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
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.

Electronic Automatic Transmission for Bicycle

Featured Project

Tianqi Liu(tliu51)

Ruijie Qi(rqi2)

Xingkai Zhou(xzhou40)

Sometimes bikers might not which gear is the optimal one to select. Bicycle changes gears by pulling or releasing a steel cable mechanically. We could potentially automate gear changing by hooking up a servo motor to the gear cable. We could calculate the optimal gear under current condition by using several sensors: two hall effect sensors, one sensing cadence from the paddle and the other one sensing the overall speed from the wheel, we could also use pressure sensors on the paddle to determine how hard the biker is paddling. With these sensors, it would be sufficient enough for use detect different terrains since the biker tend to go slower and pedal slower for uphill or go faster and pedal faster for downhill. With all these information from the sensors, we could definitely find out the optimal gear electronically. We plan to take care of the shifting of rear derailleur, if we have more time we may consider modifying the front as well.

Besides shifting automatically, we plan to add a manual mode to our project as well. With manual mode activated, the rider could override the automatic system and select the gear on its own.

We found out another group did electronic bicycle shifting in Spring 2016, but they didn't have a automatic function and didn't have the sensor set-up like ours. Commercially, both SRAM and SHIMANO have electronic shifting products, but these products integrate the servo motor inside the derailleurs, and they have a price tag over $1000. Only professionals or rich enthusiasts can have a hand on them. As our system could potentially serve as an add-on device to all bicycles with gears, it would be much cheaper.