Wind energy has dramatically changed the energy portfolio of Texas and more specifically, a region covering 75% of the state designated as ERCOT (Electric Reliability Council of Texas). Hardly existent at all ten years ago, the amount of capacity the wind farms provide is over 9000MW and accounts for 10% of the total generation. Due to the intermittent nature of wind and limitations of transmission lines, short and long term storage of this energy would benefit wind farms and the grid as a whole. This paper studies the relationship between wind, storage and real time electricity prices by analyzing prices and simulating a wind farm with different wind storage strategies over the course of a year. Based on these simulations, it is found that an ideal storage medium with no losses could be in the money for $17.50/kW for long term storage and $1,998/kW for short term storage for prices similar to 2009-2010. / text

The integration of variable renewable energy sources (VRE) is likely to cause fundamental and structural changes to the operation of future power systems. In the United Kingdom (UK), large amounts of price-insensitive and variable-output wind generation is expected to be deployed to contribute towards renewable energy and carbon dioxide (CO2) emission targets. Wind generation, with near-zero marginal costs, limited predictability, and a limited ability to provide upward dispatch, displaces price-setting thermal power plants, with higher marginal costs, changing flexibility and reserve requirements. New-build, commercial-scale, and low-carbon generation capacity, such as CO2 capture and storage (CCS) and nuclear, may impact power system flexibility and ramping capabilities. Low-carbon generation portfolios with price-sensitive thermal power plants and energy storage are therefore likely to be required to manage increased levels of variability and uncertainty at operational timescales. This work builds on a high-resolution wind reanalysis dataset of UK wind sites. The locations of existing and proposed wind farms are used to produce plausible and internally consistent wind deployment scenarios that represent the spatial distribution of future UK wind capacity. Temporally consistent electricity demand data is used to characterise and assess demand-wind variability and net demand ramp events. A unit commitment and economic dispatch (UCED) model is developed to evaluate the likely operating regimes of thermal power plants and CCS-equipped units across a range of future UK wind scenarios. Security constraints for reserve and power plant operating constraints, such as power output limits, ramp rates, minimum up/down times, and start-up times, ensure the operational feasibility of dispatch schedules. The load factors, time spent at different loads, and the ramping and start-up requirements of thermal power plants are assessed. CO2 duration curves are developed to assess the impacts of increasing wind capacity on the distribution of CO2 emissions. A sensitivity analysis investigates the impacts of part-load efficiency losses, ramp rates, minimum up/down times, and start-up/shut-down costs on power plant operating regimes and flexibility requirements. The interactions between a portfolio of energy storage units and flexible CO2 capture units are then explored. This multi-disciplinary research presents a temporally-explicit and detailed assessment of operational flexibility requirements at full 8760 hour resolution, highlighting the non-linear impacts of increasing wind capacity. The methodological framework presented here uses high spatial-and temporal-resolution wind data but is expected to provide useful insights for other VREbased power systems to mitigate the implications of inadequate flexibility.