Much of the work done has been on developing the framework for a better functioning micro-grid system. Still, there is much more work to be done to bring these findings to life. 

 

Work has been done to modify the energy local dashboard used to monitor data for the West Whins flats; however, improvements could still be made. A more user-friendly dashboard with less technical acronyms and more straightforward energy consumption plots could benefit the residents of West Whins. This would allow them to easily access and understand their energy consumption. Some very necessary data is missing from this dashboard due to a lack of hardware installations. Information on the electrical demand and the renewable energy supply is vital for analysing an energy system and understanding the electricity usage. 

 

PyLESA has been the fundamental modelling tool used in this project as it was designed to easily study such a micro-grid system, however it is not without its shortcomings. PyLESA currently has no capabilities to study solar thermal interactions within the micro-grid system. This became a major issue with our project as they could not be simulated. PyLESA currently does not allow for separate heating demands to be introduced in to separate storage tanks. This meant we could not separate the hot water storage tank from the space heating. Finally, PyLESA assumes perfect forecasting when using MPC and does account for errors. This is problematic when utilising the MPC for our proposed smart control. PyLESA is an open-source software meaning these modifications could be introduced by anyone with knowledge of Python. 

 

While our proposed smart model predictive control has been demonstrated with real weather data to show cost savings, no modifications have been made to allow for this to work within a real system. Live data feeds running through a machine learning algorithm would allow for accurate prediction of energy demands. Outputs from the model predictive control simulations must be connected to a heat pump relay where a decision can be made to turn the heat pump on or off. 

 

Further studies on the effect that future alterations have on the West Whins model may be conducted. These alterations could include a thermal store for space heating demand, a hydrogen storage tank, ground source and water source heat pumps. 

 

Further smart technologies could be studied such as Node-red, which could be used to wire together hardware devices, API’s and online services as part of the internet of things. This poses as a promising avenue to explore solutions for implementing our proposed model predictive controller.