Modeling and Optimization of a Longitudinally-Distributed Global Solar Grid
Not on the map. Why?
Abstract (arXiv)
Our simulation-based experiments are aimed to demonstrate a use case on the feasibility of fulfillment of global energy demand by primarily relying on solar energy through the integration of a longitudinally-distributed grid. These experiments demonstrate the availability of simulation technologies, good approximation models of grid components, and data for simulation. We also experimented with integrating different tools to create realistic simulations as we are currently developing a detailed tool-chain for experimentation. These experiments consist of a network of model houses at different locations in the world, each producing and consuming only solar energy. The model includes houses, various appliances, appliance usage schedules, regional weather information, floor area, HVAC systems, population, number of houses in the region, and other parameters to imitate a real-world scenario. Data gathered from the power system simulation is used to develop optimization models to find the optimal solar panel area required at the different locations to satisfy energy demands in different scenarios.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Jun 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 4; 2024: 1.
5 papers.
- 2023Search for universal minimum drag resistance underwater vehicle hull using CFDcited by 8
- 2023Fusion of ML with numerical simulation for optimized propeller designcited by 5
- 2023Vehicle lateral control using Machine Learning for automated vehicle guidancecited by 2
- 2024Automatic AI controller that can drive with confidence: steering vehicle with uncertainty knowledgecited by 1
- 2023Systematic design space exploration by learning the explored space using Machine Learningcited by 0
- 2024Automatic AI controller that can drive with confidence: steering vehicle with uncertainty knowledge24 Apr 2024
- 2023Systematic design space exploration by learning the explored space using Machine Learning14 Mar 2023
- 2023Vehicle lateral control using Machine Learning for automated vehicle guidance14 Mar 2023
- 2023Fusion of ML with numerical simulation for optimized propeller design28 Feb 2023
- 2023Search for universal minimum drag resistance underwater vehicle hull using CFD18 Feb 2023