Benth, FEFEBenthIbrahim, NANAIbrahim2024-05-292024-05-292017VOLUME 10, NUMBER 3 (SEPTEMBER 2017) PAGES: 1-33 DOI: 10.21314/JEM.2017.1641756-36151756-360710.21314/JEM.2017.164WOS:0004123380000012-s2.0-85059814480https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059814480&doi=10.21314%2fJEM.2017.164&partnerID=40&md5=c37b62a3dce5f2ca9a5d362a05adf1d7https://www.risk.net/journal-of-energy-markets/5327901/stochastic-modeling-of-photovoltaic-power-generation-and-electricity-priceshttps://oarep.usim.edu.my/handle/123456789/11361Indexed by WOS/ScopusWe 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.en-USphotovoltaic (PV) power productionelectricity pricesquanto optionsskewed normal distributionautoregressive-moving-average (ARMA) time seriestext::journal::journal article133103