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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Scenario Reduction For Stochastic Unit Commitment With Wind Penetration, Yonghan Feng, Sarah M. Ryan Jan 2014

Scenario Reduction For Stochastic Unit Commitment With Wind Penetration, Yonghan Feng, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Uncertainties in the day-ahead forecasts for load and wind energy availability are considered in a reliability unit commitment problem. A two-stage stochastic program is formulated to minimize total expected cost, where commitments of thermal units are viewed as first-stage decisions and dispatch is relegated to the second stage. Scenario paths of hourly loads are generated according to a weather forecast-based load model. Wind energy scenarios are obtained by identifying analogue historical days. Net load scenarios are then created by crossing scenarios from each set and subtracting wind energy from load. A new heuristic scenario reduction method termed forward selection in ...


Temporal Vs. Stochastic Granularity In Thermal Generation Capacity Planning With Wind Power, Shan Jin, Audun Botterud, Sarah M. Ryan Jan 2014

Temporal Vs. Stochastic Granularity In Thermal Generation Capacity Planning With Wind Power, Shan Jin, Audun Botterud, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Publications

We propose a stochastic generation expansion model, where we represent the long-term uncertainty in the availability and variability in the weekly wind pattern with multiple scenarios. Scenario reduction is conducted to select a representative set of scenarios for the long-term wind power uncertainty. We assume that the short-term wind forecast error induces an additional amount of operating reserves as a predefined fraction of the wind power forecast level. Unit commitment (UC) decisions and constraints for thermal units are incorporated into the expansion model to better capture the impact of wind variability on the operation of the system. To reduce computational ...


Impact Of Demand Response On Thermal Generation Investment With High Wind Penetration, Shan Jin, Audun Botterud, Sarah M. Ryan Nov 2013

Impact Of Demand Response On Thermal Generation Investment With High Wind Penetration, Shan Jin, Audun Botterud, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Publications

We present a stochastic programming model for investments in thermal generation capacity to study the impact of demand response (DR) at high wind penetration levels. The investment model combines continuous operational constraints and wind scenarios to represent the implications of wind variability and uncertainty at the operational level. DR is represented in terms of linear price-responsive demand functions. A numerical case study based on load and wind profiles of Illinois is constructed with 20 candidate generating units of various types. Numerical results show the impact of DR on both investment and operational decisions. We also propose a model in which ...


Toward Scalable, Parallel Progressive Hedging For Stochastic Unit Commitment, Sarah M. Ryan, Roger J.B. Wetts, David L. Woodruff Jan 2013

Toward Scalable, Parallel Progressive Hedging For Stochastic Unit Commitment, Sarah M. Ryan, Roger J.B. Wetts, David L. Woodruff

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Abstract: Given increasing penetration of variable generation units, there is significant interest in the power systems research community concerning the development of solution techniques that directly address the stochasticity of these sources in the unit commitment problem. Unfortunately, despite significant attention from the research community, stochastic unit commitment solvers have not made their way into practice, due in large part to the computational difficulty of the problem. In this paper, we address this issue, and focus on the development of a decomposition scheme based on the progressive hedging algorithm of Rockafellar and Wets. Our focus is on achieving solve times ...