The integration of variable renewable energy sources has been greatly promoted worldwide, and power system analysis becomes more important due to the more complexity in the power system with a large number of distributed generators. It is of prime importance to utilize appropriate models according to the purposes of the numerical simulations. Hence, in this paper, the latest trends of simulation models for power system analysis, such as inverters, rechargeable battery, transient stability, and microgrid, were introduced.

In Japan, the capacity of renewable energy sources is increasing rapidly. Therefore, more reserves are required than in the past, and sometimes the output of renewable generation is curtailed. One of the ways to use renewable generation effectively is to exchange power and reserve through tie lines. In this study, we developed the stochastic unit commitment model which considers the exchange of power and reserve through tie lines. The model considers the spatial correlations of prediction errors in the two regions. Several cases were simulated, and as a result, the composition of reserves for the imbalance changed when both power and reserve were exchanged through tie lines. Besides, the amount of exchanged reserve increased when the spatial correlations were taken into account. This study would contribute to further studies on the wide-area operation of the power system with many renewable energy sources.

This paper develops a method of economic evaluation of solar photovoltaics (PV) and battery systems based on the framework of Screening Curve Method (SCM). While the SCM has been known as an intuitive model to estimate the least-cost expansion of generation capacity in a bulk power system, this paper applies it to the problem of optimal sizing of PV and battery systems at customer side. For this, we propose to alter the procedure of load slicing employed in the existing SCM and to construct load slices using PV generation profile. As a result, we develop a method of economic evaluation of PV and battery systems where the customer's electricity demand and PV generation profile are represented using time series of 24 hours. The accuracy of calculated results by the developed method is verified by comparing with the results obtained by a linear programming model. An intuitive graphical analysis enabled by the developed method is illustrated through an example with typical demand and PV generation data.

Day-ahead unit commitment (DAUC) and intraday-optimization of electric load dispatching (IOED) are widely used to simulate power system operations with high-level renewable power integration. However, operation plans made by IOED models might be infeasible in reality, because the IOED model inputs actual renewable generation in a whole day. In order to check the feasibility, this paper compares simulation results of an IOED model with results of an intraday time-series electric load dispatching model (ITED model). Both models use the same DAUC results. The IOED model was modelled as a mixed integer linear problem, and the ITED model was modelled as a rule-based control model. Annual simulation results indicate that in terms of the supply shortage, the difference between the IOED model and the ITED model was not so large, especially for large shortages. On the other hand, operations of the pumped storage hydro were less frequent in the IOED model than in the ITED model.

In distribution systems, the introduction of SVC (Static Var Compensator) that can rapidly control reactive power is expected to cope with the steep voltage changes caused by PV (photovoltaic) output changes in terms of proper voltage profile management. On the other hand, voltage control equipment with tap changer such as SVR (Step Voltage Regulator) has been widely used for voltage control in the distribution systems with relatively long feeder lines. It is important issue to fully utilize those ongoing conventional voltage controllers in order to reduce capital investment cost. An interaction between SVC and SVR is one of important issues when they are connected with the same feeder line. Hence, in this paper, we developed a cooperative voltage control method which can realize more reasonable tap operation of SVR based on estimation technique of reactive power output from SVC supposing only local information is available for SVR control.

The characteristics of winter lightning flashes in Hokkaido area were investigated based on Lightning Location System (LLS) data from 2006/07 to 2016/17. The positive lightning was 41% on average over the 11 years, indicating that it was almost the same as previous studies conducted in the Hokuriku district. The total number of lightning flashes in 11-year period showed the largest in November, and the smallest in February. Over the years, the number of lightning in March has been increasing, there has been a statistically significant trend. When approaching low pressure or passing through the cold front, the number of lightning flashes increase due to continuous lightning activity, and lightning exceeding 100kA peak values were observed. On the other hand, at typical atmospheric pressure pattern in winter, the developed convective cloud band repeatedly advects to the west coast of Hokkaido, and once or a few lightning flashes from those bands. Therefore, although the lightning activity term is short, the total number of flashes is increasing.

Theoretical solution is derived for annular laminar flows with MHD interaction driven by a rotating co-axial cylinder. The effects on the flow field and rotational torque are clarified by changing the radius ratio and the strength of MHD interaction. As increasing the radius ratio, azimuthal flow velocity increases and approaches the plane Couette flow profile for weak MHD interaction. The azimuthal flow velocity, however, decreases as increasing MHD interaction, and the reverse flow emerges in large radial locations. As increasing the MHD interaction, the rotational torque increases. A larger radius ratio leads to the larger sensitivity of the change in rotational torque.