Learnings

Outcomes

This project has successfully demonstrated the ability and willingness of a residential community to proactively shift their electricity usage away from the traditional peak times of 4pm – 8pm. It has generated useful learnings for networks to understand how this can benefit, both in terms of connecting additional network load without the need for reinforcement, and the potential for community Sustain flexibility contracts. 
 
The overall behaviour of the Energy Local community has demonstrated that people are willing to change their electricity usage habits and this change in habits can be maintained. However, it should be noted that the “stayability” in this case is positively influenced by the ongoing nature of the Energy Local Club and may not be fully representative of other community groups. It does however demonstrate the positive impact such clubs can have on network flexibility needs by supporting long-term behavioural change. It may  
indicate that some kind of local organisation is needed such as Energy Local or other engagement to maintain behavioural change. 
 
It has shown the need for better control of heat pumps to match local generation and the need for thermal stores to help reduce the additional peak loading that they may create. The project has also demonstrated the potential for LoraWAN to be used for low cost data communications in areas of poor mobile phone reception. 

Lessons Learnt

The following lessons were learnt from the project: 
 

• There is the potential for communities to be involved in flexibility service provision. The project sought to determine the viability and benefits for communities in addition to usual practices. 
• Initial data from Bethesda was used to set up a model using De Montford University’s powerful Cascade System that could model from appliance to system level. Interestingly, the data showed the impact of lockdown, during the global pandemic, with less seasonal shift in usage noted in comparison to pre-lockdown levels. 
• Different scenarios were modelled to evaluate the impact of EV charger and heat pump penetration, and potential for LV shifting. An interesting impact on peak loading was noted when heat pump penetration reached 60% due to sudden changes in weather. This is likely to become more common and controls need to take this into account.