Uncertainty
In order to obtain the ex-ante least-cost schedule of energy generation and reserves for online generating units, the system operator addresses a dynamic decision-making process known as the economic dispatch (ED) problem. Current industry practice involves adopting a deterministic two-stage optimization framework that relies on a one-day-ahead horizon and a forecast of uncertain parameters. The optimal solution to the resulting problem thus yields a generation schedule for the entire day ahead.
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To test the effectiveness of different ambiguity models in representing real decision-making under ambiguity, we ran an incentivized experiment of choice under ambiguity. The study involved 310 participants recruited using the online international labor market, Amazon Mechanical Turk (MTurk), to participate in an experimental study implemented on the survey platform, Qualtrics. Each of the 310 subjects made 150 preference choices between two options involving variations of the four ambiguity problems with varying levels of ambiguity and risk.
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This text and the attached codes are related with a submitted manuscript [K. Maham, P. Kärhä, and E. Ikonen, “Spectral mismatch uncertainty estimation in solar cell calibration using Monte Carlo simulation,” (submitted)]. Various comments in the code refer to equations in this manuscript. A link to the article will be added after acceptance.
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This document provides the data for the case studies of the work “Computational Performance Enhancement Strategies for Risk-Averse Two-Stage Stochastic Generation and Transmission Network Expansion Planning”.
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The attached file include the data used in the case study of paper "An Adjustable Robust Optimization Approach for the Expansion Planning of a Virtual Power Plant".
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In this data set, a power transistor’s uncertainty added S-parameters, its estimated S-parameters, uncertainty added S-parameters of a power amplifier circuit, uncertainty added S-parameters of a cascaded amplifier, and amplifier’s design files are presented. Sumitomo’s GaAs-FET FLL57MK is used for the measurements and design. Cadence AWR is used for the power amplifier design. The power amplifier is designed for 2.4 GHz, using S-parameters.
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S-parameter data with uncertainty information are presented in the data set. High power RF transistors are measured with a regular measurement setup, consisting of a VNA, coaxial cables, bias tees, and fixture. Measured transistors are FLL57MK (GaAs-FET), LP601 (LDMOS-FET), CLF1G0060S-10 (GaN-HEMT), T2G6000528-Q3 (GaN-HEMT), CGH40010-F (GaN-HEMT). The data can be used to analyze for uncertainty studies and designing with uncertainty added S-parameters.
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