Operational medium range flood forecasting systems are increasingly moving towards the adoption of ensembles of numerical weather predictions (NWP), known as ensemble prediction systems (EPS), to drive their predictions. We review the scientific drivers of this shift towards such ‘ensemble flood forecasting’ and discuss several of the questions surrounding best practice in using EPS in flood forecasting systems. We also review the literature evidence of the ‘added value’ of flood forecasts based on EPS and point to remaining key challenges in using EPS successfully.

Ensemble flood forecasting: A review

Dynamic modeling and small signal stability analysis of distributed photovoltaic grid-connected system with large scale of panel level DC optimizers

Predicting the Power Output of a Grid-Connected Solar Panel Using Multi-Input Support Vector Regression

A method for forecasting reduction in sunlight intensity due to cloud cover at a photovoltaic power plant is described. The method comprises determining characteristics of one or more clouds from sensors surrounding the photovoltaic power plant. The cloud characteristics are used to create a 3D map of the clouds. The 3D map in combination with information on the angle of the sun is used to create a 3D projection on the surface of the earth, resulting in a 2D surface irradiance map. The 2D surface irradiance map may be taken in successive projections or used in combination with wind speed data to forecast fluctuation in irradiance at the photovoltaic power plant. The forecasted reductions in power may be used to enact measures at the plant such as reducing the power output of inverters to prevent sudden fluctuations in the power output of the photovoltaic plant feeding the utility.

Method for predicting and mitigating power fluctuations at a photovoltaic power plant due to cloud cover

A wind power generation system includes one or both of a memory or storage device storing one or more processor-executable executable routines, and one or more processors configured to execute the one or more executable routines which, when executed, cause acts to be performed. The acts include receiving weather data, wind turbine system data, or a combination thereof; transforming the weather data, the wind turbine system data, or the combination thereof, into a data subset, wherein the data subset comprises a first time period data; selecting one or more wind power system models from a plurality of models; transforming the one or more wind power system models into one or more trained models at least partially based on the data subset; and executing the one or more trained models to derive a forecast, wherein the forecast comprises a predicted electrical power production for the wind power system.

Systems and methods for improved wind power generation

The invention provides a photovoltaic power prediction method based on a ground-based cloud chart. The method comprises the following steps: 1) pre-estimating the movement of a cloud cluster; 2) predicting irradiance on the ground; 3) establishing a comprehensive photoelectric conversion model; 4) and carrying out photovoltaic power prediction. A plurality of digital picture processing techniques are comprehensively applied, so that requirements of problems are highlighted, pertinency and practicality are high, and combined with the traditional statistical method, the photovoltaic power prediction method provides effective technical support and method reference for a photovoltaic power refinement prediction; models are established with multi-steps based on synthesizing of multi-factors; key links in the photovoltaic prediction field are all included in the description of the method, so that universality and robustness are high; in order to combine concrete scenes and application objects used during usage, adjustment parameters are reserved in some links, so that operation is convenient and prediction effect is guaranteed.

Photovoltaic power prediction method based on ground-based cloud chart

The invention provides a cloud cluster movement estimation method facing to photovoltaic power prediction. The cloud cluster movement estimation method for the photovoltaic power prediction comprises the following steps: preprocessing an image of a ground-based cloud picture; thresholding the ground-based cloud picture; detecting and marking a cloud cluster and extracting center of mass of the cloud cluster; and estimating moving speed and direction of the cloud cluster. By the cloud cluster movement estimation method for the photovoltaic power prediction, each cluster in a time sequence image is tracked and studied to determine the moving speed and direction of the cloud cluster in the future, so that the cloud cluster movement in the future is estimated, and an important data source is provided for minute-grade power prediction within a super-short period of 0-4 hours for a photovoltaic power station.

Cloud cluster movement estimation method facing to photovoltaic power prediction

The invention provides a photovoltaic super-short-term generated power forecasting method based on cloud cover simulation. The method comprises the following steps that photovoltaic super-short-term generated power of a photovoltaic power station in the next four hours is forecasted according to a weather-type cloudless sky forecasting method; cloud cover information of the photovoltaic power station in the next four hours is simulated, forecasted data correction is carried out for horizontal plane irradiance attenuation caused by cloud, and forecasting of the photovoltaic super-short-term generated power of the photovoltaic power station is finished. The forecasting method has the greater advantages on the aspect of capturing the cloud cover shading information than a cloudless sky working condition photovoltaic power super-short-term forecasting model, and the effective time duration is greatly prolonged compared with that forecasted by a photovoltaic power super-short-term forecasting model based on a foundation cloud picture.

Photovoltaic super-short-term generated power forecasting method based on cloud cover simulation

This paper proposes a practical and effective method base on weather patterns for producing 15-minutes short-term prediction of photovoltaic generation with a prediction horizon of 24 hours. Two different radiation prediction models are examined for two different weather patterns. In the clear sky model, the surface radiation is predicted by calculating the cutting plane instantaneous intensity of solar radiation and atmospheric transparency coefficient. In the mode of non-clear sky, future radiation is forecasted by finding the quadratic curve of the measured surface radiation and the time. Finally, the radiation - power conversion model is developed to calculate the corresponding power prediction through the outputting of the short-term radiation prediction model. The proposed approach been applied in many PV power plant in the Northwest part of China. It is shown that the system can produce reasonable forecast results, providing a good guidance for dispatching and efficient running for PV power plant.

Method for short-term photovoltaic generation power prediction base on weather patterns

The invention discloses a micro-siting method of a wind detecting network of a ten-million-kilowatt-class large wind power base. The micro-siting method of the wind detecting network of the ten-million-kilowatt-class large wind power base includes the following steps. Firstly, a distribution map of average wind speeds for multiple years is drawn; secondly, orthogonal functions are decomposed based on annual average wind speed data and experience of multiple measuring states for multiple years and spatial and temporal distribution characteristics of the wind speeds of a zone where the large wind power base is located are analyzed; thirdly, a typical zone where wind speeds change uniformly is divided based on the spatial and temporal distribution characteristics of the wind speeds of the zone where the large wind power base is located; fourthly, CFD model software is applied to calculate microscale air flow parameters and a proper site is confirmed. The micro-siting method of the wind detecting network of the ten-million-kilowatt-class large wind power base has the advantages of overcoming the defect that climate resource diagnostic analysis does not exist in the prior art and achieving combination of macroscopic analysis and micro-siting.

A micro-siting method of wind detecting network of ten-million-kilowatt-class large wind power base

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