Flood hazard evaluation is an important input for Nuclear Power Plants external events safety studies. In the present study, flood hazard at various nuclear sites in India due to rainfall has been evaluated. Hazard estimation is a statistical procedure by which rainfall intensity versus occurrence frequency is estimated from historical records of rainfall data and extrapolated with asymptotic extreme value distribution. Rainfall data needed for flood hazard assessment are daily annual maximum rainfall (24?h data). The observed data points have been fitted using Gumbel, power law and exponential distribution, and return period has been estimated. To study the stationarity of rainfall data, a moving window estimate of the parameters has been performed. The rainfall pattern is stationary in both coastal and inland regions over the period of observation. The coastal regions show intense rainfall and higher variability than inland regions. Based on the plant layout, catchment area and drainage capacity, the prototype fast breeder reactor (PFBR) site is unlikely to be flooded. 相似文献
Renewable energy curtailment is a critical issue in China, impeding the country’s transition to clean energy and its ability to meet its climate goals. This paper analyzes the impacts of more flexible coal-fired power generation and improved power dispatch towards reducing wind power curtailment. A unit commitment model for power dispatch is used to conduct the analysis, with different scenarios demonstrating the relative impacts of more flexible coal-fired generation and improved power dispatch. Overall, while we find both options are effective in reducing wind power curtailment, we find that improved power dispatch is more effective: (1) the effect of ramping down coal-fired generators to reduce wind power curtailment lessens as the minimum output of coal-fired generation is decreased; and (2) as a result, at higher wind capacity levels, wind curtailment is much more significantly reduced with improved power dispatch than with decreased minimum output of coal-fired generation.
Key policy insights
China should emphasize both coal power flexibility and dispatch in its policies to minimize renewable power curtailment and promote clean energy transition.
China should accelerate the process of implementing spot market and marginal cost-based economic dispatch, while making incremental improvements to the existing equal share dispatch in places not ready for spot market.
A key step in improving of dispatch is incorporating renewable power forecasts into the unit commitment process and updating the daily unit commitment based on the latest forecast result.
China should expand the coal power flexibility retrofit programme and promote the further development of the ancillary service market to encourage more flexibility from coal-fired generation.
Abstract The well-established physical and mathematical principle of maximum entropy (ME), is used to explain the distributional and autocorrelation properties of hydrological processes, including the scaling behaviour both in state and in time. In this context, maximum entropy is interpreted as maximum uncertainty. The conditions used for the maximization of entropy are as simple as possible, i.e. that hydrological processes are non-negative with specified coefficients of variation (CV) and lag one autocorrelation. In this first part of the study, the marginal distributional properties of hydrological variables and the state scaling behaviour are investigated. Application of the ME principle under these very simple conditions results in the truncated normal distribution for small values of CV and in a nonexponential type (Pareto) distribution for high values of CV. In addition, the normal and the exponential distributions appear as limiting cases of these two distributions. Testing of these theoretical results with numerous hydrological data sets on several scales validates the applicability of the ME principle, thus emphasizing the dominance of uncertainty in hydrological processes. Both theoretical and empirical results show that the state scaling is only an approximation for the high return periods, which is merely valid when processes have high variation on small time scales. In other cases the normal distributional behaviour, which does not have state scaling properties, is a more appropriate approximation. Interestingly however, as discussed in the second part of the study, the normal distribution combined with positive autocorrelation of a process, results in time scaling behaviour due to the ME principle. 相似文献