Promoting Social Behaviour in Reducing Peak Electricity Consumption Using Multi-Agent Systems

In response to anthropogenic climate change, many countries and international organisations have committed to legally binding greenhouse gas emissions targets. The UK and the EU have both recently updated their legislation to include net zero emissions targets in place for 2050 (Skidmore, 2019; Sassoli and Matos Fernandes, 2021). This requires moving away from using fossil fuels for energy generation and moving towards renewable sources such as photovoltaic cells and wind turbines. Centralised'national grids' are able to'switch on and off' traditional fossil fuel power plants in order to increase or decrease the energy supply to meet the demand of the users. As the proportion of energy being generated from renewable sources increases this raises a problem - how can load-balancing (the matching of supply and demand) be managed when the output is inherently dependent on weather conditions. This load-balancing problem is easier to address on a small scale, and as such governments and energy providers are supporting the development of'Community energy systems', where local communities such as a small town own and manage their own renewable energy resources (Walker and Devine-Wright, 2008; Gruber et al., 2021). Decentralised community energy systems allow for a higher share of renewable technologies to be integrated into energy generation (Chiradeja and Ramakumar, 2004); minimise transmission losses between the source of energy generation and the end users (Pepermans et al., 2005); and improve energy security as the energy supply is less impacted by geopolitical factors (Alanne and Saari, 2006). As social awareness of environmental issues increases, the willingness of communities to invest in community energy systems is also expected to increase (Pasimeni, 2019). While there are clear benefits to widespread adoption, the shift towards community energy systems means that comarXiv:2211.10198v2