A Chance-Constrained Programming Model for the Optimal Stopping Decision of Power R&D Project

Chang Sheng Yi; Xue Bin Guan; Jian Bing Gao

doi:10.4028/www.scientific.net/AMR.805-806.1167

Paper Titles

Impacts of Short-Term Generation Rights Transaction on Transmission Loss for Power System
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Reactive Power Optimization of Distribution System Incorporating Distributed Generations and Running Cost
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The Framework and Key Technologies of Power Grid Operation Track Oriented Automatic Smart Dispatch
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A Chance-Constrained Programming Model for the Optimal Stopping Decision of Power R&D Project
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Study on the Algorithm of Distribution Network Planning Containing Distributed Power
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Dynamic Simulation of a Microgrid with Renewable Microsources Based on DIgSILENT/PowerFactory
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Modeling and Simulation for Quantitative Assessment of Process Level Networks in Substation Based on OPNET
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Research of Building Safety Management System of Reply Protection in Power Company Based on Workflow
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 805-806A Chance-Constrained Programming Model for the...

A Chance-Constrained Programming Model for the Optimal Stopping Decision of Power R&D Project

Abstract:

A power R&D process can be regarded as a jump process of scientific knowledge full of exploration and complexity. Every jump represents a scientific breakthrough or a new discovery in this setting. In this paper, the inter-arrival times are treated as random variables observe arbitrary distributions. The ɑ-optimistic net return of project performance is proposed and a chance-constrained programming model is established to model the power R&D optimal stopping decision problem. Considering the complexity of the model, the stochastic simulation is designed to estimate the values of project return performance and the simultaneous perturbation stochastic approximation (SPSA) algorithm is employed to solve the proposed model. Finally, the effectiveness of the hybrid algorithm and the applicability of the model are illustrated by numerical examples.

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Periodical:

Advanced Materials Research (Volumes 805-806)

Pages:

1167-1170

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.805-806.1167

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Online since:

September 2013

Authors:

Chang Sheng Yi, Xue Bin Guan, Jian Bing Gao

Keywords:

Chance-Constrained Programming, Optimal Stopping, Power R&D Project, SPSA

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