scholarly journals Data-Driven Power System Optimal Decision Making Strategy under Wildfire Events

2022 ◽  
Author(s):  
Wanshi Hong ◽  
Bin Wang ◽  
Mengqi Yao ◽  
Duncan Callaway ◽  
Larry Dale ◽  
...  
Keyword(s):  
Decision Making ◽  
Power System ◽  
Data Driven ◽  
Optimal Decision ◽  
System Optimal ◽  
Optimal Decision Making

Probabilistic Spinning Reserve Model of Power System Containing Wind

2015 ◽  
Vol 799-800 ◽  
pp. 1238-1243
Author(s):  
Ning Ning Cui ◽  
Zhe Nan Zhang ◽  
Wei Liu ◽  
Yang Zhang ◽  
Qiang Li
Keyword(s):  
Decision Making ◽  
Power System ◽  
Wind Power ◽  
Optimization Model ◽  
Unit Commitment ◽  
Optimal Scheduling ◽  
Optimal Decision ◽  
Spinning Reserve ◽  
Probability Table ◽  
Optimal Decision Making

In order to reflect the influences of the stochastic uncertain of wind power on the optimal decision-making of the power system spinning reserve, a probabilistic optimization model of the spinning reserve is proposed. Considering uncertain factors such as predicted-deviation of wind, predicted-deviation of load and fault outage of generator, the capacity outage probability table is combined with predicted-deviation of wind and predicted-deviation of load. By introducing the analytic expressed probability reserve constraints into the unit commitment model considering the wind power, the spinning reserve of power system can be optimized to the expectable contingency level. Using a calculation example, the effectiveness of the model is proved, providing a new model for uncertainty analysis and optimal scheduling decisions of power system containing wind.

scholarly journals GEAR: On Optimal Decision Making with Auxiliary Data

Stat ◽  
2021 ◽  
Author(s):  
Hengrui Cai ◽  
Rui Song ◽  
Wenbin Lu
Keyword(s):  
Decision Making ◽  
Optimal Decision ◽  
Auxiliary Data ◽  
Optimal Decision Making

Operation decision of logistics service supply chain: considering interruption probability in emergencies

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guangsheng Zhang ◽  
Xiao Wang ◽  
Zhiqing Meng ◽  
Qirui Zhang ◽  
Kexin Wu
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Evolutionary Game ◽  
Optimal Strategies ◽  
Optimal Decision ◽  
Content Type ◽  
Logistics Service ◽  
Social Reputation ◽  
Punishment Intensity ◽  
Optimal Decision Making

PurposeTo remedy the inherent defect in current research that focuses only on a single type of participants, this paper endeavors to look into the situation as an evolutionary game between a representative Logistics Service Integrator (LSI) and a representative Functional Logistics Service Provider (FLSP) in an environment with sudden crisis and tries to analyze how LSI supervises FLSP's operations and how FLSP responds in a recurrent pattern with different interruption probabilities.Design/methodology/approachRegarding the risks of supply chain interruption in emergencies, this paper develops a two-level model of single LSI and single FLSP, using Evolutionary Game theory to analyze their optimal decision-making, as well as their strategic behaviors on different risk levels regarding the interruption probability to achieve the optimal return with bounded rationality.FindingsThe results show that on a low-risk level, if LSI increases the degree of punishment, it will fail to enhance FLSP's operational activeness in the long term; when the risk rises to an intermediate level, a circular game occurs between LSI and FLSP; and on a high level of risk, FLSP will actively take actions, and its functional probability further impacts LSI's strategic choices. Finally, this paper analyzes the moderating impact of punishment intensity and social reputation loss on the evolutionary model in emergencies and provides relevant managerial implications.Originality/valueFirst, by taking both interruption probability and emergencies into consideration, this paper explores the interactions among the factors relevant to LSI's and FLSP's optimal decision-making. Second, this paper analyzes the optimal evolutionary game strategies of LSI and FLSP with different interruption probability and the range of their optimal strategies. Third, the findings of this paper provide valuable implications for relevant practices, such that the punishment intensity and social reputation loss determine the optimal strategies of LSI and FLSP, and thus it is an effective vehicle for LSSC system administrator to achieve the maximum efficiency of the system.

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