Wind Power Forecasting using an Artificial Neural Network for ASPCS

In order to use effectively renewable energy sources, we propose a new system, called Advanced Superconducting Power Conditioning System (ASPCS) that is composed of Superconducting Magnetic Energy Storage (SMES), Fuel Cell-Electrolyzer (FC-EL), hydrogen storage and DC/DC and DC/AC converters in connection with a liquid hydrogen station for fuel cell vehicles. The ASPCS compensates the fluctuating electric power of renewable energy sources such as wind and photovoltaic power generations by means of the SMES having characteristics of quick response and large Input-Output power, and hydrogen energy with FC-EL having characteristics of moderate response and large storage capacity. The moderate fluctuated power of the renewable energy is compensated by a trend forecasting method with the Artificial Neural Network. In case of excess of the power generation by the renewable energy to demand it is converted to hydrogen with EL. In contrast, shortage of the electric power is made up with FC. The faster fluctuation power that cannot be compensated by the forecasting method is effectively compensated by SMES. In the ASPCS, the SMES coil with an MgB2 conductor is operated at 20 K by using liquid hydrogen supplied from a liquid hydrogen tank of the fuel cell vehicle station. The necessary storage capacity of SMES is estimated as 50 MJ to 100 MJ depending on the forecasting time for compensating fluctuation power of the rated wind power generation of 5.0 MW. As a safety case, a thermosiphon cooling system is used to cool indirectly the MgB2 SMES coil by thermal conduction. In this paper, a trend forecasting result of output power of a wind power generation and the estimated storage capacity of SMES are reported.

Numerical simulation on AC loss in REBCO tapes carrying non-sinusoidal currents

AC loss is one of the greatest obstacles for high‐temperature superconducting(HTS)applications.In some HTS applications,coated conductors carry non‐sinusoidal currents.Thus,it is important to investigate the effect of various waveforms on AC loss in coated conductors.In this work,transport AC loss in a 4 mm‐wide REBCO coated conductor carrying sinusoidal and non‐sinusoidal currents,is numerically investigated.The current amplitudes,the frequency of the transport current,and n‐value are varied.Non‐sinusoidal transport current waveforms studied include square,five types of trapezoidal,and triangular waveforms.Simulated results show that,for a given current amplitude,AC loss for the square current waveform is the greatest,that for the triangular waveform is the smallest.The sequence of AC loss in the conductor for different current waveforms coincides with the penetration depth,which implies the penetration depth determines the AC loss of the coated conductor.Furthermore,the transport AC loss in the conductor was found to decrease with frequency as f2=n for non‐sinusoidal transport current.