A Solution to the Techno-Economic Generation Expansion Planning Using Modified Remora Optimization Algorithm

Abstract

In the recent decade Generation Expansion Planning (GEP) has received a lot of attention among academics and energy policymakers, especially to reduce the greenhouse gas (GHG) emissions such as CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> , N <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> O and CH <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</inf> . Every country strives to decarbonize its economy by enacting policies that improve the penetration of Renewable Energy Sources (RES) in its power production capacity. GEP is a significant challenge that incorporates technological, economic, financial, geographical, and environmental factors. GEP is most commonly used to tackle large-scale, dynamic, discrete, and non-linear constrained optimization problems. This research provides a multidimensional GEP architecture based on boosting RES integration with the help of Modified Remora Optimization Algorithm. The simulation results are reviewed and compared with the previously reported results in the results section. The proposed technique demonstrates the improved convergence characteristics and resilience when compared to the other compared results.