Publication:
Stochastic modeling of photovoltaic power generation and electricity prices

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Date

2017

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Incisive Media

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Abstract

We propose a stochastic model for the maximal production of photovoltaic (PV) power on a daily basis, based on data from three transmission system operators in Germany. We apply sun intensity as a seasonal function and model the deseasonalized data using an autoregressive process with skewed normally distributed noise, with seasonal variance to explain the stochastic dynamics. It is further demonstrated that the power spot prices are negatively dependent on the PV production. As an application of our results, we discuss virtual power plant derivatives and energy quanto options, as well as continuous-time stochastic processes for PV and power spot price dynamics.

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Keywords

photovoltaic (PV) power production, electricity prices, quanto options, skewed normal distribution, autoregressive-moving-average (ARMA) time series

Citation

VOLUME 10, NUMBER 3 (SEPTEMBER 2017) PAGES: 1-33 DOI: 10.21314/JEM.2017.164

URI

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059814480&doi=10.21314%2fJEM.2017.164&partnerID=40&md5=c37b62a3dce5f2ca9a5d362a05adf1d7
 https://www.risk.net/journal-of-energy-markets/5327901/stochastic-modeling-of-photovoltaic-power-generation-and-electricity-prices
 https://oarep.usim.edu.my/handle/123456789/11361

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