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Title: Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch

Abstract

This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it has been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient conditionmore » has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.« less

Authors:
 [1];  [1];  [1];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1344064
Report Number(s):
PNNL-26084
DOE Contract Number:
AC05-76RL01830
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
96 KNOWLEDGE MANAGEMENT AND PRESERVATION; Stochastic optimization; decision-making; probability density functions; economic power dispatch

Citation Formats

Wang, Hong, Wang, Shaobu, Fan, Rui, and Zhang, Zhuanfang. Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch. United States: N. p., 2016. Web. doi:10.2172/1344064.
Wang, Hong, Wang, Shaobu, Fan, Rui, & Zhang, Zhuanfang. Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch. United States. doi:10.2172/1344064.
Wang, Hong, Wang, Shaobu, Fan, Rui, and Zhang, Zhuanfang. 2016. "Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch". United States. doi:10.2172/1344064. https://www.osti.gov/servlets/purl/1344064.
@article{osti_1344064,
title = {Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch},
author = {Wang, Hong and Wang, Shaobu and Fan, Rui and Zhang, Zhuanfang},
abstractNote = {This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it has been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.},
doi = {10.2172/1344064},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 9
}

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