A novel stochastic home energy management system considering negawatt trading

The decarbonization and sustainability of smart cities is calling for new schemes and businesses capable of increasing the efficiency of energy systems. In this context, energy communities are emerged as a valuable framework to optimally integrate prosumers into electricity networks and take the maximum advantage of do-mestic resources such as controllable appliances or rooftop photovoltaic arrays. Within communities, prosumers can exchange energy through peer-to-peer platforms, but they can also exchange negawatts. This trading mechanism focuses on acquiring or selling consumption rights rather than actual energy, thus further incre-menting the flexibility of the system. In this regard, this paper develops a novel stochastic-based home energy management model considering negawatt trading. An original iterative algorithm is presented by which the developed negawatt-focus problem is converted into a more useful and practical negawatt-aware mechanism, by which the scheduling plan is ready to exploit trading opportunities without notably incrementing the electricity bill, which is considered the primary objective of home energy management applications. Several results are presented to validate the new tool, illustrate the concept of negawatt trading and how it affects to power allo-cation in prosumer installations. Results show that negawatt trading supposes a monetary opportunity for pro-sumers if it is optimally exploited, enabling a reduction of the electricity bill by 45 % compared with the conventional case. Moreover, the role of batteries in negawatt trading is highlighted, providing energy backup when importable power must be reduced. Actually, total negawatts exported increase by 34 % when storage capacity increases from 3 to 5 kWh.