This article has no abstract.

View full abstract

The demand and supply control in a power system is based on the acquisition and forecasting of the system data. Penetration of wind-power generation and photovoltaic generation could make the data acquisition and forecast more difficult. Therefore, further development in the time-series data analysis and forecasting techniques would be requested. This paper reports the recent trend in this area.

View full abstract

This paper describes smoothing effect and fluctuation of PV generation for the voltage management in distribution system. The purpose of the analysis is to show quantitatively the fluctuation and the smoothing effect of PV generation by weather, using actual generation data from 25 distributed PVs in the distribution area. The analysis showed the impact of PV output fluctuation by weather based on the indexes of the coherence and the maximum fluctuation. In particular, it showed the relationship between area largeness and PV output fluctuation by frequency. It was found that both of the two indexes were different by weather, and fine and cloudy day seemed to be the most difficult situation for the voltage management in distribution system.

View full abstract

The 2011 Tohoku earthquake had a great impact on Japanese energy policy. It is expected to phase out nuclear power plants and install a large amount of generation from renewable energy sources. Attention is particularly focused on photovoltaic (PV) generation in whose technology Japan is superior, and the high price is set in feed-in tariff policy which started in 2012. However, a large integration of PV on power grids may cause imbalance between power supply and demand. It will be indispensable to use PV power generation forecasts in economic-load dispatching control (EDC), so that the economics and reliability of power systems networks can be maintained. Thus, in the previous studw, we proposed an EDC method with unit commitment (UC) based on the results provided by a day-ahead PV forecast. In this study, we evaluate the frequency and trennd of outages and surpluses of power due to the forecast error of PV power generation by numerical simulations conducted using the power system model of Kanto area in Japan. The results showed that outage or surplus power occurs not only due to overestimations or underestimations of PV power but also due to operation conditions of the power systems.

View full abstract

In a future power system, it is very important to evaluate phenomenon called mutual smoothing effect, because cost of countermeasures to mitigate impact of highly penetrated PVs' fluctuation will depend on the effect. In the previous work, the authors developed a method called “Transfer Hypothesis” for presuming total output fluctuation of highly penetrated PVs considering mutual smoothing effect based on analyses of measured irradiance data in the spring time. In the method, parameter called “Transfer Swing Period” which is identified from measured irradiance data is important to represent smoothing effect. Therefore, if the transfer swing period has some trends depending on season, month or fluctuation condition, presumption results could be affected by how to select the transfer swing period. This paper shows a study on impact of the parameter (transfer swing periods) selection on presumed total output fluctuation of highly penetrated PVs and consideration for a future power system.

View full abstract

On March 11^th in 2011, the power system suffered heavy damage from the huge earthquake and tsunami in Tohoku region. This paper describes the change of features including in the time series of the open demand data by the disaster 3/11/2011. The demand data is separated into three sections; one is for the `before disaster' analysis from April 2008 to February 2011, the second section is for the `while disaster' survey during March, April and May in 2011, and last data section is for the `after disaster' analysis from June 2011 to March 2013. We discriminated the periodical components of the daily, the weekly, and the seasonal fluctuation among the demand time series by applying newly developed procedure, the quasi-ideal moving average method. Some significant change were observed on the stochastic of the `before disaster' and the `after disaster' periodical components analysis. The change of the temperature sensitivity was also surveyed by using the open weather data in Sendai.

View full abstract

Currently, the installed capacity of photovoltaic generations (PV) is rapidly growing from perspective of environment and energy security. However, unstable and unpredictable generated power variation from PV disturbs balance of total generated power and demand power across a power system, and as a result, deterioration in frequency control of a power system would be concerned. Therefore, magnitude of generated power variation of penetrated PV should be estimated to evaluate those deterioration before penetration of PVs. In this paper, as the basic study, we develops a method to generate the time series of spatially averaged solar radiation in 10km by applying low pass filter which is designed to represent smoothing effect.

View full abstract

This paper proposes an observability index for evaluation of measurement formation in estimation of total output of solar photovoltaic generators (PVs) widely distributed in a power system area. Since direct measurement of all the PVs in the area is infeasible in reality, estimation error is unavoidable. In this paper observability is defined as the maximum accuracy of an ideal estimator of the total output. In the place of an ideal estimator, a known estimation method is used to approximately quantify observability. First, correlation coefficient as a function of distance (CCoD) is qualitatively justified since the estimation method employed is based on CCoD. Second, an observability index is defined as the maximum accuracy of the estimation. The index depends on spatial distribution of both measurement points and PVs. Third, the index is calculated for an actual large scale measurement formation and then the characteristic of the index is discussed to show its appropriateness.

View full abstract

This paper proposes a new reliability assessment method for two control areas interconnected by a tie line which can be used in the evaluation of the mass penetration effects of intermittent generation. The proposed method is based on the state enumeration method and can evaluate in short computation time with good accuracy. To investigate the validity of proposed method, the performance of this method is compared with a non-sequential Monte Carlo simulation. Furthermore some applications of the proposed method are shown.

View full abstract

Large-scale penetration of photovoltaic power generation (PV) causes concerns in keeping supply-and-demand balance of a power system because output power of PVs shows considerable fluctuations due to weather condition. To assess the impacts on the balance, fluctuation characteristics of PVs should be examined for the case of large-scale penetration of PVs. Since fluctuation of total output of many PVs dispersed across an area is dominated by smoothing effects and the smoothing effects are governed by correlation among solar irradiances across the area, correlation in solar irradiances at various locations should be examined. The paper analyzes solar irradiances on the days with large short-term fluctuations in irradiance using cross correlation function, spectral analyses, etc. The results show that the days with large fluctuations can be generally classified into two categories—ie., days with high and low correlations—and the correlation basically depends on horizontal scale of clouds.

View full abstract

In order to mitigate the impacts of high penetration photovoltaic power generation system (HP-PVS) on the electric power system operation, the statistical evaluation of the aggregated power output fluctuation characteristics of HP-PVS is important. By using the multi-points irradiance data observed for a year in the Chubu region of Japan, we have evaluated the fluctuation characteristics of spatial average irradiance. However, the study period is not enough for a statistical evaluation. Therefore, this study assessed the usability of the sunshine duration data of AMeDAS (Automated Meteorological Data Acquisition System) for the statistical evaluation of fluctuation characteristics in terms of daily maximum fluctuation width in 120min. The irradiance estimation method from the sunshine duration data at single point proposed in the precedent study was modified to be suitable for the spatial average irradiance estimation by taking into account the smoothing effect of irradiance fluctuation among several points. The result suggests that the AMeDAS sunshine duration data would be useful for the statistical evaluation of fluctuation characteristics of spatial average irradiance of electric power system service area.

View full abstract

A method is proposed for forecasting global solar radiation. The method is based on weather information using binary trees and factor analysis. The feature of this method is that it is possible to use a simple linear forecasting equation. The method has been tested on the meteorological and global solar radiation data obtained at several observation sites, and the results show that it is promising to be used to keep the balance between demand and supply of electric power in the near future power systems with a large number of photovoltaic systems installed.

View full abstract

Because of lack of infrastructures to monitor PV (PhotoVoltaics) power generated in homes, large amount of PV power generation in power system will become unmeasurable. This problem may prevent power companies from managing their power system efficiently. To solve this problem, we propose PV power generation estimation method without requiring any historical data of actual PV power generation values or operating capacity of PV power generators. Main idea of proposed method is estimating power demand curve from solar radiation curve and power system load curve with pattern estimation method. After estimating power demand curve, we estimate PV power generation values by fitting linear combination of these curves to power system load curve. We have evaluated proposed method with actual factory data. As a result, we have found root mean square error of proposed method is less than 1.5% of maximum power demand and the error rate is independent from capacity of PV power generators.

View full abstract

The prediction of solar insolation is needed to predict the photovoltaic (PV) generation output connected to power systems. This paper proposes a method for estimating the errors of solar insolation forecasts, which are unavoidable, using only the input variables employed in solar insolation prediction and the predicted solar insolation. Given that some big errors of solar insolation forecasts concentrate in the certain intervals of some variables, we use the statistics method to find those variables and the proper boundaries of the intervals and combine them as the rules to judge the categories of errors. The error estimation technique can inform the PV/power system operators what kind of error the predicted value of solar insolation is likely to have and how much the confidence of the correct estimation is. Since the big errors cause either large over expectation or under expectation of PV outputs, the results of error estimation are useful for operators to identify the extreme situations which cause the large deviation of power. From the simulation of two study cases, error estimation results of our proposed method are acceptable.

View full abstract