Abstract
The connection of renewable energy sources such as wind and solar power into the power grid can significantly reduce both costs and pollution emissions. However, the variability, volatility, and anti-peak regulation characteristics of renewable energy pose significant challenges for power system dispatch. This paper proposes a hybrid economic emission dispatch model (HDEED) for wind–solar–thermal-storage systems, with operational cost and pollution emission as objective functions. The study aims to develop optimal grid-connection strategies for clean energy by utilizing the energy-shifting capability of energy storage systems. This includes strategies based on optimal load fluctuation and optimal operation income for new energy stations. A generalized load fluctuation coefficient is proposed to assess load fluctuations after wind and solar energy integration, comparing and analyzing the performance of energy storage power stations with varying capacities. In terms of algorithm development, the paper proposes the Pelican optimization algorithm with a clustering strategy (POA-CS), specifically tailored to address the complexities of economic emission scheduling. The effectiveness of the proposed strategy and algorithm is validated using an enhanced IEEE-39 bus test system. Results indicate that the generalized load fluctuation coefficient under the optimal grid-connected strategy based on load fluctuation is 21% lower than that of direct grid connection of wind power and photovoltaic, leading to a significant reduction in net load fluctuation. Furthermore, under the optimal grid-connected strategy based on the operation income of new energy stations, the revenue of these plants increased by 22.40% compared to direct grid connections of wind power and photovoltaic systems. The POA-CS algorithm demonstrates superior performance, continuity, and smoothness in obtaining the Pareto optimal boundary under consistent testing conditions.
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