<p>The integration of renewable energy sources (RESs) and energy storage (ES) systems into power grids has introduced significant challenges, particularly in terms of economic and environmental dispatch. The intermittent nature of RESs and uncertainties related to their output make it difficult for traditional dynamic economic/emission dispatch (DEED) methods to ensure optimal power generation. The primary goal of DEED problems is to efficiently manage the production of electrical energy while satisfying various operational and system constraints, such as ramp rate (RR) limitations and the valve point effect (VPE). This optimization is achieved by minimizing both the overall fuel cost and emissions of power generation units. To address these challenges, this paper proposes a novel hybrid optimization approach that incorporates demand response programs (DRP) alongside ES and RES to enhance system flexibility. By leveraging DRP, consumers' participation in shifting or reducing their demand is considered, leading to a more balanced and cost-effective dispatch strategy. The proposed optimization framework employs a hybrid method that combines particle swarm optimization (PSO) and modified shuffled frog leaping algorithm (MSFLA) to effectively solve the DEED problem. Additionally, a fuzzy-based approach is utilized to achieve a trade-off between economic and environmental objectives, ensuring an optimal balance between fuel cost reduction and emission minimization. The effectiveness of the proposed methodology is validated on a test system with 10 generating units over a 24-h period. The numerical results indicate that, compared to conventional techniques such as grasshopper optimization (GO), PSO, shuffled frog leaping algorithm (SFLA), and other methods reported in the literature, the proposed strategy achieves significantly improved trade-off solutions. The incorporation of DRP further enhances the adaptability of the system by reducing peak demand and improving cost efficiency, making it a practical and effective solution for real-world power system operations. Specifically, the integration of DRP led to a 5% decrease in fuel costs and a 4% decline in emissions compared to cases without DRP, highlighting its role in improving both economic efficiency and environmental sustainability within the DEED framework. The results demonstrate that HPSO-MSFLA is a highly effective optimization technique for the DEED problem in modern power grids with high levels of renewable energy sources and DRP. When compared to traditional methods like PSO and SFLA, HPSO-MSFLA consistently delivers better performance.</p>