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
To enhance the resilience of power systems with offshore wind farms(OWFs),a proactive scheduling scheme is proposed to unlock the flexibility of cloud data centers(CDCs)responding to uncertain spatial and temporal imp...To enhance the resilience of power systems with offshore wind farms(OWFs),a proactive scheduling scheme is proposed to unlock the flexibility of cloud data centers(CDCs)responding to uncertain spatial and temporal impacts induced by hurricanes.The total life simulation(TLS)is adopted to project the local weather conditions at transmission lines and OWFs,before,during,and after the hurricane.The static power curve of wind turbines(WTs)is used to capture the output of OWFs,and the fragility analysis of transmission-line components is used to formulate the time-varying failure rates of transmission lines.A novel distributionally robust ambiguity set is constructed with a discrete support set,where the impacts of hurricanes are depicted by these supports.To minimize load sheddings and dropping workloads,the spatial and temporal demand response capabilities of CDCs according to task migration and delay tolerance are incorporated into resilient management.The flexibilities of CDC’s power consumption are integrated into a two-stage distributionally robust optimization problem with conditional value at risk(CVaR).Based on Lagrange duality,this problem is reformulated into its deterministic counterpart and solved by a novel decomposition method with hybrid cuts,admitting fewer iterations and a faster convergence rate.The effectiveness of the proposed resilient management strategy is verified through case studies conducted on the modified IEEERTS 24 system,which includes 4 data centers and 5 offshore wind farms.展开更多
为了结合海底电缆寿命周期特点、制定适用于近海风电场高压海底电缆的选型标准,以海缆传输容量大于风电场设计向外传输容量为约束条件,构建了包括购置、敷设、损耗、故障损失、运行维护以及回收净投资成本的海缆全寿命周期成本(LCC)模型...为了结合海底电缆寿命周期特点、制定适用于近海风电场高压海底电缆的选型标准,以海缆传输容量大于风电场设计向外传输容量为约束条件,构建了包括购置、敷设、损耗、故障损失、运行维护以及回收净投资成本的海缆全寿命周期成本(LCC)模型,并以LCC等额年值最小作为选型标准。以国内某海上风电场海底电缆选型为案例进行计算分析。结果表明,购置、损耗、故障损失成本与自身LCC占比较重,最高分别达到26.4%、30.8%、62.0%;所有方案前期投资与自身LCC占比≤40%。当电压等级相同时,单芯海缆方案损耗成本至少比三芯海缆方案高出4.68×103万元;而当线芯数相同时,高电压等级故障损失成本至少比低电压等级海缆方案高出8.8×103万元;2回110 k V 3×500 mm2高压XLPE绝缘钢丝铠装海缆方案LCC等额年值(3.08×103万元/a)最小,该方案最优。展开更多
针对海上风电机组出现故障时,传统蚁群算法在模型初期效率较低、易陷入局部最优且收敛速度差的问题,提出了一种基于GA-PACO的海上风电场运维策略仿真模型。使用遗传算法进行全局搜索和函数优化,将其作为蚁群算法的初始信息素;改进启发...针对海上风电机组出现故障时,传统蚁群算法在模型初期效率较低、易陷入局部最优且收敛速度差的问题,提出了一种基于GA-PACO的海上风电场运维策略仿真模型。使用遗传算法进行全局搜索和函数优化,将其作为蚁群算法的初始信息素;改进启发信息函数,优化局部最优解,使蚁群算法在搜索目标时更明确,并提升收敛速度;引入信息素调节因子,改进信息素算法性能,使蚁群能够选取高质量的路径,降低稳定的迭代次数。实验结果表明,GA-PACO算法在仿真80台风机时,技术发电量可利用率(Technical Energy Availability,TEA)达98.97%,发电量提升1821万kW·h;仿真160台风机时,TEA达98.06%,发电量提升2386万kW·h。通过仿真为风电场精准找到最优维护路径,提供有效的运维策略,增加风电机组的实际发电量。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.
基金the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources under Grant LAPS21002the State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment under Grant SGHNFZ00FBYJJS2100047.
文摘To enhance the resilience of power systems with offshore wind farms(OWFs),a proactive scheduling scheme is proposed to unlock the flexibility of cloud data centers(CDCs)responding to uncertain spatial and temporal impacts induced by hurricanes.The total life simulation(TLS)is adopted to project the local weather conditions at transmission lines and OWFs,before,during,and after the hurricane.The static power curve of wind turbines(WTs)is used to capture the output of OWFs,and the fragility analysis of transmission-line components is used to formulate the time-varying failure rates of transmission lines.A novel distributionally robust ambiguity set is constructed with a discrete support set,where the impacts of hurricanes are depicted by these supports.To minimize load sheddings and dropping workloads,the spatial and temporal demand response capabilities of CDCs according to task migration and delay tolerance are incorporated into resilient management.The flexibilities of CDC’s power consumption are integrated into a two-stage distributionally robust optimization problem with conditional value at risk(CVaR).Based on Lagrange duality,this problem is reformulated into its deterministic counterpart and solved by a novel decomposition method with hybrid cuts,admitting fewer iterations and a faster convergence rate.The effectiveness of the proposed resilient management strategy is verified through case studies conducted on the modified IEEERTS 24 system,which includes 4 data centers and 5 offshore wind farms.
文摘为了结合海底电缆寿命周期特点、制定适用于近海风电场高压海底电缆的选型标准,以海缆传输容量大于风电场设计向外传输容量为约束条件,构建了包括购置、敷设、损耗、故障损失、运行维护以及回收净投资成本的海缆全寿命周期成本(LCC)模型,并以LCC等额年值最小作为选型标准。以国内某海上风电场海底电缆选型为案例进行计算分析。结果表明,购置、损耗、故障损失成本与自身LCC占比较重,最高分别达到26.4%、30.8%、62.0%;所有方案前期投资与自身LCC占比≤40%。当电压等级相同时,单芯海缆方案损耗成本至少比三芯海缆方案高出4.68×103万元;而当线芯数相同时,高电压等级故障损失成本至少比低电压等级海缆方案高出8.8×103万元;2回110 k V 3×500 mm2高压XLPE绝缘钢丝铠装海缆方案LCC等额年值(3.08×103万元/a)最小,该方案最优。
文摘针对海上风电机组出现故障时,传统蚁群算法在模型初期效率较低、易陷入局部最优且收敛速度差的问题,提出了一种基于GA-PACO的海上风电场运维策略仿真模型。使用遗传算法进行全局搜索和函数优化,将其作为蚁群算法的初始信息素;改进启发信息函数,优化局部最优解,使蚁群算法在搜索目标时更明确,并提升收敛速度;引入信息素调节因子,改进信息素算法性能,使蚁群能够选取高质量的路径,降低稳定的迭代次数。实验结果表明,GA-PACO算法在仿真80台风机时,技术发电量可利用率(Technical Energy Availability,TEA)达98.97%,发电量提升1821万kW·h;仿真160台风机时,TEA达98.06%,发电量提升2386万kW·h。通过仿真为风电场精准找到最优维护路径,提供有效的运维策略,增加风电机组的实际发电量。
