• Corpus ID: 244714720

Achieving an Accurate Random Process Model for PV Power using Cheap Data: Leveraging the SDE and Public Weather Reports

@article{Qiu2021AchievingAA,
  title={Achieving an Accurate Random Process Model for PV Power using Cheap Data: Leveraging the SDE and Public Weather Reports},
  author={Yiwei Qiu and Jin Lin and Zhipeng Zhou and Ningyi Dai and Feng Liu and Yong Hua Song},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.13812}
}
The stochastic differential equation (SDE)-based random process models of volatile renewable energy sources (RESs) jointly capture the evolving probability distribution and temporal correlation in continuous time. It has enabled recent studies to remarkably improve the performance of power system dynamic uncertainty quantification and optimization. However, considering the non-homogeneous random process nature of PV, there still remains a challenging question: how can a realistic and accurate… 

References

SHOWING 1-10 OF 31 REFERENCES

A Statistical Model for Hourly Large-Scale Wind and Photovoltaic Generation in New Locations

The analysis of large-scale wind and photovoltaic (PV) energy generation is of vital importance in power systems, where their penetration is high. This paper presents a modular methodology to assess

Probabilistic forecasts of solar irradiance using stochastic differential equations

Probabilistic forecasts of renewable energy production provide users with valuable information about the uncertainty associated with the expected generation. Current state‐of‐the‐art forecasts for

Stochastic modeling of intraday photovoltaic power generation

Adaptive Learning Hybrid Model for Solar Intensity Forecasting

A novel adaptive learning hybrid model (ALHM) for precise solar intensity forecasting based on meteorological data that captures the linear, temporal, and nonlinear relationships in the data, and keeps improving the predicting performance adaptively online as more data are collected.

Day-ahead probabilistic forecast of solar irradiance: a Stochastic Differential Equation approach

In this work, we derive a probabilistic forecast of the solar irradiance during a day at a given location, using a stochastic differential equation (SDE for short) model. We propose a procedure that

Stochastic Online Generation Control of Cascaded Run-of-the-River Hydropower for Mitigating Solar Power Volatility

An ultra-short-term stochastic generation control method for cascaded hydropower to mitigate solar power volatility and characterize the spatial-temporal hydraulic coupling of the cascadedHydropower plants and river operation constraints is proposed.

Fast Monte Carlo Simulation of Dynamic Power Systems Under Continuous Random Disturbances

A fast MCs method is proposed that enables the LHS to speed up sampling continuous disturbances, which is based on the Itô process model of the disturbances and the approximation of the itô process by functions of independent normal random variables.

Nonintrusive Uncertainty Quantification of Dynamic Power Systems Subject to Stochastic Excitations

The proposed nonintrusive method for quantifying uncertainty in dynamic power systems subject to stochastic excitations is based on commercial simulation software such as PSS/E with carefully designed input signals, which ensures ease of use for power utility companies.