Swarm Based Ocean Energy Harvesters

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Low Cost Swarm Autonomous Vehicles
for
Ocean Energy Harvesting

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Energy requirements of Indian sub continent
Power Consumption 2014-2015
Energy(MU)
-100,000
0
100,000
200,000
300,000
400,000
Region
northern western southern eastern north-eastern
Energy Requirement Energy Generated Demand
Power Requirement in 2016-17
Energy(MU)
-125,000
0
125,000
250,000
375,000
500,000
Region
northern western southern eastern north-eastern
Energy requirement Energy generated Demand

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Renewable Energy in India
Renewable Energy in Indian coastal areasEnergyin(MU)
0
3500
7000
10500
14000
Coastal Areas in India
Mumbai Goa Mangalore coastal kerla Kanniyakumari Tuticorin Pondicherry Chennai Nellore Visakhapatnam Bhubaneswar diu and daman
Energy Generated Energy Consume Demand

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Energy Storage
Unit
Swarm
Charging Unit
10 meters
30 meters
50 meters
Swarm 1
Swarm 1
Swarm 2
Swarm 3
Swarm 4
Swarm 5
Swarm
Master
Sea Level
Acoustics
Channels
Environment monitoring
sensors:
• Salinity(pH)
• Ocean Current
• Temperature
System Overview
AUV

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Swarm
7
Swarm
4
Swarm
8
Swarm
5
Swarm
6
Swarm
2
Swarm 1
Swarm
3
Energy
Storage Unit
AUV
0-15 mts
15-30 mts
30-50 mts
Swarm
Charging
Unit
Top View

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Concept
▪ AUVs Energy Harvesters will convert the infinite Kinetic energy of the ocean
stream into electricity.
▪ One swarm acts like a Master and guides the other swarms based on
the ATON’s Predictive Algorithm.
▪ Swarm has various sensors that can percept the Environmental changes like
Salinity pH variations, temperature, pressure and flow directions of water.
▪ Buoy in the surface of water is to predict the atmospheric weather conditions
like wind flow, moisture, temperature, etc.
▪ Risk Analysis Management system predicts the wave pattern with the help of
Doppler Current Wave Guide and intimates the swarm of AUVs to make a
formation that can generates its max. Energy efficiency.

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ATON
▪ Autonomously Taking actiON Intelligence System
▪ Intelligent Energy Harvest
▪ Monitor – Predict - Analyze the marine ecology.
▪ Reinforced actions in the time of Decision Making Delay and Autonomous
Decision Failure
▪ Risk Analyzing by Identifying sensor data patterns in Marine Ecological
system

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Inertial
Measurement
Unit (IMU)
Camera
Turbine
Acoustic sensors
Environment
monitoring
sensors
ATON
Algorithm
Swarm AUV with ATON

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Conclusion
▪ Unlimited Unexplored Energy in Low Cost Installation
▪ Predicting the Environmental Data Patterns
▪ Maintaining Balanced Biological Marine Ecosystem
▪ Surveillance of coastal areas

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THANK YOU
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