Rüdiger Barth

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

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.

A Stochastic Unit-commitment Model for the Evaluation of the Impacts of Integration of Large Amounts of Intermittent Wind Power

A large share of integrated wind power causes technical and financial impacts on the operation of the existing electricity system due to the fluctuating behaviour and unpredictability of wind power. The presented stochastic bottom-up electricity market model optimises the unit commitment considering five kinds of markets and taking explicitly into account the stochastic behaviour of the wind power generation and of the prediction error. It can be used for the evaluation of varying electricity prices and system costs due to wind power integration and for the investigation of integration measures

WILMAR: A Stochastic Programming Tool to Analyze the Large-Scale Integration of Wind Energy

Wind power is highly variable and partly unpredictable and therefore energy systems of the future have to cope with increased variability and stochasticity. The paper describes the use of a novel stochastic programming model to assess the impact of increased wind power generation on electricity systems. This WILMAR model takes explicitly the stochastic behavior of wind generation and the forecast errors into account. Also a detailed modeling of power plant, grid and market characteristics is performed. WILMAR thus allows to assess the impact of increased wind generation on reserve needs and usage, power plant operation and system cost.

Simulation of short-term forecasts of wind and load for a stochastic scheduling model

A tool is presented that generates stochastic input parameters consisting of simulated short-term wind power and load forecasts required by a stochastic scheduling model. In combination with additionally generated time-series describing the occurrence of forced outages of conventional power plants, the demand for reserves in dependency of the forecast horizon is determined. The distribution of the stochastic input parameters is represented by the use of scenario trees. Results of an exemplary application are discussed showing the dependency of simulated forecast errors on the assumed forecast error standard deviations as well as the impact on required reserves.

Operating the Irish power system with increased levels of wind power

This paper summarises some of the main impacts of large amounts of wind power installed in the island of Ireland. Using results from various studies performed on this system, it is shown that wind power will impact on all time frames, from seconds to daily planning of the system operation. Results from studies examining operation of the system with up to approximately 40% of electricity provided by wind show that some of the most important aspects to be considered include the type of wind turbine technology, the provision of reserve to accommodate wind forecasting error and the method used to plan plant schedules.

Wind power integration studies using a multi-stage stochastic electricity system model

A large share of integrated wind power causes technical and financial impacts on the operation of the existing electricity system due to the fluctuating behaviour and unpredictability of wind power. The presented stochastic electricity market model optimises the unit commitment considering four kinds of electricity markets (e.g. a spot and balancing market) and taking into account the stochastic behaviour of the wind power generation and of the prediction error. It can be used for the evaluation of varying electricity prices and system costs due to wind power integration and for the investigation of integration measures.

Regional electricity price differences due to intermittent wind power in Germany: impact of extended transmission and storage capacities

A fast growth of installed wind power capacity has been experienced in several European countries. In Germany, notably high wind power capacities are planned in the North. If the existing transmission capacities between individual regions become insufficient, the electricity prices will differ considerably and the system operation can become unstable. It is supposed that the extension of transmission capacities and the use of energy storages avoid this separation of individual regions. In this paper, the arising price differences between regions in Germany are estimated using a novel stochastic linear optimisation model that optimises the efficient power market operation on an hourly basis. To estimate the impact of extensions of transmission lines and energy storages on the electricity prices systematic case studies are undertaken. It is exemplarily shown that differences of electricity prices can be equalised with transmission capacity extensions whereas they remain with the use of storage devices.

Advanced Unit Commitment Strategies in the United States Eastern Interconnection

This project sought to evaluate the impacts of high wind penetrations on the U.S. Eastern Interconnection and analyze how different unit commitment strategies may affect these impacts.