Utility Wind Integration and Operating Impact State of the Art

By J. Smith, M. Milligan, E. DeMeo, B. Parsons. 2007

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Citations in the corpus

Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting (2017, background): “The random nature of wind, however, makes it difficult to achieve the power balance needed for its grid integration (Smith et al., 2007).”
Offshore wind energy potential in China: Under technical, spatial and economic constraints (2011, unknown): “[48].”
Wind power forecasting : state-of-the-art 2009. (2009, background): “[332] also published an earlier review of the utility wind integration and operating impact in 2007.”
Aggregate Flexibility of Thermostatically Controlled Loads (2015, background): “It is widely accepted that the deep penetration of renewable generation will substantially increase the need for ancillary services [2]–[4].”
The Market Value of Variable Renewables The Effect of Solar and Wind Power Variability on their Relative Price (2013, unknown): “…economic costs of VRE variability, but these publications focus on balancing or grid-related costs while not accounting for profile costs, and seldom report the price impact (Gross et al. 2006, Smith et al. 2007, DeCesaro & Porter 2009, Milligan & Kirby 2009, GE Energy 2010, Holttinen et al. 2011).”
Evaluating the Impacts of Real-Time Pricing on the Cost and Value of Wind Generation (2010, background): “References [2], [3], [4] survey some techniques to study the impacts of wind generation on day-ahead unit commitment, real-time redispatch, and ancillary service requirements.”
Low-dimensional models in spatio-temporal wind speed forecasting (2015, unknown): “The random nature of wind, however, makes it difficult to achieve the power balance needed for its integration into the grid [3], [4].”
Improved battery models of an aggregation of Thermostatically Controlled Loads for frequency regulation (2013, unknown): “Ancillary services such as regulating reserve (or frequency regulation) and load following play an important role in maintaining a functional and reliable grid under normal conditions [2]–[4].”
Generation expansion planning optimisation with renewable energy integration: A review (2017, background): “In-depth reviews of studies that determine the feasibility of integrating large amounts of wind power in power systems and the resulting operational impacts have been performed [57,58].”
Evaluating the Impacts of Real-Time Pricing on the Usage of Wind Generation (2009, unknown): “[2], [3], and [4] describe some methods of estimating the impacts of integrating wind generators into power systems and their associated AS requirements.”
On the economics of renewable energy sources (2013, background): “On the one hand, a significant body of literature quantifies “integration costs” that are associated with different aspects of variability (Gross et al., 2006; Smith et al., 2007; Milligan and Kirby, 2009; DeCesaro and Porter, 2009; GE Energy, 2010; Holttinen et al., 2011).”
A review of combined approaches for prediction of short-term wind speed and power (2014, background): “These wind-related uncertainties can put the system reliability and power quality at risk with the increasing penetration of wind power and thus, the main grid integration issues such as balance management and reserve capacities can come into question [1–3].”
The Market Value of Variable Renewables (2013, unknown): “A number of integration studies quantify economic costs of VRE variability, but these publications focus on balancing or grid-related costs while not accounting for profile costs, and seldom report the price impact (DeCesaro and Porter, 2009; GE Energy, 2010; Gross et al., 2006; Holttinen et al., 20”
Renewable Electricity Futures Study. Volume 1. Exploration of High-Penetration Renewable Electricity Futures (2012, background): “48 Summaries of this literature are available in Gross et al. (2007), Smith et al. (2007), and Holttinen et al. (2009).”