[align=center]
Sustainable Microgrids: Modeling, Optimization, And Cost Ana
Published 9/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 34m | Size: 140 MB
Learn to design, optimize and evaluate microgrids with exergy, LCA, and cost analysis"
What you'll learn[/center]

Model and simulate hybrid microgrids integrating PV, battery, diesel, and biogas systems
Apply multi-objective optimization techniques (GA, Pareto front) to energy systems
Evaluate system performance using LCOE, CAPEX/OPEX, and CO₂ emissions metrics
Analyze exergy efficiency and perform Life Cycle Assessment (LCA) for sustainability
Build and interpret dispatch strategies using Python and MATLAB
Translate technical results into actionable insights for energy planning and policy
Learn to translate technical modeling results into actionable insights for energy planning and policy decisions.
Requirements
No prior experience in optimization, LCA, or exergy required. Basic familiarity with MATLAB or Python is helpful, but all key concepts and tools are introduced progressively
Basic understanding of energy systems is helpful, but not required. You'll be guided step by step through all technical concepts and modeling tools.
Description
This course provides a comprehensive and hands-on introduction to sustainable microgrid design and optimization, bringing together environmental assessment, thermodynamic rigor, and economic evaluation in a unique and practical way. Rather than focusing on theory alone, it equips you with the analytical and computational tools needed to model, simulate, and optimize microgrid systems under real-world conditions.You will explore how to apply Life Cycle Assessment (LCA) to quantify environmental impacts, how to use exergy analysis to measure energy efficiency at the system level, and how to employ multi-objective optimization tools to balance trade-offs between cost, performance, and sustainability. Through guided exercises in MATLAB and Python, combined with real datasets, you will learn how to simulate energy flows, compare technology pathways, and critically assess design options for biogas, solar, hybrid, and other renewable energy systems.Beyond the technical dimension, the course emphasizes the economic and strategic aspects of microgrids. You will gain practical skills to calculate CAPEX, OPEX, and LCOE, conduct sensitivity analyses, and benchmark performance across scenarios-skills that are directly applicable to project planning, investment appraisal, and policy support.Designed for engineers, consultants, researchers, and institutional decision-makers, this modular and bilingual program offers flexibility and immediate applicability. Each module integrates case studies, quizzes, and downloadable resources to reinforce learning and support independent practice.By the end of the course, you will be able not only to design and optimize microgrids but also to build your own simulation engine, communicate results effectively, and provide evidence-based insights that guide energy policy, business strategy, and technical innovation. This training will sharpen your system-level thinking, preparing you to address the urgent energy challenges of both emerging economies and advanced contexts with confidence, precision, and impact.
Who this course is for
This course is designed for engineers, energy consultants, and advanced students interested in modeling and optimizing sustainable microgrids. It's ideal for those working in renewable energy, rural electrification, or energy planning-especially in island or off-grid contexts. Whether you're a technical decision-maker, a researcher, or a practitioner looking to apply Python/MATLAB to real-world energy systems, this course will give you the tools to simulate, evaluate, and improve hybrid microgrid performance.
Engineers, energy consultants, advanced students, and technical decision-makers seeking to master modeling, optimization, and environmental evaluation of sustainable microgrids using MATLAB and Python.