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5.0
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5.0
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1,000
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99%
Would take again
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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
MECH 6342 Jie Zhang | |||||
A | |||||
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| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
MECH 6342 Jie Zhang | |||||
A | |||||
Grades: 513
Median GPA: A-
Mean GPA: 3.567
4.1
Professor rating
3.3
Difficulty
27
Ratings given
78%
Would take again
Renewable Energy and Grid Integration
MECH 6342
Erik Jonsson School of Engineering and Computer Science
This course will discuss renewable energy and energy efficiency systems modeling, design, and optimization. After examining the technological specifications of the most important renewable energy resources (e.g., wind energy, photovoltaics, and solar thermal power) and energy efficiency technologies (e.g., energy storage, home and building energy, electric vehicles), grid integration of renewable energy and energy efficiency technologies will be examined in detail. All of these concepts will be explored in great detail and reinforced through the completion of a semester long project, where the students will be solving problems of broad interest in a group setting. Students will use Matlab and R for project design. The course builds on prerequisite knowledge in engineering system design, engineering mathematics, probability and statistics, and optimization methods. 3 credit hours.
Offering Frequency: Based on student interest and instructor availability
Grades: 49
Median GPA: A
Mean GPA: 3.816
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Grades: 513
Median GPA: A-
Mean GPA: 3.567
4.1
Professor rating
3.3
Difficulty
27
Ratings given
78%
Would take again
Renewable Energy and Grid Integration
MECH 6342
Erik Jonsson School of Engineering and Computer Science
This course will discuss renewable energy and energy efficiency systems modeling, design, and optimization. After examining the technological specifications of the most important renewable energy resources (e.g., wind energy, photovoltaics, and solar thermal power) and energy efficiency technologies (e.g., energy storage, home and building energy, electric vehicles), grid integration of renewable energy and energy efficiency technologies will be examined in detail. All of these concepts will be explored in great detail and reinforced through the completion of a semester long project, where the students will be solving problems of broad interest in a group setting. Students will use Matlab and R for project design. The course builds on prerequisite knowledge in engineering system design, engineering mathematics, probability and statistics, and optimization methods. 3 credit hours.
Offering Frequency: Based on student interest and instructor availability
Grades: 49
Median GPA: A
Mean GPA: 3.816
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