Performance Evaluation of District Energy Microgrids Planning Tool for Non-Technical Users

Community Microgrids are increasingly gaining popularity worldwide for their efficiency, cost-effectiveness, and local resilience improvement. Microgrid planning tools play a crucial role in their deployment. In the process, tentative designs of the microgrid are simulated, analyzed, and optimized. Due to the complexity of the problem, planning tools must carefully balance computational efficiency while seeking the most optimal solutions. This paper investigates the impact of algorithm selection on CPU and memory utilization of a Community Microgrid planning tool that is specifically designed for non-technical users. We compare two version of the code with two alternatives for Community Microgrid planning tools: a Greedy Algorithm, and a Linear Programming Approach. This comparison examines scenarios spanning from 2 to 50 buildings. Our findings revealed a significant difference in performance between the two algorithms, underscoring the critical role of algorithm selection in optimizing the efficiency of Community Microgrid Planning Tools.