Synergistic Integration of Renewable Energy and HVDC Technology for Enhanced Multi-objective Economic Emission Dispatch Using the Salp Swarm Algorithm

This paper proposes a Salp Swarm Algorithm (SSA), a unique optimization technique for the synergistic integration of renewable energy and High Voltage Direct Current (HVDC) technology to enhance the performance of multi-objective economic emission dispatch (MODED). The primary aim is to optimize both the economic and environmental aspects of power systems. A mathematical model for MODED based on Wind-Solar-Thermal integrated energy has been carefully constructed, considering variables like the valve point effect, equality constraints, and inequality constraints. The study determines optimal generation levels and associated costs for six thermal generating units under various power demands, exploring diverse scenarios such as Economic Dispatch for High Voltage Alternating Current (HVAC) with Losses, Economic Dispatch for HVDC with Losses, Economic Dispatch for HVDC addressing challenges related to voltage instability, protection difficulties and losses in DC systems, Economic Dispatch HVAC & HVDC with Losses and Economic Dispatch for HVAC & HVDC with Renewable Energy (RE). To validate the model, tests have been conducted on the IEEE 30 Bus System with a substantial presence of renewable energy.