Ever-increasing consumption of electrical energy has forced extension of power networks to large areas. This would raise reliability and stability problems of power networks. Hence, there is a serious need to work on protection arrangements and relays behavior for solving these problems. By suitable configuration of protection systems and using correct protection functions, negative effects of undesirable faults in power system will be decreased. In this paper, an algorithm is proposed to enhance the performance of differential relays based on the fuzzy logic systems. The algorithm is employed for the protection of short transmission lines against internal faults with/without resistance. By selecting the best stability characteristics based on fuzzy logic systems, the possibility of protection relays' malfunction will be negligible. In this algorithm, sensitivity, reliability and speed of the relay performance are preserved at suitable levels. Considerable external faults which can saturate current transformers (CTs) have been taken to account in this algorithm. This study purpose is to present an algorithm based on the fuzzy logic, which can select the best slopes for stability characteristics of a differential relay during various conditions. The presented algorithm performance has been analyzed by PSCAD/EMTDC software and compared to conventional methods. The results of fuzzy adaptive protection performance testing prove that the proposed algorithm remains fully immune to current transformer saturation during external faults. The other advantage of this algorithm bases on the fact that the scheme does not need to detect CT saturation, it processes the proposed criteria signals independently of the situation.

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The 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.