Open AccessAnalysis of hybrid wind-photovoltaic-hydro generation system based on short-term scheduling
Author(s) -
Tenghui Li,
Zhe Huang,
Shida She
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1549/5/052006
Subject(s) - renewable energy , photovoltaic system , wind power , particle swarm optimization , hybrid power , hybrid system , electricity generation , computer science , reliability engineering , electric power system , engineering , power (physics) , electrical engineering , physics , quantum mechanics , machine learning
Renewable energy sources are beneficial to provide clean power generation but simultaneously brings power supply risk due to natural uncertainties. A hybrid wind-solar-hydro generation system, which takes advantage of the complementary characteristic of renewable energy sources, is capable to supply the power demand reliably. A multi-objective model of the hybrid system is proposed to achieve minimum power supply risk and maximum economic benefit under natural limitations. To handle natural uncertainties, autoregressive integrated moving average model is applied to produce typical daily models of weather conditions in different scenarios. Meanwhile, particle swarm optimization algorithm is improved to solve the multi-objective model by introducing the ϵ-constraint method. Lastly, an example of a large-scale hybrid wind-photovoltaic-hydro system is given to analyse reliability, profit, efficiency and operation in different scenarios. The study has shown that the hybrid system does not crash reliability but increases economic benefit, it’s necessary to reserve wind and solar generation, wind generation needs to cooperate with hydro generation according to water dispatching.