ENGINERIFY was assigned a project for 100 KW load management by harnessing energy from hot water through a heat pump and storing it in a PCM buffer tank. Multiple scenarios, PCM materials, and options were modeled to develop an optimized system that provides 100 KW of uninterrupted 8 hours energy supply when needed, energy storage coupled with water required quantity. It was done in Python for model development and ANN was used for the prediction of PCM efficiency and energy storage. The model was then simulated on Simulink and validated. the final PFD and P&ID were developed. It was done for a Client from the Netherlands. This model is to be used in solar power plants, thermal power plants, and buildings energy storage purposes.
Scope
The main objective of this project was to develop an optimized model for multiple aspects integrated. To perform this project, the following activities were conducted:
Engineering data collection that includes operation data, historical data for water storage, and temperature.
Database, drawings (PFDs and P&IDs), etc.
Research and development for mass and energy balance, rate equations, load calculation, design equations and constants, etc.
Python modeling
Making Simulation on Simulink/Matlab
Performing model validation, Data validation, and evaluation of model performance.
Implemented an Artificial Neural Network to predict water temperature, PCM efficiency and energy production.
Development of an Implementation Plan for the model
Preparation of final Comprehensive Report
Process
A Comprehensive approach is set forth to ensure all essential components integral to the project scope are included. One of the aspects was to optimize enough water storage to provide 100KW energy storage capacity for 8 hours, Second to develop PCM buffer tank system with efficient material that can work for low and medium temperature ranges and is capable of saving enough energy. The Third was to optimize the whole system and use an air heat pump to make up for energy when enough water was not available. Fourth was to integrate all aspects and model a perfect system, Fifth was to do data validation and model prediction through ANN.
Outcome
Optimum and optimized model developed
100 KW uninterrupted energy supply for 8 hours
Data validation was done successfully
Prediction of Energy production, water temperature, and PCM performance
Suggested better options for process control application and operation.
This modeling offered a clear picture of harnessing thermal energy from hot water and storing it in a PCM buffer tank. It also presented a better plan to improve process smoothness, control, energy optimization, and prediction based on the company’s needs
Deliverables:
Enginerify successfully submitted the following deliverables
Python-based model file
MATLAB/Simulink simulation
Datasheets
Artificial neural network code
Implementation guide
Detailed final report
