| Popis: |
Acute impacts of past extreme climatic events on power distribution networks (PDNs) have highlighted the significance of resilience in PDNs. However, maintaining and enhancing the resilience of PDNs over an extended horizon is challenging and requires long-term planning. This chapter presents a decision-making framework for resilience enhancement of PDNs that undergo gradual deterioration and face the risk of exposure to multiple stochastic hurricane events over a decision horizon. The proposed framework integrates modeling of climatic stressors, performance of physical components of PDNs, and probabilistic resilience quantification to form a nonlinear constrained optimization problem with binary decision variables for replacement of deteriorating assets. The objective of the optimization problem is to maximize life-cycle resilience by determining the optimal sequence of preventive maintenance actions. The major complexity of this optimization problem arises from the large number of combinations of possible maintenance actions over an extended decision horizon as well as the existing constraints. To overcome these challenges, this study introduces the BICDE algorithm, which is developed via the integration of a binary differential evolutionary (BDE) algorithm with the improved (μ+λ)-constrained differential evolution (ICDE). The BICDE has the capability of the ICDE to solve constrained optimization problems and features of the BDE algorithm to handle nonlinear, nondifferentiable, and multimodal objective functions with binary decision variables. The presented framework is applied to a large-scale aging PDN. The BICDE-based strategy is compared to the strength-based strategy set by National Electric Safety Code (NESC) that is commonly used in practice. The results indicate that the optimal strategy based on the proposed framework leads to a significant cumulative improvement of 23.1% in the expected resilience of the PDN over a planning horizon of 100 years. |
