计及气象可达性的海上风电运维效益仿真方法

为改善海上风电传统经济评价方法的局限性，根据气象条件等因素对海上风电运维的影响，分析计及气象可达性的海上风电运维流程，提出涵盖停机时间、损失电量、风电场可利用率和运维成本等经济评价指标计算方法，建立基于Anylogic平台的海上风电运维效益仿真模型，模拟风电机组、船舶、人员实时状态，统计各项经济评价指标，评估海上风电场运维经济效益。案例结果表明：所建立的效益仿真模型可模拟风电场的运维流程，并较为准确地推算出停机时间、损失电量、风电场可利用率及运维成本等关键指标，反映海上气象条件对风电场经济效应的影响，可为海上风电场的运行维护提供技术参考。     

风电场的组合维修策略研究

为降低风电场维修成本,提出针对风电场的风电机组部件组合维修策略。在各部件故障率服从威布尔分布的基础上,确定各部件的最优预防性维修周期,进而确定各部件后续预防性维修的实施时刻。将未来一段时间内的全部维修任务按分组方案组合为多个维修组,单一维修组内包含的全部维修任务采用分层优化方法安排给多支维修队一起执行,以使在风电机组停机时间最短情况下维修队工作时间最短。对比组合维修策略与预防性维修策略的维系成本,以分组方案节约维修成本为适应度,使用遗传算法求解最优分组方案。仿真结果验证了该策略可有效减少风电机组的停机时间,降低风电场维修成本。     

考虑混搭风电机组的海上风电场集电线路拓扑动态优化方法

随着海上风电朝着深远海、大型化的方向发展,市场上风电机组的迭代速度加快,而海上风电场整体开发周期长,与风电机组的机型研发速度不相匹配,故在海上风电场的开发过程中可能会将不同型号的风电机组进行组合布机;但要如何在不同机型的搭配方式中,从经济性与可靠性的角度选择出最佳的拓扑结构进行连接,是混搭风电机组拓扑结构优化的主要难点之一。因此,构建考虑混搭风电机组的海上风电场集电线路拓扑结构动态优化方法,以改进K-means算法和改进Prim算法完成海上风电场的回路划分、路径设计;采用动态交叉优化策略完成拓扑中海缆交叉的处理,权衡每个拓扑方案的经济性与可靠性成本,进行最佳拓扑结构输出;最后通过不同混搭风电机组场景下的拓扑优化结果,验证该方法的有效性。     

基于发电成本和疲劳均匀性的风电场有功功率控制策略研究

针对限功率工况下风电场机组有功分配问题,文章建立了机组发电成本模型和综合疲劳模型。采用改进的粒子群优化算法,在风电场各机组风功率预测信息的基础上,以风电机组疲劳均衡、单位发电成本最低为目标,以功率平衡、出力限制、开停机时间限制等为约束条件,研究限电情况下风电场内有功控制优化策略。最后,对比3种分配方案下风电场的有功总出力、发电成本和疲劳均匀性,分析限功率控制下风电场典型机组的有功出力特征,结果表明,同时考虑发电成本和疲劳均衡条件的优化策略在有效降低成本的基础上能够保证机组间的疲劳均衡,从而降低机组维修频率。     

风电机组维修方式的多目标决策研究

维修费用占风电场运行成本的较大比重,维修方式的选择直接影响着维修费用,科学地选择维修方式有助于降低运维成本,提高风电场的效益。文章分析了风电场风电机组结构特性及其运行、维修的特点;采用模糊层次分析法建立了风电机组维修方式的决策模型;根据比较准则,构建了三角模糊数判断矩阵;通过逐层计算权重得到备选维修方式的选择概率,并以最大概率为准则制定了维修方案。文章还以风电机组发电机维修方式的选择为例,验证了该模型的合理性和正确性。     

基于主动尾流控制的风电机群协同优化调度

针对机组间尾流效应严重影响风电机组发电效率的问题,提出了风电机组安全偏航约束计算方法、尾流特性混合半机理建模方法以及风电机群多目标协同优化调度方法。基于FAST. FARM平台完善了多自由度可控机组与尾流的动态交互集成仿真环境,对比分析了2台机组串列式排布以及华东地区某海上风电场7台机组实际排布下的协同运行优化性能。结果表明：所建立的集成仿真模型能够合理表征风电机群与空气流场的多领域动态交互特性,所提方法能够有效提升风电机群发电效能,促进经济效益、资源利用和成本控制的均衡优化。     

基于深度强化学习的海上风电机组状态维护与备件库存联合优化

维护与备件库存管理是海上风电运维的两个密不可分的关键环节。为提高海上风电机组设计寿命周期内的运维经济性，构建状态维护与备件库存联合优化策略。首先，将海上风电机组构建为由叶片、齿轮箱、电气、偏航、轮毂、制动、传动链、发电机8个子系统组成的系统，然后将各子系统的劣化过程构建为多状态马尔可夫随机过程，建立维护与备件库存的交互模型，其中包括被动维护时间与随机故障以及备件库存的关系、备件库存对维护活动的影响等。随后，设计子系统的劣化状态与备件库存状态、状态检修动作与备件订购的表征方法，并以此形成深度强化学习Dueling DQN的框架，通过对深度网络的迭代训练，求解海上风电机组的最优维护与备件订购决策序列。最后，以某海上风电场内的风电机组为例，验证所提联合优化方法的优越性，并讨论强化学习的探索率、风电场的可达率对运维成本的影响。     

基于布谷鸟算法的风电机组装配序列优化

装配序列规划（ASP）是风电机组制造的重要技术。ASP是一个组合优化问题,风电机组最优装配序列的搜索空间和计算量均很大。提出基于布谷鸟算法的风电机组装配序列优化方法。首先,从三维装配体模型中提取多种装配约束信息并表示成装配约束矩阵,以降低最优装配序列的搜索空间;继而构造装配序列目标函数,建立装配序列规划模型,方便算法计算出最优装配序列;对离散布谷鸟算法（DCA）改进,求解ASP模型,获得风电机组产品的最优装配序列。最后通过实验验证了ASP模型的有效性和DCA的优良性能。     

考虑疲劳均衡的海上风电场主动尾流控制研究

海上风电场运行维护成本高,而其尾流效应影响更加突出,不但会影响风电场的发电效率,还会增大风电场内机组的疲劳载荷,增加运维成本。文章针对基于疲劳均匀的海上风电场主动尾流控制展开研究,通过GH-Bladed软件计算建立了风电机组在典型控制工况下关键零部件的疲劳损伤量数据库。其中的工况包括最大功率追踪、桨距角控制和偏航控制3种,并引用了量子粒子群算法,通过变桨和偏航两种方法进行优化控制,以实现海上风电场发电量提升和风电机组疲劳均匀的多目标主动尾流优化控制策略,降低海上风电场运维成本。仿真结果表明了所提出控制方法的可行性。     

基于风电场机组大部件运行状态的年度检修策略

风电场机组年度检修是保证所有风电机组正常运行的重要手段,合理的检修方案可以降低风电场运行维护成本。为确定风电场的最优年度检修方案,文章提出了一种基于大部件运行状态的风电场年度检修策略。首先,综合考虑大部件的工作役龄、维修历史及当前运行状态,以威布尔比例强度模型计算部件的故障概率;然后,定义检修改善因子,描述年度检修对部件故障概率的降低程度,建立考虑故障停机时间、故障维修费用及检修成本的年度检修策略优化模型;最后,通过算例分析验证该策略的正确性及有效性。     

Optimal selection of time windows for preventive maintenance of offshore wind farms subject to wake losses

The maintenance of wind farms is one of the major factors affecting their profitability. During preventive maintenance, the shutdown of wind turbines causes downtime energy losses. The selection of when and which turbines to maintain can significantly impact the overall downtime energy loss. This paper leverages a wind farm power generation model to calculate downtime energy losses during preventive maintenance for an offshore wind farm. Wake effects are considered to accurately evaluate power output under specific wind conditions. In addition to wind speed and direction, the influence of wake effects is an important factor in selecting time windows for maintenance. To minimize the overall downtime energy loss of an offshore wind farm caused by preventive maintenance, a mixed-integer nonlinear optimization problem is formulated and solved by the genetic algorithm, which can select the optimal maintenance time windows of each turbine. Weather conditions are imposed as constraints to ensure the safety of maintenance personnel and transportation. Using the climatic data of Cape Cod, Massachusetts, the schedule of preventive maintenance is optimized for a simulated utility-scale offshore wind farm. The optimized schedule not only reduces the annual downtime energy loss by selecting the maintenance dates when wind speed is low but also decreases the overall influence of wake effects within the farm. The portion of downtime energy loss reduced due to consideration of wake effects each year is up to approximately 0.2% of the annual wind farm energy generation across the case studies—with other stated opportunities for further profitability improvements.     

Multi-objective optimized operation of integrated energy system with hydrogen storage

In this paper, an integrated energy system (IES) consisting of wind turbine unit, photovoltaic cell unit, electrolytic hydrogen unit, fuel cell unit, and hydrogen storage unit is proposed, and the construction of multi objectives for day-ahead power dispatching of the IES considering both operation and environment cost is discussed. By adopting piecewise linearization method, the optimization variables are divided into 24 periods, and the day-ahead power dispatching optimization problem is transformed into a 24-h piecewise optimization problem. On the basis, a complete non-linear mixed integer dynamic scheduling optimization model is established. An improved non-dominated sorting genetic algorithm (NSGA-II) is applied to solving the model. In optimization process, an interactive strategy is adopted to solve the coordination between discretization of variables and restriction of switching times of electrolyzer. Optimization results show that, compared with the single objective of minimizing operating costs, the multi-objective optimization scheme can reduce carbon emissions by 3.5% with 2.8% increase of operating cost. Compared with the single objective of minimizing environmental, the multi-objective optimization scheme can reduce operating cost carbon by 5.12% with 2.6% increase of environmental cost.     

Power generation efficiency analysis of offshore wind farms connected to a SLPC (single large power converter) operated with variable frequencies considering wake effects

This paper deals with the power generation efficiency analysis of a proposed offshore wind farm topology, consisting of a SLPC (single large power converter) that simultaneously controls a group of generators. This common converter can operate at a VF (variable frequency) or at a CF (constant frequency). The results are compared with the conventional onshore wind farm scheme, where individual power converters are connected to each turbine, guaranteeing maximum power generation for the entire wind farm. A methodology to analyze different wind speed and direction scenarios, and to compute the optimal electrical frequency for each one, is presented and applied to different case studies depending on the wind farm size. In order to obtain more realistic values of wind speeds, the wake effect amongst wind turbines is considered. A wake model considering single, partial and multiple wakes inside a wind farm and taking into account different wind directions, is presented. Both wind farm topologies are analyzed by means of simulations, taking into account both wind speed variability in wind farms and the number of wind turbines. The possible resulting benefits of simplifying the MPCs (multiple power converters) of each turbine, namely saving costs, reducing losses and maintenance and increasing the reliability of the system, are analyzed, focusing on the total power extraction. The SLPC-VF scheme is also compared with a CF scheme SLPC-CF, and it is shown that a significant power increase of more than 33% can be obtained with SLPC-VF.     

基于连续隐马尔可夫模型的风水火联合低碳检修优化

目的  新型电力系统背景下,风机的低碳检修与常规机组的协同检修等问题亟待解决。文章兼顾多属性气象因子影响和低碳性、经济性需求,建立基于连续隐马尔可夫的风水火联合低碳检修优化模型。 方法  首先,以降雨量、风速、雷电危险度为观测序列,以检修容量为隐状态序列,利用连续隐马尔可夫（Continuous Hidden Markov Model, CHMM）过程实现对风电场检修容量的动态跟踪。然后,以最优检修容量为决策依据、以总成本最小为优化目标,统筹考虑检修约束、系统控制约束等,构建风水火联合低碳检修优化模型。最后,以IEEE30节点系统进行算例展开研究。 结果  结果表明,所提模型具有更显著的经济效益和低碳特性。 结论  文章所做研究对风机的运行维护具有较高的理论价值,工程适用性较强。     

考虑海缆影响的风电集群无功优化配置方法

针对海上风电集群的无功补偿配置问题,在充分考虑双馈式发电机(DFIG)的无功调节能力及机群拓扑结构对海上风电无功优化影响的基础上,计及高压海缆对地电容与匝间电容的影响,以降低海上风电集群有功功率损耗和使离散设备调节的成本支出最小为目标函数,将海上风电集群内各节点电压偏差作为罚函数,建立了适用于海上风电集群和高压海缆一体的无功优化模型,采用细胞膜优化算法分别计算DFIG额定功率和空载两种运行方式,得到无功补偿配置最优方案。算例分析表明,该算法有效可行。     

几何约束条件下海上风电场布局优化方法研究

考虑实际工程需求,开发一种几何约束条件下海上风电场智能布局优化方法。该方法使用Gaussian模型计算风力机尾流区的速度亏损,并以最大化风电场年发电量为目标采用差分进化算法进行优化,可满足海上风电场布局时的各类几何约束。利用该方法分别在3行、4行、7行几何约束下对中国某海上风电场的风力机排布方式进行优化。结果显示,相比于原始布局方案,在考虑海缆铺设成本增加的情况下布局优化方案可提升风电场年发电量2.13%～2.64%。进一步分析表明,布局优化过程中可行解数量的设置需综合考虑智能算法寻优难度的影响。     

海上风电场功率提升和疲劳平衡综合优化控制

针对海上风电场,综合功率提升和疲劳平衡分配的优化目标,提出一种以天为优化周期的优化策略.在电网高负荷时段,基于Jensen尾流模型,以轴向诱导因子为优化变量,风电场整场功率最大为目标,运用随机粒子群算法进行风功率利用提升优化控制;在电网低负荷时段,基于风电机组综合疲劳系数计算方法,以机组轴向诱导因子为优化变量,应用尾流...     

Variable geometry wind turbine for performance enhancement,improved survivability and reduced cost of energy

The conceptual design and proof‐of‐concept testing of a furling vertical axis wind turbine, suited to large‐scale offshore deployment, is described. Through the implementation of variable geometry capabilities, extreme storm loads can be reduced, and unsteady flow‐related fatigue loads can be minimized thereby reducing capital (structural) and maintenance costs. Moreover, annual power generation can be optimized in real‐time to account for unsteady wind effects related to weather and siting thus improving efficiency and annual power generation. Copyright © 2014 John Wiley & Sons, Ltd.     

Multidisciplinary design optimization of offshore wind turbines for minimum levelized cost of energy

This paper presents a method for multidisciplinary design optimization of offshore wind turbines at system level. The formulation and implementation that enable the integrated aerodynamic and structural design of the rotor and tower simultaneously are detailed. The objective function to be minimized is the levelized cost of energy. The model includes various design constraints: stresses, deflections, modal frequencies and fatigue limits along different stations of the blade and tower. The rotor design variables are: chord and twist distribution, blade length, rated rotational speed and structural thicknesses along the span. The tower design variables are: tower thickness and diameter distribution, as well as the tower height. For the other wind turbine components, a representative mass model is used to include their dynamic interactions in the system. To calculate the system costs, representative cost models of a wind turbine located in an offshore wind farm are used. To show the potential of the method and to verify its usefulness, the 5 MW NREL wind turbine is used as a case study. The result of the design optimization process shows 2.3% decrease in the levelized cost of energy for a representative Dutch site, while satisfying all the design constraints.