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Simultaneous Optimization of Energy Entropy and Structural Resilience in Power Transmission Networks Using a Hierarchical Metaheuristic Algorithm
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Vahid Khademi *   , Farzad Barzgar |
| Department of Electrical Engineering, Technical and Vocational University (TVU), Tehran, Iran |
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Abstract: (115 Views) |
This paper presents a novel multi-objective optimization framework for power transmission networks that simultaneously aims to minimize economic costs and energy losses, maximize structural resilience against disruptions, and enhance the uniformity of power flow distribution based on the energy entropy index. To this end, a new composite objective function is designed, which, for the first time, incorporates energy entropy as a network load balancing criterion alongside a weighted structural resilience index. Additionally, a set of constraints including line capacity limits, power balance, and scenario-based disruption constraints are formulated. To solve this complex and nonlinear problem, a hybrid hierarchical metaheuristic algorithm is developed, employing an entropy-based mutation mechanism and stratified selection to improve solution quality. The effectiveness of the proposed model is evaluated on two standard test systems: a 14-bus network and a 39-bus network, under four different scenarios. Simulation results show that in the 14-bus network, using the proposed algorithm leads to a 14% increase in energy entropy compared to conventional methods, and an 18% improvement in the structural resilience index. Moreover, the total operational cost is reduced from 880 to 850 units. In the 39-bus network, a significant improvement in power flow uniformity and reduction in losses is observed, with losses decreasing from 18.4 to 14 MW and generation cost dropping from 3400 to 3100 units. These results demonstrate the capability of the proposed model and algorithm in simultaneously enhancing transmission network performance indicators and improving operational reliability. |
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| Keywords: Transmission Network Optimization, Energy Entropy, Hierarchical Metaheuristic Algorithm, Energy Losses. |
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Full-Text [PDF 523 kb]
(15 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2025/01/20 | Accepted: 2025/04/21 | Published: 2025/05/31
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