Establishing the role that wind generation may have in future generation portfolios

By R. Doherty, Hugh Outhred, Mark O'Malley. IEEE Transactions on Power Systems, 2006

163 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/e55a06c8a7bf3f9210c5cb765cf44baa6f3844df

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Mark J. O'Malley
2. Aidan Tuohy

In Electrical and Electronic Engineering

1. Mark J. O'Malley
2. Aidan Tuohy
3. A. Duffy
4. Michael F. Conlon
5. Alan O'Connor
6. Jean-Paul Watson
7. Vasilis Fthenakis
8. P. Meibom

In Renewable Energy, Sustainability and the Environment

1. A. Duffy
2. Michael F. Conlon
3. Mark J. O'Malley
4. Aidan Tuohy

Citations in the corpus

• Assessing the Economic Benefits of Compressed Air Energy Storage for Mitigating Wind Curtailment (2015, background): “497 Generator VOM costs were obtained from several sources [45]– 498 [47] and start costs were derived from historic start costs [27].”
• Pumped storage in systems with very high wind penetration (2011, methodology): “This is an optimised portfolio for the Irish system in 2020 using the methods described in Doherty et al. (2006).”
• Modeling and solving a large-scale generation expansion planning problem under uncertainty (2011, background): “However, integration of wind generation into the electrical grid is problematic due to output uncertainty, caused by weather (wind speed) dependence [26,24,38,50,36,32].”
• A Study of Principal Component Analysis Applied to Spatially Distributed Wind Power (2011, background): “Thus while generation expansion studies can justifiably use uni-variate statistical models for total system wind power production [2], in contrast the spatially distributed context of the transmission network planning problem requires an effective representation of multivariate wind statistical inte”
• Stochastic Optimization Model to Study the Operational Impacts of High Wind Penetrations in Ireland (2011, methodology): “The approaches described for example in [7]–[ 9 ] are only capable of assessing the operational impacts of wind power variability.”
• The Optimal Share of Variable Renewables: How the Variability of Wind and Solar Power affects their Welfare-optimal Deployment (2012, unknown): “Doherty et al. (2006) apply a simple linear investment-dispatch model to Ireland, finding the optimal amount of wind capacity strongly dependent on the price of CO2 and gas. Olsina et al. (2007) derive the optimal capacity mix for Spain.”