Integrated planning of emission reduction based unit commitment and generation dispatch solution for sustainable power system

The dynamic nature of consumer load demands requires power systems to make complex decisions about the operation of multiple generating units. The Unit Commitment Problem (UCP) optimizes unit scheduling over a 24-48 h horizon while considering operational constraints. Simultaneously, reducing greenhouse gas (GHG) emissions has become critical, making the Combined Economic Emission Dispatch (CEED) problem vital for balancing cost and environmental sustainability. This paper presents the African Vulture Optimization Algorithm (AVOA) for solving UCP and the Multi-Objective African Vulture Optimization Algorithm (MOAVOA) for solving the CEED problem. Using the IEEE 39-bus system with 10 generating units as a test case, AVOA achieves lower operational costs and faster convergence compared to existing UCP methods. MOAVOA balances fuel costs and emissions, reducing daily emissions by 3,882.76 tons and saving $176,119.03 in emission taxes, offsetting the slight fuel cost increase. Comparisons with MOPSO, MOABC, and MOAOA validate MOAVOA's superiority in minimizing costs and emissions. To evaluate the sensitivity of the proposed algorithm, the IEEE 118-bus system with 54 generating units was introduced. Furthermore, the results confirm the robustness and adaptability of AVOA and MOAVOA under varying load demands and conditions, demonstrating their effectiveness.