This paper presents a security-constrained unit commitment (SCUC) algorithm which takes into account the intermittency and volatility of wind power generation. The UC problem is solved in the master problem with the forecasted intermittent wind power generation. Next, possible scenarios are simulated for representing the wind power volatility. The initial dispatch is checked in the subproblem and generation redispatch is considered for satisfying the hourly volatility of wind power in simulated scenarios. If the redispatch fails to mitigate violations, Benders cuts are created and added to the master problem to revise the commitment solution. The iterative process between the commitment problem and the feasibility check subproblem will continue until simulated wind power scenarios can be accommodated by redispatch. Numerical simulations indicate the effectiveness of the proposed SCUC algorithm for managing the security of power system operation by taking into account the intermittency and volatility of wind power generation.

Security-Constrained Unit Commitment With Volatile Wind Power Generation

This Deliverable of ANEMOS.plus (Advanced Tools for the Management of Electricity Grids with Large-Scale Wind Generation) and SafeWind projects presents the state of the art in wind power forecasting. More than 380 references of journal and conference papers have been reviewed. (LN)

http://ecolo.org/documents/documents_in_english/wind-predict-ANEMOS.pdf

The state-of-the-art in short-term prediction of wind power. A literature overview

This paper proposes a new simulation method that can fully assess the impacts of large-scale wind power on system operations from cost, reliability, and environmental perspectives. The method uses a time series of observed and predicted 15-min average wind speeds at foreseen onshore- and offshore-wind farm locations. A Unit Commitment and Economic Dispatch (UC-ED) tool is adapted to allow for frequent revisions of conventional generation unit schedules, using information on current wind energy output and forecasts for the next 36 h. This is deemed the most faithful way of simulating actual operations and short-term planning activities for a system with large wind power penetration. The problem formulation includes ramp-rate constraints for generation schedules and for reserve activation, and minimum up-time and down-time of conventional units. Results are shown for a realistic future scenario of the Dutch power system. It is shown that problems such as insufficient regulating and reserve power-which are typically associated with the variability and limited predictability of wind power-can only be assessed in conjunction with the specifics of the conventional generation system that wind power is integrated into. For the thermal system with a large share of combined heat and power (CHP) investigated here, wind power forecasting does not provide significant benefits for optimal unit commitment and dispatch. Minimum load problems do occur, which result in wasted wind in amounts increasing with the wind power installed

/pdf/impacts-of-wind-power-on-thermal-generation-unit-commitment-5cdpcdyu3w.pdf

Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch

The paper analyzes the impact of integrating wind generation on the regulation and load following requirements of the California Independent System Operator (CAISO). These requirements are simulated and compared for the study cases with and without wind generation impacts included into the study for the years 2006 and 2010. Regulation and load following models were built based on hour-ahead and five-minute ahead load and wind generation forecasts. In 2006, the CAISO system peaked at 50 270 MW. Wind generation (at the installed capacity of 2600 MW) had limited impact on the requirement of load following and regulation in the CAISO Balancing Authority. However, in 2010 (with an expected installed capacity of approximately 6700 MW), this impact will significantly increase. The results provide very useful information for the CAISO to adjust its scheduling and real-time dispatch systems to reliably accommodate future wind generation additions within the CAISO Balancing Authority.

/pdf/operational-impacts-of-wind-generation-on-california-power-4ensdj5ovs.pdf

Operational Impacts of Wind Generation on California Power Systems

The Market Value of Variable Renewables

This paper presents a data-driven approach for estimating the degree of variability and predictability associated with large-scale wind energy production for a planned integration in a given geographical area, with an application to The Netherlands. A new method is presented for generating realistic time series of aggregated wind power realizations and forecasts. To this end, simultaneous wind speed time series—both actual and predicted—at planned wind farm locations are needed, but not always available. A 1-year data set of 10-min averaged wind speeds measured at several weather stations is used. The measurements are first transformed from sensor height to hub height, then spatially interpolated using multivariate normal theory, and finally averaged over the market resolution time interval. Day-ahead wind speed forecast time series are created from the atmospheric model HiRLAM (High Resolution Limited Area Model). Actual and forecasted wind speeds are passed through multi-turbine power curves and summed up to create time series of actual and forecasted wind power. Two insights are derived from the developed data set: the degree of long-term variability and the degree of predictability when Dutch wind energy production is aggregated at the national or at the market participant level. For a 7.8 GW installed wind power scenario, at the system level, the imbalance energy requirements due to wind variations across 15-min intervals are ±14% of the total installed capacity, while the imbalance due to forecast errors vary between 53% for down- and 56% for up-regulation. When aggregating at the market participant level, the balancing energy requirements are 2–3% higher. Copyright © 2008 John Wiley & Sons, Ltd.

/pdf/estimation-of-variability-and-predictability-of-large-scale-1ei7vuobi5.pdf

Estimation of variability and predictability of large‐scale wind energy in The Netherlands

The nature of turbulent flow towards, near and behind a wind turbine, the effect of turbulence on the electricity production and the mechanical loading of individual and clustered wind turbines, and some future issues are discussed.

https://iopscience.iop.org/article/10.1088/1742-6596/318/7/072005/pdf

Turbulence and wind turbines

A dynamic wind farm aggregate model for the simulation of power fluctuations due to wind turbulence

In Nederland hebben marktpartijen de taak om de balans in het elektriciteitsnette handhaven. Deze partijen zijn wettelijk verantwoordelijk voor het afstemmen van invoeding en afname binnen hun programma. Door het wisselend windaanbod heeft invoeding vanuit windenergie inherent te maken met onbalans. Is het nu gewenst om het vermogen van windturbines te voorspellen als bijdrage aan de netbalans? Om dit vast te stellen heeft ECN een geavanceerde windvermogen voorspeller gemaakt. De praktijkvoorbeelden laten zien dat voor elke 3 kWh windstroom er 1 kWh onbalans is. Met eenvoudiger methoden zou de onbalans 1,3 kWh zijn. Hieruit blijkt dat geavanceerde voorspellingen de onbalans weliswaar verkleinen (vergeleken met eenvoudiger alternatieven), maar niet verhinderen (zoals nodig binnen de taakstelling). Gegeven het Nederlandse prijsinstrument dat kosten toerekent aan een marktpartij met onbalans, leiden voorspellingen tot lagere onbalanskosten maar niet tot het verdwijnen van deze kosten. Gezien vanuit het perspectief van netbalanshandhaving of van een marktpartij, zijn wind- vermogen voorspellingen dus nuttig maar niet afdoende. Om de onbalans en de onbalanskosten te vermijden, zullen marktpartijen met windvermogen in Nederland ook andere instrumenten moeten inzetten.

A.J. Brand

Papers

Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch

Estimation of variability and predictability of large‐scale wind energy in The Netherlands

Turbulence and wind turbines

A dynamic wind farm aggregate model for the simulation of power fluctuations due to wind turbulence

Aanbodvoorspeller duurzame energie - Deel 2: Korte-termijn prognose van windvermogen