PID-Type Fuzzy Controller for Grid-Supporting Inverter of Battery in Embedded Small Variable Speed Wind Turbine

Frequency and voltage of embedded variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) is strongly affected by wind speed fluctuations. In practice, power imbalance between supply and demand is also common, especially when VSWT-PMSG is connected to a weak micro grid (MG). If load demand fluctuations become high, isolated MG may be unable to stabilize the frequency and voltage so that battery storage needs to be installed into the MG to adjust energy supply and demand. To allow flexible control of active and reactive power flow from/to battery storage, grid-supporting inverters are used. For a system that contains highly nonlinear components, the use of conventional linear proportional-integral-derivative (PID) controllers may cause system performance deterioration. Additionally, these controllers show slow, oscillating responses, and complex equations are required to obtain optimum responses in other controllers. To cope with these limitations, this paper proposes PID-type fuzzy controller (PIDfc) design to control grid-supporting inverter of battery. To ensure safe battery operating limits, we also propose a new controller scheme called intelligent battery protection (IBP). This IBP is integrated into PIDfc. Several simulation tests are performed to verify the scheme’s effectiveness. The results show that the proposed PIDfc controller exhibits improved performance and acceptable responses, and can be used instead of conventional controllers.

Regression Analysis of Electric Power Market Price of JEPX

The deregulation of electric power industries is introducing around the world and electric power markets are operated under the deregulation. Also in Japan, JEPX (Japan Electric Power Exchange) operates a day-ahead market since April 2005. We have already analyzed the electric power market prices in the several markets including JEPX by autoregressive models. We compose simple regression equations, of which a dependent variable is the market price and explanatory variables are the demand and the market price of 24 hours ago. In this paper, we analyze JEPX price data in summer seasons from 2007 to 2013. In this period, the JEPX price is affected by many social phenomena such as Lehman Shock and East Japan earthquake disasters. We compare the determination coefficient and the coefficients of regression and investigate the change of coefficients over the years.

Seasonal Regression Models for Electricity Consumption Characteristics Analysis

This paper presents seasonal regression models of demand to investigate electricity consumption characteristics. Electricity consumption in commercial areas in Japan is analyzed by using meteorological variables, namely temperature and relative humidity. A dummy variable for holidays is also considered. We have developed models for two levels of period to analyze demand characteristics, that is, half year models and seasonal models. Some options for each model are calculated and validated by statistical tests to obtain better models. As results, half year and seasonal models present explicit information about how the variables affect the demand differently for each period. These specific information help in analyzing characteristics of studied commercial demand.