in order to widely distribute our wireless sensor-nodes, it will be essential to achieve “maintenance-free” and “low-cost” sensor-nodes.

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Discussed here is electricity monitoring using wireless sensor nodes in 10 convenience stores. Through field experiments, we clarified the reason why energy-saving of convenience stores is difficult. Simply said the answer is “the effect of measures for saving power does' have a close connection with reduction of electric bill. Many equipment without display cooler and freezers and air-conditioning has stable and small power consumption in average temperature. If we can cut these power consumption, their values are small in comparison with total power consumption. Power consumption of display cooler and air-conditioning has large part of total power consumption, and fluctuate largely every day due to changing temperature and human behavior. This fluctuation masks the effect of individual measures. Therefore, we can’t obtain the evidence of the effect of measures from electric bill. How can we know adequate level of power consumption, in other word “reference” for power-saving? In order to make “reference” for achieving power profiling, it would be necessary to gather and analyze a large amount of power consumption data during a long period of time with several kinds of equipment.

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