Communities are witnessing an increasing number of power outages due to the growing number of extreme weather events that adversely impact our power grid. It is imperative that critical infrastructure assets such as universities and hospital campuses have the tools available to identify options to improve power resilience. District Energy Systems (DES) with Combined Heat and Power (CHP) and CHP-based microgrids are found to be highly resilient to a variety of extreme weather events. At present, DES and multi-building microgrid planning processes are complex, time-consuming, and subjective. This project develops an innovative, simple-to-use geographical information system (GIS)-based scenario tool for a layperson to develop a quick feasibility analysis of a CHP-based DES or microgrid. GIS-integrated models/tools have great potential to better inform urban energy planning and policy-making teams. The information in a GIS tool has been used to illustrate, analyze and draw conclusions about important features such as energy usage, capacity, and potential. The GIS tool communicates with a back-end computational engine and calculates the optimum options available to users and possible return on investments. The computations complexity represents an NP-Hard type of problem and involve optimizing heuristic algorithms such as Genetics Algorithms, Integer Linear Programming, and Particle Swarm Optimizations. The back end is implemented in a cluster-based High Performance Computing Center (HPC) at the University of Houston.