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Energy Flow Optimization in Decentralized Grids
( 30 Modules )

Module #1
Introduction to Decentralized Grids
Overview of decentralized grids, their benefits and challenges, and the importance of energy flow optimization.
Module #2
Energy Flow Fundamentals
Review of energy flow concepts, including power flow, voltage, and current in AC and DC systems.
Module #3
Decentralized Grid Architecture
Overview of decentralized grid architecture, including microgrids, nanogrids, and community energy systems.
Module #4
Energy Storage in Decentralized Grids
Importance of energy storage in decentralized grids, types of energy storage systems, and their applications.
Module #5
Renewable Energy Sources in Decentralized Grids
Overview of renewable energy sources, including solar, wind, and hydro power, and their integration into decentralized grids.
Module #6
Energy Flow Optimization Problem Formulation
Formulation of the energy flow optimization problem, including objective functions, constraints, and variables.
Module #7
Linear Programming and Optimization Methods
Introduction to linear programming and optimization methods, including simplex method, dual simplex method, and interior point method.
Module #8
Mixed-Integer Linear Programming and Optimization Methods
Introduction to mixed-integer linear programming and optimization methods, including branch and bound method and cutting plane method.
Module #9
Dynamic Programming and Optimization Methods
Introduction to dynamic programming and optimization methods, including Bellmans principle of optimality and dynamic programming algorithms.
Module #10
Metaheuristics and Optimization Methods
Introduction to metaheuristics and optimization methods, including genetic algorithms, simulated annealing, and ant colony optimization.
Module #11
Energy Flow Optimization Algorithms
Overview of energy flow optimization algorithms, including linear and nonlinear programming, and metaheuristics.
Module #12
Distributed Energy Flow Optimization
Distributed energy flow optimization methods, including consensus-based optimization and distributed gradient descent.
Module #13
Decentralized Energy Flow Optimization Case Studies
Case studies of decentralized energy flow optimization in microgrids, nanogrids, and community energy systems.
Module #14
Energy Flow Optimization with Energy Storage
Optimization of energy flow with energy storage systems, including battery management and charging/discharging strategies.
Module #15
Energy Flow Optimization with Renewable Energy Sources
Optimization of energy flow with renewable energy sources, including solar and wind power forecasting and uncertainty management.
Module #16
Energy Flow Optimization with Electric Vehicles
Optimization of energy flow with electric vehicles, including vehicle-to-grid and vehicle-to-home applications.
Module #17
Energy Flow Optimization with Demand Response
Optimization of energy flow with demand response, including price responsive and load shifting strategies.
Module #18
Energy Flow Optimization with Microgrids
Optimization of energy flow in microgrids, including islanding and grid-connected operation.
Module #19
Energy Flow Optimization with Nanogrids
Optimization of energy flow in nanogrids, including residential and commercial applications.
Module #20
Energy Flow Optimization with Community Energy Systems
Optimization of energy flow in community energy systems, including shared energy storage and renewable energy systems.
Module #21
Energy Flow Optimization with Distribution Grids
Optimization of energy flow in distribution grids, including feeder optimization and voltage optimization.
Module #22
Energy Flow Optimization with Transmission Grids
Optimization of energy flow in transmission grids, including line flow optimization and contingency analysis.
Module #23
Energy Flow Optimization with Grid Resiliency
Optimization of energy flow with grid resiliency, including islanding and self-healing strategies.
Module #24
Energy Flow Optimization with Cybersecurity
Optimization of energy flow with cybersecurity, including threat detection and mitigation strategies.
Module #25
Energy Flow Optimization with Data Analytics
Optimization of energy flow with data analytics, including predictive analytics and machine learning applications.
Module #26
Energy Flow Optimization with IoT and Edge Computing
Optimization of energy flow with IoT and edge computing, including real-time data processing and control.
Module #27
Energy Flow Optimization with Blockchain
Optimization of energy flow with blockchain, including peer-to-peer energy trading and secure energy transactions.
Module #28
Energy Flow Optimization with Policy and Regulations
Optimization of energy flow with policy and regulations, including net metering and renewable portfolio standards.
Module #29
Energy Flow Optimization with Technical and Economic Analysis
Technical and economic analysis of energy flow optimization, including cost-benefit analysis and sensitivity analysis.
Module #30
Course Wrap-Up & Conclusion
Planning next steps in Energy Flow Optimization in Decentralized Grids career


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