Opportunities for
Smart Controls
Previous research has shown that the current West Whins system could greatly benefit from the integration of smart controls (Flett, et al., 2020). Currently, there are no installed smart controls, the heat pump is simply observed to turn on following demand from a dwelling. Specifically, there is no consideration given to local renewable generation or tariff prices at time of import. One of the recommendations report is to charge the thermal store on an opportunistic basis, i.e. when there is surplus generation (Flett, et al., 2020). By implementing controls to the system, an efficient use of local generation and optimised economic performance is expected. The simple action of implementing controls could significantly increase the performance of the entire system.
Machine Learning
An emerging technology being utilised in smart control design is machine learning. (Antonopoulos, et al., 2020) In combination with the available monitoring feeds within West Whins, this is a particularly important area of exploration. By implementing machine learning in combination with a user input, a demand prediction infrastructure can be created where the system can enhance itself with the passing of time. This means the longer it is functioning, the better prediction it will perform.
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This demand prediction system can receive live feeds of domestic hot water and space heating demand from the Emoncms monitoring feeds. The system can then learn via algorithms (which would be a function of the time of day, week and year) and the user-input, such that a forecasted demand profile can be factored into the system’s decision making. This is a necessary component of predictive controls which has been suggested in the project’s proposed smart control.
Demand Shaper
Even though this module is still in development for heat pumps, this module could be used elsewhere in Findhorn. Seeing as electric vehicle charging infrastructure is already present within Findhorn, optimising the charging period via demand shaper poses a promising avenue for exploration. For more information on demand shaper, follow this link.
Octopus Agile
Octopus Agile Tariff is the first smart time of use tariff of its kind in the UK. It is ideal to inform the consumer about the different tariffs there will be throughout the day, giving a change for users to move the shiftable loads such as using the dish washer or washing machine. Findhorn’s current tariff is outdated and becoming much less common in recent years. By using the cost comparison apps on Emoncms the effects of upgrading to the agile tariff have been investigated.
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Following the analysis over a 1-week period comparing the price for the heat pump’s energy consumption, the Economy 7 tariff (Figure 1) cost was found to be £47.17 compared to £42.14 for the agile tariff (Figure 2). A number of days were tested throughout the year showing the agile tariff to save between 10p and £3 in a single day. Assuming that in a week savings could be anywhere between £4 and £5, the comparison has proven that by simply changing energy provider (before implementing any controls) over £200 could be saved in a year.
Figure 1 : Cost for heat pump consumption using the Economy 7 Tariff
Figure 2: Cost for heat pump consumption using the Agile Octopus Tariff