Reducing the operation and maintenance (O & M) cost is one of the potential actions that could reduce the cost of energy produced by offshore wind farms. This article attempts to reduce O & M cost by improving...Reducing the operation and maintenance (O & M) cost is one of the potential actions that could reduce the cost of energy produced by offshore wind farms. This article attempts to reduce O & M cost by improving the utilization of the maintenance resources, specifically the efficient scheduling and routing of the maintenance fleet. Scheduling and routing of maintenance fleet is a non-linear optimization problem with high complexity and a number of constraints. A heuristic algorithm, Ant Colony Optimization (ACO), was modified as Multi-ACO to be used to find the optimal scheduling and routing of maintenance fleet. The numerical studies showed that the proposed methodology was effective and robust enough to find the optimal solution even if the number of offshore wind turbine increases. The suggested approaches are helpful to avoid a time-consuming process of manually planning the scheduling and routing with a presumably suboptimal outcome.展开更多
风能作为一种清洁的可再生能源,对于实现“双碳”目标以及低碳能源体系转型至关重要。分析和研究了漂浮式海上风电发展面临的挑战和潜在的技术,特别是重点探讨了信息与通信技术(Information and Communication Technology,ICT)和机器人...风能作为一种清洁的可再生能源,对于实现“双碳”目标以及低碳能源体系转型至关重要。分析和研究了漂浮式海上风电发展面临的挑战和潜在的技术,特别是重点探讨了信息与通信技术(Information and Communication Technology,ICT)和机器人技术在漂浮式海上风电运维中的潜在应用,进而设计了漂浮式海上风电运维系统架构,旨在降低运维成本和提高运营安全性。所提出的解决方案涵盖了浮式平台设计、数字孪生形式的远程操作、自主水下机器人等多个方面。展开更多
文摘Reducing the operation and maintenance (O & M) cost is one of the potential actions that could reduce the cost of energy produced by offshore wind farms. This article attempts to reduce O & M cost by improving the utilization of the maintenance resources, specifically the efficient scheduling and routing of the maintenance fleet. Scheduling and routing of maintenance fleet is a non-linear optimization problem with high complexity and a number of constraints. A heuristic algorithm, Ant Colony Optimization (ACO), was modified as Multi-ACO to be used to find the optimal scheduling and routing of maintenance fleet. The numerical studies showed that the proposed methodology was effective and robust enough to find the optimal solution even if the number of offshore wind turbine increases. The suggested approaches are helpful to avoid a time-consuming process of manually planning the scheduling and routing with a presumably suboptimal outcome.
文摘风能作为一种清洁的可再生能源,对于实现“双碳”目标以及低碳能源体系转型至关重要。分析和研究了漂浮式海上风电发展面临的挑战和潜在的技术,特别是重点探讨了信息与通信技术(Information and Communication Technology,ICT)和机器人技术在漂浮式海上风电运维中的潜在应用,进而设计了漂浮式海上风电运维系统架构,旨在降低运维成本和提高运营安全性。所提出的解决方案涵盖了浮式平台设计、数字孪生形式的远程操作、自主水下机器人等多个方面。