There are several methods of peak-shaving, which reduces grid power demand, electricity bought from electricity utility, through lowering “demand spike” during On-Peak period. An optimization method using linear programming is proposed, which can be used to perform peak-shaving of grid power demand for grid-connected PV+ system. Proposed peak shaving method is based on the forecast data for electricity load and photovoltaic power generation. Results from proposed method are compared with those from On-Off and Real Time methods which do not need forecast data. The results also compared to those from ideal case, an optimization method which use measured data for forecast data, that is, error-free forecast data. To see the effects of forecast error 36 error scenarios are developed, which consider error types of forecast, nMAE (normalizes Mean Absolute Error) for photovoltaic power forecast and MAPE (Mean Absolute Percentage Error) for load demand forecast. And the effects of forecast error are investigated including critical error scenarios which provide worse results compared to those of other scenarios. It is shown that proposed peak shaving method are much better than On-Off and Real Time methods under almost all the scenario of forecast error. And it is also shown that the results from our method are not so bad compared to the ideal case using error-free forecast.

This study shows an application method of Micro Grid integrating Solar Energy Seasonal Storage (SESS) based on the analysis of time-variant load characteristics of electric railway. Micro Grid includes various renewable energy generation plants as like wind farm, photovoltaic, small hydro, fuel cell, etc. and some energy storage systems to meet the balance between generation production and demand. The essential concept of this paper is the connection and integration between electric railway and Micro Grid including SESS which is able to control power system frequency. This new concept for power system stabilization would be tested in an independent Micro Grid site and some detail application methods would be evaluated for the commercialization.