🎏 Wind Turbines Multi-Objective Optimization

In this project we aim to solve a multi objective optimization problem using Evolutionary Algorithms and Particle Swarm Intelligence Optimization.

• EA (implemented)
• PSO

You have been commissioned by Brazil to find in which city to place wind turbines in order to maximize the energy production, plus you also have to decide where to place a power plant in order to minimize infrastructure cost 🤯. Will you be able to find the solution for 110 cities that are very far from each other? 😈

💡 We actually found a dataset containing information about the weather in Brazil, here the reference.

We want to optimize the placement of wind turbines in the Brazil region by considering the following:

• Power Plant: transport energy from wind turbines to power plant and from power plant to cities
• Limited types of wind turbines: there are more than one kind of wind turbines

🚀 Project Timeline

• Defining Main Project Objectives
• Reading Papers about the topic
• Gather Data
• Clean Data
• Statistical Inference on data
• Test windpowerlib as fitness function for power generation of wind turbines
• Implement fitness function for wind turbines placement
• Gather Data about cost and activation function the choosen wind turbines
• Euclidian distance fitness function for placing the power plant
• Collect matplotlib graphs, Pareto fronts in particular
• Writing Analysis

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