Transitioning to clean and low-carbon energy is becoming a crucial goal for many entities in the energy systems sector such as governments, power utilities, and policymakers. This shift to clean energy is supported by a diverse portfolio of data products such as satellite data, smart meter data, power networks, green energy datasets (e.g., solar installations & electric vehicles), microgrid networks, and building stock data. Among these, network datasets are becoming increasingly common in addressing a wide array of issues in residential energy, especially in applications that focus on social good. Thus, streamlining the process of generating different types of networks will be helpful. In this work, we propose a versatile network synthesis and analytics pipeline developed using software design principles that make it modular, scalable, and extensible. Three case studies are presented to illustrate the significance of network data in sustainable energy applications.

Motivated by a wide range of applications, research on agent-based models of contagion propagation over networks has attracted a lot of attention in the literature. Many of the available software systems for simulating such agent-based models require users to download software, build the executable, and set up execution environments. Further, running the resulting executable may require access to high performance computing clusters. Our work describes an open access software system (NetSimS) that works under the “Modeling and Simulation as a Service” (MSaaS) paradigm. It enables users to run simulations by selecting models and parameter values, initial conditions, and networks through a web interface. The system supports a variety of models and networks with millions of nodes and edges. In addition to the simulator, the system includes components that enable users to choose initial conditions for simulations in a variety of ways, to analyze the data generated through simulations, and to produce plots from the data. We describe the components of NetSimS and carry out a performance evaluation of the system. We also discuss two case studies carried out on large networks using the system. NetSimS is a major component within net.science, a cyberinfrastructure for network science.