Stochastic Optimization Model to Study the Operational Impacts of High Wind Penetrations in Ireland

By P. Meibom, R. Barth, B. Hasche, H. Brand, Christoph Weber, Mark J. O'Malley. IEEE Transactions on Power Systems, 2011

364 citations recorded by the source corpus.

A stochastic mixed integer linear optimization scheduling model minimizing system operation costs and treating load and wind power production as stochastic inputs is presented. The schedules are updated in a rolling manner as more up-to-date information becomes available. This is a fundamental change relative to day-ahead unit commitment approaches. The need for reserves dependent on forecast horizon and share of wind power has been estimated with a statistical model combining load and wind power forecast errors with scenarios of forced outages. The model is used to study operational impacts of future high wind penetrations for the island of Ireland. Results show that at least 6000 MW of wind (34% of energy demand) can be integrated into the island of Ireland without significant curtailment and reliability problems.

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

View Paper: https://www.semanticscholar.org/paper/ad9226c6d9ce9d9b24727da4d8cded3cdc8edd21

How researchers see this paper

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

In Electrical and Electronic Engineering

1. Zuyi Li
2. Mohammad Shahidehpour
3. Hongyu Wu
4. Xinxin Zhu
5. Wei Tian
6. Aidan Tuohy
7. Le Xie
8. Mark J. O'Malley

In Safety, Risk, Reliability and Quality

1. Hongyu Wu
2. Zuyi Li
3. Aidan Tuohy
4. Wei Tian
5. Mark J. O'Malley
6. Mohammad Shahidehpour
7. Marc G. Genton
8. Rafal Weron

Citations in the corpus

• Challenges and barriers to demand response deployment and evaluation (2015, background): “In recent times, there as been considerable work in developing stochastic unit commitment tools to account for the uncertainty associated with variable renewable generation, particularly wind [68,69].”
• A Model Predictive Control Approach to Microgrid Operation Optimization (2014, methodology): “An MPC method has been commonly proposed to solve the unit commitment problem with wind power generation (see [22]).”
• Chance-Constrained Day-Ahead Scheduling in Stochastic Power System Operation (2014, background): “Rolling planning is carried out for rescheduling based on the most up-to-date wind forecasts and existing schedules [15].”
• Pumped storage in systems with very high wind penetration (2011, methodology): “This tool was then further developed into a full mixed integer unit commitment tool for the All Island Grid Study (Meibom et al., 2007a) and (Meibom et al., 2011), which was carried out to examine the future Irish power system with high levels of renewables.”
• Stochastic dual dynamic integer programming (2018, background): “Examples include long term capacity planning of generation and transmission systems [5,8], day-ahead generation scheduling (unit commitment) [10,20,54,77,87], planning and operation of renewable energy systems [17,30,46,63], management of electricity storage systems [55,56], etc.”
• Short-Term Spatio-Temporal Wind Power Forecast in Robust Look-ahead Power System Dispatch (2014, background): “TABLE I NOTATIONS developed by P. Meibom et al. to study the operational impacts of high wind generation in Europe [23], [24].”