Abstract

In response to the escalating demand for sustainable energy solutions, the integration of diverse energy sources has gained prominence. Energy hubs, facilitating the amalgamation of multiple sources, enhance system efficiency and flexibility. Yet, coordinating the operation of such multi-energy systems remains challenging due to complexity and uncertainties, especially with renewable sources. This paper introduces a Cournot model-based approach for optimizing three interconnected energy hubs. The objective is to minimize total operating costs while ensuring reliability and efficiency. Leveraging the Cournot model, commonly employed in energy studies for competition and pricing, we capture the strategic behavior of energy hubs. The proposed solution employs a modified butterfly flame heuristic algorithm to navigate the non-linear and non-convex optimization problem, efficiently seeking global optimal solutions. Numerical experiments on a three-hub test case validate the method, demonstrating a 3.5 % reduction in total operation costs compared to the base case and over 2.5 % cost reduction for each hub. The proposed algorithm outperforms traditional methods in terms of convergence speed and solution quality, offering a promising avenue for optimizing the operation and management of multi-energy systems. In summary, this paper introduces a novel approach grounded in the Cournot model and a hybrid heuristic algorithm for optimizing three interconnected energy hubs, effectively addressing uncertainties associated with renewable sources and ensuring reliable and efficient system operation.

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