Client Background

Client: A Leading Energy Firm in the USA

Industry Type: Energy

Services: Power, Energy, Distribution

Organization Size: 5000+

Project Objective

To create an agent based model of a virtual power plant in Netlogo. To see the function of multiple such power plants that worked simultaneously. These power plants created and supplied energy based on a demand parameter that can be controlled by the observer

Project Description

  • The client defined specific requirements as to how he wanted the model to be. 
  • The requirements were divided into 4 parts. Each successive part increased in complexity and required the model to be adjusted or configured to fit that part into it
  • The entire model when completed contained all the four parts defined by the client in the Statement of work. 

Our Solution

  • Created the model according to requirements. 
  • The clustering of multiple agents and their position is decided mathematically based on the total number of agents and the sum of their energies. The agents form a cluster based on the condition that the sum of their power is a figure that is above a certain threshold amount, the threshold amount is also decided by the observer.

Project Deliverables

Tools used

-Netlogo

– python 

Language/techniques used

  • Netlogo uses a specific language that resembles the logo language but has it’s unique syntax and variations in the way variables are stored and how a list is parsed 

Models used

  • Clustering

Skills used

  • Netlogo programming 

What are the technical Challenges Faced during Project Execution

  • The major challenge was controlling the behavior of each agent in the model. The lack of understanding of the language and the available resources about it made it challenging to figure out the actual behavior of the agents and the overall model. 
  • The decision to decide where exactly each agent will cluster on the grid was difficult primarily because each agent spawned on a random patch of the screen. This meant that each agent would have to be given a spot to land on and form a cluster with other agents. 
  • The next challenge was deciding the condition on which the agents will cluster as their relative distance to each other couldn’t be used as a parameter as it wasn’t relevant to the model’s purpose. 

How the Technical Challenges were Solved

  • The technical challenges were solved by extensive research and referring to several forums over the span of 2 months. 

Project Snapshots

Project Video

https://www.youtube.com/watch?v=1fzCUzZ0q0Q&ab_channel=Blackcoffer

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