Very short-term probabilistic wind power forecasting based on Markov chain models

Carpinone, A.; Langella, R.; Testa, A.; Giorgio, Massimiliano

doi:10.1109/pmaps.2010.5528983

Cited by 70 publications

(40 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The Markov chain model takes into account the time correlation and has been frequently used for the generation of synthetic wind speed series [17]. We adopt this approach in our study.…”

Section: Wind Speedmentioning

confidence: 99%

Joint optimisation of generation and storage in the presence of wind

Liu

Giulietti²,

Chen

2016

IET Renewable Power Generation

View full text Add to dashboard Cite

Abstract:We study an independent grid where the penetration of wind energy is high and exploit the joint planning of energy storage and a renewable energy source, as it can potentially result in a more economical and efficient energy system. More specifically, we consider an energy system that consists of a gas-fired plant, and a small wind farm with a capacity for energy storage. We assume that the gas-fired plant has a maximum generation capacity that is no more than the electricity demand. We first propose an optimization model with known wind speed and electricity demand. Then we gradually extend this deterministic model to take into account the stochastic nature of the renewable energy source and electricity demand. Furthermore, we consider the possibility of connecting our system to the National Grid, which we import from or export to when our system has an energy shortage or surplus in meeting the demand. Our results provide helpful insights in planning the joint deployment of generation capacity and energy storage, and show that the system operates more efficiently and economically when it is connected to the National Grid.

show abstract

“…The Markov chain model takes into account the time correlation and has been frequently used for the generation of synthetic wind speed series [17]. We adopt this approach in our study.…”

Section: Wind Speedmentioning

confidence: 99%

Joint optimisation of generation and storage in the presence of wind

Liu

Giulietti²,

Chen

2016

IET Renewable Power Generation

View full text Add to dashboard Cite

show abstract

“…ar a [11] has introduced a new proposal to involve uncertainties in Fuzzy Markov Chains by using Interval Type-2 Fuzzy Sets (IT2 FS). Carpinone et al [12] have proposed the method which is based on the use of discrete time Markov chain models of a proper order and also developed wind power time series analysis. Adnan and Islam [13] have presented a technique for voice correction and interpolation using Markov chain detection.…”

Section: Related Workmentioning

confidence: 99%

Markov Chain Application in Object-Oriented Software Designing

Kumar¹,

Saxena²

2013

IJCA

View full text Add to dashboard Cite

In the current scenario, the performance evaluation of the software system is one of the major factors of the software development that helps to develop the quality oriented software. There are many performances optimizing techniques which are used for evaluating the performance of the software systems. Many of the researchers have used the optimization techniques i.e. Markov chain to find out the performance of the object-oriented software design. The present papers is based upon the evaluating the performance of the designed UML model for a real case study of Life Insurance of India (LIC). The performance is evaluated for sharing the attributes by the UML classes. The concept of the probabilistic adjacency metric is used and Dijkstra's algorithm is applied to compute the optimal path.

show abstract

“…In (Carpinone et al, 2010) they are here used to develop a probabilistic forecasting method that allows to provide estimates of future wind power generation, not only as point forecasts, but also as estimate of the probability distributions associated to the point forecasts.…”

Section: Very Short Term Wind Forecastmentioning

confidence: 99%