A Real Time, Wireless And Low Cost Data Acquisition System For Residential Pv Modules
Product Description
Aim:
Aim of this projects is to build a Weather and Load forecasting system for residential microgrid systems using machine learning algorithm.
Introduction:
Sustainable
development and environmental issues are crucial objectives of the energy
sector. Re-structure of the electrical power market, diffusion of the renewable
energy technologies, promotion of distributed generation (DG), and transmission
integration are some leading tools for the energy sector to sustainable
development as its ultimate goal. The deployment of DG units has received a
great deal of attention. For instance, renewable energy sources (RESs)
accounted for 26.5% of the global electrical power demand in 2017, and it is
predicted to increase in next years.
Prosumers- An
individual who produce and consume the value. Prosumer microgrid systems are
grabbing attention in recent studies. Such this systems person who producing
the electricity using power sources like Photo Voltaic Modules (PV Modules) and
Wind turbine. To effectively utilize these kind of systems we are proposing a
model which forecast the Load and Weather. By forecasting production of
electricity and consumption of electricity we effectively control the microgrid
system and also can store it in batteries. Based on forecasted data, we can analyze
the Battery storage system and we can minimize the cost of maintaining it.
In this system, we are having 6 nodes with different value of nodes and all the nodes connected to the main server. Within sever system, we are running machine learning algorithms to forecast the weather and load. Each node contains NodeMCU, Current sensor, voltage sensor and various loads. Here, Raspberry pi act as server system which portable and power efficient.
Proposed
System:
Proposed system forecasts the load and weather using SVM algorithm based
on stored data from various nodes. Every node contains Current sensor, voltage
sensor, Node MCU as a controller and loads with different values. Each node
sends their values to server through local network.
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Package Includes
Software Projects Includes
- Demo Video
- Abstract
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The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days
Hardware Projects Includes
- Demo Video
- Abstract
- Base paper
- Full Project PPT
- Datasheets
- Circuit Diagrams
- Source Code
- Screen Shots & Photos
- Software Links
- Reference Papers
- Lit survey
- Full Project Documentation
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The Delivery time for Hardware
projects is 7-8 working days.
Mini Projects: Software Includes
- Demo Video
- Abstract
- Base paper
- Full Project PPT
- UML Diagrams
- SRS
- Source Code
- Screen Shots
- Software Links
- Reference Papers
- Full Project Documentation
- Online support
The
Delivery time for software Miniprojects is 2 -3 working days.
Mini Projects - Hardware includes
- Demo Video
- Abstract
- PPT
- Datasheets
- Circuit Diagrams
- Source Code
- Screen Shots & Photos
- Software Links
- Reference Papers
- Full Project Documentation
- Online
support
The Delivery time for Hardware Mini projects is 7-8 working days.