Abstract
AbstractThe market clearing pricing (MCP) model is used to operate electricity, gas, and heating networks (EGHNs) with flexible energy hubs (EHs) in the day‐ahead energy market. It's two‐level optimization. Its higher level refers to EHs' participation in the market and their profit maximization bound by the operational model of power sources, storage devices, and responsive loads in the form of EHs and their flexibility limit. In the lower‐level problem, the MCP model calculates energy price and evaluates EH performance's effects on the networks' technical and economic indices. It optimizes power flow in the networks to reduce centralized generator operating costs. This approach is linear approximation. Unscented transformation (UT) model load and renewable power uncertainties. This technique contains the fewest situations, reducing issue volume and computing time. Benders decomposition (BD) technique calculates energy prices, EHs, and networks. Finally, the numerical results show that the proposed scheme can extract the optimal economic and flexibility states of EHs. EHs' optimal performance enhanced energy networks' economic and operating status compared to power flow studies and promoted societal welfare by lowering energy prices.
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