In 2012, the Japanese government enforces Feed-in Tariff and promotes the installation of renewable energy into the power system. In particular, photovoltaic (PV) system has been installed in large scale. Net load curve in the power system where large amount of PV system is installed is lower than the conventional load curve in the daytime. In this paper, the long term fluctuation of future net load curves in Kansai area which are estimated by distribution of insolation, forecasting data of PV capacity and observed load data in KEPCO is evaluated. The PV capacity forecasting is based on open data of PV capacity in cities, towns and villages provided by Agency for Natural Resources and Energy.
The result shows that the phased change of the fluctuation properties is occurred as the large amount of PV system is installed into conventional power system. In particular, the load curves in morning turned in decreasing trends from increasing trends. Moreover, the cases of rise in net load during over 6 hours are increased.

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The penetration of renewable energy is advanced to implement low-carbon society. Especially the increase of the photovoltaic generation energy is remarkable. But as a result, the trend that net electricity demand is decreased in the daytime and is increased suddenly in the evening, which is called ‘Duck-Curve phenomenon’ become apparent, and the destabilization of the utility grid caused by the fluctuation of photovoltaic generation power output. To solve this problem, the virtual power plant is planned as one of the solutions, and the battery aggregation using the distributed and cooperated rechargeable batteries is considered as one of the technical elements. One of the strong candidate of rechargeable battery is lithium ion batteries. To maximize the profit of the battery aggregation, it is necessary to diagnose the degradation in real time and estimate the cost effectiveness of lithium ion batteries. We found the convenient technique of diagnosis which can be done under operation of lithium ion batteries and battery management systems. To contribute to optimum system operation of the distributed and cooperated rechargeable batteries, we propose a new cost effectiveness index of lithium ion batteries based on this technique.

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