Project :: ECE 445 - Senior Design Laboratory

Project

#	Title	Team Members	TA	Documents	Sponsor
29	Advanced Modeling and Display of ZJU International Campus Power System	Erkai Yu Jiahe Li Tiantong Qiao Yilang Feng		design_document1.pdf final_paper1.pdf final_paper2.pdf proposal1.pdf	Ruisheng Diao
	# Team Member (NetId) - Tiantong Qiao(tqiao4) - Erkai Yu (erkaiyu2) - Jiahe Li (jiaheli2) - Yilang Feng(yilangf2) # Problem The electricity consumption of Haining International Campus of Zhejiang University is high and the visualization is not very intuitive, we intend to build a highly visual electricity consumption model. In addition, features such as AI prediction and intelligent control may be added to optimize the power consumption of the Haining campus. # Solution Our project plan is to build a physical model of the power system in the Haining International Campus of Zhejiang University and to perform power flow calculations using electricity consumption data from the Engineering Department. The brightness/different colors of LED strips are used to represent the current, voltage, power and other information. Based on this, anomaly detection can be implemented for various types of behaviors within the grid, such as abnormal user behaviors and grid infrastructure failures. Given the historical data of power consumption, we can build a vivid demonstration of the power flow inside the campus across the year. Based on that, we can also make predictions of how the power usage will change in the future. If given the live data of power consumption, we will be able to integrate them into our system, both for live demonstration and power monitoring. We also plan to use event-driven algorithms to autonomously detect abnormal conditions or disturbances. Other advanced applications, such as AI intelligent control, grid loss calculation, and installation and connection of distributed wind/photovoltaics power sources can also be developed. # Solution Components (and Distribution of Work) 1. Physical model of the campus -- Solid modeling of international campus districts using 3D printing technology or other modeling methods(Yilang Feng) 2. Power Flow Calculations -- Use software such as OpenDSS or Matpower to calculate the power flow of the electricity consumption of the campus(Tiantong Qiao), and control the LED light bar to display horizontally.(Erkai Yu) 3. Advanced Applications: -- Power usage anomaly detection, AI intelligent control, event-driven short circuit analysis, grid loss calculation, distributed photovoltaic generation, etc(Jiahe Li). # Criterion for Success The success of our project hinges on achieving key performance criteria, including the precision and accuracy of our power flow modeling. Utilizing software like OpenDSS or Matpower, we aim to attain a high level of accuracy in depicting the power flow within the campus, ensuring close alignment with historical and real-time power consumption data. In parallel, the construction of a physically accurate model of the international campus, employing 3D printing technology or other methods, is crucial for creating an immersive and realistic demonstration. Additionally, the implementation of LED strips with varying colors and brightness levels, responsive to calculated power flow and real-time data, is essential for effective representation. Furthermore, the success criteria encompass the accurate prediction of future power usage based on historical data, validation against real-time data, seamless integration of live power consumption data, and the autonomous detection of abnormal conditions through event-driven algorithms. The project's success is further evaluated through the successful implementation and practical assessment of advanced applications such as AI intelligent control, grid loss calculation, and the integration of distributed wind/photovoltaic power sources to enhance the overall capabilities of the campus power system.

Title

Team Members

Documents

Sponsor

Advanced Modeling and Display of ZJU International Campus Power System

Erkai Yu
Jiahe Li
Tiantong Qiao
Yilang Feng

design_document1.pdf
final_paper1.pdf
final_paper2.pdf
proposal1.pdf

Ruisheng Diao

# Team Member (NetId)
- Tiantong Qiao(tqiao4)
- Erkai Yu (erkaiyu2)
- Jiahe Li (jiaheli2)
- Yilang Feng(yilangf2)

# Problem
The electricity consumption of Haining International Campus of Zhejiang University is high and the visualization is not very intuitive, we intend to build a highly visual electricity consumption model. In addition, features such as AI prediction and intelligent control may be added to optimize the power consumption of the Haining campus.

# Solution
Our project plan is to build a physical model of the power system in the Haining International Campus of Zhejiang University and to perform power flow calculations using electricity consumption data from the Engineering Department. The brightness/different colors of LED strips are used to represent the current, voltage, power and other information. Based on this, anomaly detection can be implemented for various types of behaviors within the grid, such as abnormal user behaviors and grid infrastructure failures.

Given the historical data of power consumption, we can build a vivid demonstration of the power flow inside the campus across the year. Based on that, we can also make predictions of how the power usage will change in the future. If given the live data of power consumption, we will be able to integrate them into our system, both for live demonstration and power monitoring.

We also plan to use event-driven algorithms to autonomously detect abnormal conditions or disturbances. Other advanced applications, such as AI intelligent control, grid loss calculation, and installation and connection of distributed wind/photovoltaics power sources can also be developed.

# Solution Components (and Distribution of Work)

1. Physical model of the campus
-- Solid modeling of international campus districts using 3D printing technology or other modeling methods(Yilang Feng)
2. Power Flow Calculations -- Use software such as OpenDSS or Matpower to calculate the power flow of the electricity consumption of the campus(Tiantong Qiao), and control the LED light bar to display horizontally.(Erkai Yu)
3. Advanced Applications: -- Power usage anomaly detection, AI intelligent control, event-driven short circuit analysis, grid loss calculation, distributed photovoltaic generation, etc(Jiahe Li).

# Criterion for Success

The success of our project hinges on achieving key performance criteria, including the precision and accuracy of our power flow modeling. Utilizing software like OpenDSS or Matpower, we aim to attain a high level of accuracy in depicting the power flow within the campus, ensuring close alignment with historical and real-time power consumption data. In parallel, the construction of a physically accurate model of the international campus, employing 3D printing technology or other methods, is crucial for creating an immersive and realistic demonstration. Additionally, the implementation of LED strips with varying colors and brightness levels, responsive to calculated power flow and real-time data, is essential for effective representation. Furthermore, the success criteria encompass the accurate prediction of future power usage based on historical data, validation against real-time data, seamless integration of live power consumption data, and the autonomous detection of abnormal conditions through event-driven algorithms. The project's success is further evaluated through the successful implementation and practical assessment of advanced applications such as AI intelligent control, grid loss calculation, and the integration of distributed wind/photovoltaic power sources to enhance the overall capabilities of the campus power system.

Featured Project

# People

Scott Liu - sliu125

Connor Lake - crlake2

Aashish Kapur - askapur2

# Problem

Buses are scheduled inefficiently. Traditionally buses are scheduled in 10-30 minute intervals with no regard the the actual load of people at any given stop at a given time. This results in some buses being packed, and others empty.

# Solution Overview

Introducing the _BusPlan_: A network of smart detectors that actively survey the amount of people waiting at a bus stop to determine the ideal amount of buses at any given time and location.

To technically achieve this, the device will use a wifi chip to listen for probe requests from nearby wifi-devices (we assume to be closely correlated with the number of people). It will use a radio chip to mesh network with other nearby devices at other bus stops. For power the device will use a solar cell and Li-Ion battery.

With the existing mesh network, we also are considering hosting wifi at each deployed location. This might include media, advertisements, localized wifi (restricted to bus stops), weather forecasts, and much more.

# Solution Components

## Wifi Chip

- esp8266 to wake periodically and listen for wifi probe requests.

## Radio chip

- NRF24L01 chip to connect to nearby devices and send/receive data.

## Microcontroller

- Microcontroller (Atmel atmega328) to control the RF chip and the wifi chip. It also manages the caching and sending of data. After further research we may not need this microcontroller. We will attempt to use just the ens86606 chip and if we cannot successfully use the SPI interface, we will use the atmega as a middleman.

## Power Subsystem

- Solar panel that will convert solar power to electrical power

- Power regulator chip in charge of taking the power from the solar panel and charging a small battery with it

- Small Li-Ion battery to act as a buffer for shady moments and rainy days

## Software and Server

- Backend api to receive and store data in mongodb or mysql database

- Data visualization frontend

- Machine learning predictions (using LSTM model)

# Criteria for Success

- Successfully collect an accurate measurement of number of people at bus stops

- Use data to determine optimized bus deployment schedules.

- Use data to provide useful visualizations.

# Ethics and Safety

It is important to take into consideration the privacy aspect of users when collecting unique device tokens. We will make sure to follow the existing ethics guidelines established by IEEE and ACM.

There are several potential issues that might arise under very specific conditions: High temperature and harsh environment factors may make the Li-Ion batteries explode. Rainy or moist environments may lead to short-circuiting of the device.

We plan to address all these issues upon our project proposal.

# Competitors

https://www.accuware.com/products/locate-wifi-devices/

Accuware currently has a device that helps locate wifi devices. However our devices will be tailored for bus stops and the data will be formatted in a the most productive ways from the perspective of bus companies.