An Advanced Statistical Method for Wind Power Forecasting

By G. Sideratos, S. M. I. Nikos D. Hatziargyriou. 2007

632 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality

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Citations in the corpus

A survey of data fusion in smart city applications (2019, background): “Nowadays, the most common renewable energy sources emerged in the market are solar farm [101], [141] and wind power [215], [216].”
Distributed Optimal Energy Management in Microgrids (2015, methodology): “As can be seen from the figure, the load is shifted from the time when the energy price is high (t ∈ [14, 17]) to when the price is low (t ∈ [19, 21]).”
Centralized Control for Optimizing Microgrids Operation (2008, methodology): “Indicatively, methods for wind power forecasting, such as [5] and [6] can be utilized.”
Wind power forecasting : state-of-the-art 2009. (2009, background): “Sideratos and Hatziargyriou [172] described a statistical WPF system that uses artificial intelligence and fuzzy logic techniques.”
Markov chain modeling for very-short-term wind power forecasting (2015, background): “The atter [7–10] consist of emulating the relationship between hisorical values of wind power, historical and forecasted values of eteorological variables and future wind power output, whose arameters have to be estimated from data, without making any ssumption on the physics of the phenomenon under”
Wind Energy: Forecasting Challenges for Its Operational Management (2013, methodology): “Notably, neural networks and other machine learning approaches became popular after the original proposal of Kariniotakis, Stavrakakis and Nogaret (1996) and more recently with the representative work of Sideratos and Hatziargyriou (2007).”
Current status and future advances for wind speed and power forecasting (2014, methodology): “[61] Sideratos G, Hatziargyriou ND.”
Distributed Compressive CSIT Estimation and Feedback for FDD Multi-User Massive MIMO Systems (2014, methodology): “In this section, we analyze the CSIT estimation performance in terms of the normalized mean absolute error [41] of the channel matrices.”
Opportunity Cost Bidding by Wind Generators in Forward Markets: Analytical Results (2011, background): “Other relevant work includes a detailed discussion of utility metrics for risk-averse traders [9], assessment of the cost of wind forecast errors [10] and real-time prices [11], advanced wind forecasting methods [12], operational strategies coordinating wind generation with reserves, storage, and hy”