MAK 4067E – RENEWABLE ENERGY SYSTEMS

 MAK 4067E  –  RENEWABLE ENERGY SYSTEMS

2026–2027 Fall Semester  |  CRN: 14964

 

 

Lecturer	Seyhan ONBAŞIOĞLU
Room	537
E-mail	onbasiogl1@itu.edu.tr
Office Hours	Any time by appointment
Course Hours	Tuesday  14:30–17:30

 

Course Description

Sustainable energy and utilization of energy sources. Fundamental concepts: Energy 5.0 & Autonomous Energy Grids, AI-driven multi-source energy modulation, resilient microgrids, Demand-Supply Analysis, Scale Analysis, Capacity Factor, Effectiveness. Geothermal energy utilization: Thermodynamic cycles, heat pumps. Wind energy utilization: Basic aerodynamics, statistics, capacity factor. Biomass Conversion: Anaerobic digestion, gasification, power generation. Hydrogen Energy & Production, Fuel Cells. Solar Energy: Concentrated thermal power, Photovoltaic Systems, solar modules. Energy Storage & Batteries. Fusion Energy.

Textbooks

Main Textbook (Recommended)

da Rosa, A. V., & Ordonez, J. C., Fundamentals of Renewable Energy Processes, 4th Edition, Academic Press / Elsevier, 2021. ISBN: 978-0-12-819036-3

This single-volume text is the recommended replacement for the instructor's lecture notes. It covers all core topics of the course—solar (thermal and PV), wind, geothermal, hydrogen and fuel cells, biomass, ocean/tidal energy, and energy storage—with rigorous thermodynamic and engineering analysis. The 4th edition introduces updated material on grid integration, efficiency metrics, and capacity-factor analysis. It is available as an e-book through Elsevier ScienceDirect.

Supplementary Textbooks

General Renewable Energy Coverage

Twidell, J., & Weir, T., Renewable Energy Resources, 3rd Edition, Routledge / Taylor & Francis, 2015. ISBN: 978-0-415-58437-0 — Accessible engineering treatment; excellent problem sets; strong chapters on wind statistics, solar geometry, and hydropower.

Sorensen, B., Renewable Energy: Physics, Engineering, Environmental Impacts, Economics and Planning, 5th Edition, Academic Press, 2017. ISBN: 978-0-12-804567-1 — Broad physics-based perspective from resource assessment to life-cycle economics; valuable for the demand-supply and scale-analysis parts of the course.

Kreith, F., & Goswami, D. Y. (Eds.), Energy Efficiency and Renewable Energy Handbook, CRC Press, 2016. ISBN: 978-1-4665-9672-6 — Encyclopaedic reference handbook; useful for geothermal, biomass, and storage chapters.

Hodge, B. K., Alternative Energy Systems and Applications, 2nd Edition, John Wiley & Sons, 2017. ISBN: 978-1-119-04680-7 — Practical engineering focus; good treatment of geothermal heat pumps and solar collectors.

AI for Energy Systems & Smart Microgrids (Weeks 4 and 10)

Bordons, C., Garcia-Torres, F., & Ridao, M. A., Model Predictive Control of Microgrids, Springer, 2019. https://doi.org/10.1007/978-3-030-24570-2 — Primary ML/control reference for AI-driven multi-source energy modulation and autonomous dispatch.

Li, Y., Zhao, Y., Wu, L., & Zeng, Z., Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch, Springer, 2023. https://doi.org/10.1007/978-981-99-0639-0 — Load/generation forecasting with deep learning, PINNs, and multi-agent control; directly supports Weeks 4 and 10 material.

Topic-Specific References

Sundén, B., Hydrogen, Batteries and Fuel Cells, Academic Press, 2019. https://doi.org/10.1016/C2018-0-01247-5 — Detailed electrochemical and thermodynamic treatment; closely matches Weeks 7 and 9.

Hayes, J. G., & Goodarzi, G. A., Electric Powertrain: Energy Systems, Power Electronics and Drives for Hybrid, Electric and Fuel Cell Vehicles, John Wiley & Sons, 2018. ISBN: 978-1-119-06364-4 — Supports battery management and energy storage discussions.

 

Assessment Criteria

Component	Weight	Details
Quizzes (6 × 5 pts)	30 pts	Weeks 2, 4, 6, 8, 10, 12
Project & Essay	30 pts	Large-scale system design with AI dispatch
Final Exam	40 pts

⚠  70 % attendance and a minimum of 3 completed quizzes are required to sit for the final exam.

The course project focuses on the design of a large-scale energy system incorporating statistical demand/supply analysis and AI-driven multi-source dispatch.

Course Plan

Week	Date	Topic
1	Sept. 29	Introduction and General Concepts  (Energy 5.0, Human-Centric & Autonomous Energy Systems)
2	Oct. 6	Geothermal Energy
3	Oct. 13	Wind Energy
4	Oct. 20	AI for Energy Systems: Machine learning for load/generation forecasting, PINNs, and multi-source energy modulation
5	Oct. 27	Solar Power (Thermal Energy Conversion)
6	Nov. 3	Solar Power (Direct Energy Conversion & Photovoltaic Systems)
7	Nov. 10	Fuel Cells: Thermodynamics & Operation
8	Nov. 17	Presentation of Intermediate Calculations of the Project
9	Nov. 24	Hydrogen Production / Hydrogen Storage
10	Dec. 1	Smart Microgrids & Autonomous Dispatch: Multi-agent control, real-time power balance, and smart inverter modulation
11	Dec. 8	Energy Storage Systems & Battery Management Systems (BMS)
12	Dec. 15	Biomass Conversion Processes (Anaerobic Digestion)
13	Dec. 22	Biomass Conversion Processes (Gasification)
14	Dec. 29	Fusion Energy