Layering residential peer networks and geospatial building networks to model change in energy saving behaviors

Complex human or engineered network systems can be examined as a series of coexisting layers. A variety of dynamic perturbations, such as information flows across computer networks, traffic flows across transportation networks and the spread of energy saving practices across human networks, have been treated separately as single networks in previous research. However, because these phenomena often consist of human networks interacting with engineered networks, analyzing the properties of the multi-layer network systems may provide more accurate insights. In this paper, we examine a multi-layer network system to provide insight into the diffusion of energy consumption practices through peer networks within and across residential buildings. We introduce a new model-the Layered Network Model-that treats that treats a residential peer network and a geospatial building network as a single, layered network. We compare this model to a previously published Multi-Layer Interactive Network Model by simulating diffusion through a real multi-layer network system consisting of a residential peer network and a geospatial building network from three experimental data-sets. We found our model to be more accurate and efficient, hence contributing an efficient mathematical model and set of simulation algorithms that accurately capture the post-perturbation response of a layered, residential peer network and a geospatial building network.

► Peer networks have been shown to impact energy conservation behavior.
► However, geospatial properties of networks may also impact conservation behavior.
► We develop an analytical model to layer peer and geospatial networks in buildings.
► We compare our Layered Network Model to an existing conventional interacting model.
► We found our model to be more efficient and accurate at predicting energy savings.