Project Team
Students
Nazrin Norazhar
Computer Science
Penn State Harrisburg
Bramantyo Bhaskoro
Computer Science
Penn State Harrisburg
Faculty Mentors
Dariush Khezrimotlagh
Penn State Harrisburg
School of Science, Engineering, and Technology
Project
Project Video
Project Abstract
This research explores the application of optimization algorithms in Transmission Expansion Planning (TEP) to facilitate the integration of renewable energy sources (RES) into the existing electrical grid. As global temperatures rise, the urgency to mitigate climate change by transitioning from nonrenewable to renewable energy sources becomes paramount. A significant challenge lies in incorporating RES into the grid without extensive infrastructure overhauls. TEP addresses this by using optimization algorithms to determine the optimal connection topology between power generation stations, in our case RES, and substations.
Our study examines various optimization methodologies, including mathematical optimization techniques such as Linear Programming (LP) and Mixed-Integer Linear Programming (MILP), as well as metaheuristic and heuristic algorithms. The literature review reveals a predominant focus on optimization algorithms applied to offshore wind farm turbines. Hence, our study aims to encompass all types of RES, including solar and hydro and focuses on evaluating Pennsylvania’s renewable energy integration potential.
We utilized a MILP model to leverage existing substation infrastructure to maximize the integration of RES in Pennsylvania. Our investigation found a lack of data available in Pennsylvania showing renewable energy site potential, with only 111 identified as existing sites and an abundance of 2,199 substations. This suggests that Pennsylvania policymakers should push for a statewide survey of renewable energy potential, given the ample substation infrastructure already in place.
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