132482Responsive Algorithmic Enterprise (RAE)ClosedFeasibility StudiesInnovate UKThis project aims to develop new algorithms for energy control utilising appliance signature data from three case-studies (a car-park, a plastic factory and a village community). The algorithms will be used for peak load management and load balancing and will be designed to rectify previously identified issues in monitored data due when simple demand response is applied. In addition the algorithms will be able to take advantage of secondary power sources such as PV, wind and battery storage. This is a collaboration between the University of Reading using their expertise in energy data analytics and optimisation and AND Technology Research with the expertise in energy monitoring and control. Trials will then be undertaken through simulation and tested using energy monitoring equipment that has been pioneered by AND Technology Research. This equipment is designed for cost effectiveness and is targeted at the organisations operating at a meso level. In summary, the University of Reading and AND Technology Research will develop predictive control algorithms for meso-level energy management based on the energy data available from monitoring.