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风电场选址时存在对多种备选方案进行选择的问题,文章从多角度出发,选取地理、技术、经济、环境因素,提出了基于模糊层次分析法的解决方案,构建风电场选址的递阶层次结构。以三角模糊数互补判断矩阵为基本的数学模型,构造因素的比较判别矩阵以及方案的优先矩阵;通过将三角模糊数互补判断矩阵转化为精确数矩阵,对其进行一致性的判定和改进,计算出各因素权重,对备选方案进行单因素排序以及综合排序。并通过实例分析,验证了该方法在风电场选址决策中的有效性和正确性。 相似文献
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海上风电场用海面积有限,尾流影响比陆上大,微观选址是其规划设计的关键技术。传统优化算法大多采用离散化变量,使得潜在解空间减少到有限个,难以达到最优化的效果。为了提高海上风电场微观选址优化效率,文章提出了一种基于中心引力优化(CFO)算法的海上风电场微观选址方法。该算法使用实数编码,通过将微观选址优化的变量假设为天体,各个天体之间相互作用,达到平衡的原理,具有可能得到全局最优解和效率高的优点。使用该算法对海上风电场微观选址优化进行仿真,并与现有方法比较。结果表明,所提出的算法得到的排布方式发电量最高,并具有优化精度高、速度快和优化排布较为均匀的特点。该研究结果可以为实际工程应用提供参考。 相似文献
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摘要: 风电出力的随机性和间歇性使得风电在接入发电系统时会对发电系统可靠性造成影响。考虑到风电出力与负荷之间存在一定的相关性,提出了一种基于模糊聚类的风电场多状态可靠性模型。模型根据风电场出力与负荷数据的分布情况,使用两维模糊聚类对数据进行状态划分,并计算各状态之间的转移概率,最后通过序贯蒙特卡罗模拟对含风电场发电系统进行可靠性评估。算例分析结果表明,所建模型能够很好地模拟出风电场出力和负荷的分时序列,且可靠性分析结果准确有效。 相似文献
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针对大规模海上风电集电系统拓扑结构优化问题,提出一种改进单亲遗传算法,建立了集电系统全寿命周期成本现值计算模型,并以现值和最小为目标,通过设计满足海缆载流量约束的种群生成方式和与交叉点个数相关的淘汰系数来避免海缆交叉,优化对比了35、66 kV电压等级的集电系统拓扑结构。算例结果表明,提出的改进单亲遗传算法与传统算法相比总成本可减少14.2%,具有较好的寻优能力;与35 kV相比,集电系统采用66 kV电压等级综合效益更好,可为大规模海上风电场集电系统规划设计提供参考。 相似文献
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针对海上风电场集电多分支线路导致的故障定位精度不高的问题,提出一种基于行波原理与故障分支判定矩阵的故障区段定位方法。分析风电场拓扑结构和行波波头传输路径,建立固有距离差值矩阵。利用变分模态分解(VMD)和Teager能量算子(TEO)标定各端故障初始行波波头,并根据双端行波法得出故障距离差值矩阵。通过计算故障距离差值矩阵与固有距离差值矩阵的差值,构建故障分支判据判定矩阵,并根据不同故障点判定矩阵之间的差别,提出相应的故障区段判定依据。仿真结果表明:所提故障区段定位方法精确率高,且不受过渡电阻、故障类型等因素的影响。 相似文献
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为克服含风电场可靠性评估中需已知风速分布函数的缺点,提出了一种基于三阶多项式正态变换(TPNT)的非序贯蒙特卡洛模拟法评估含风电场发输电系统的可靠性。在已知风速历史数据或风速分布函数的情况下,通过TPNT构建风速随机变量与标准正态分布变量的关系,进而利用标准正态分布函数的性质产生具有任意数量的具有指定相关性的风速样本,并应用于风电场接入的发输电系统可靠性计算中。通过算例分析验证了TPNT应用于发输电系统可靠性计算中的适用性。在此基础上,从风速相关性、额定容量、风资源强度和风电场位置四个角度分析了风电场接入对可靠性的影响。为含风电场发输电系统可靠性的评估提供了新思路。 相似文献
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An optimization framework for global optimization of the cable layout topology for offshore wind farm (OWF) is presented. The framework designs and compares closed-loop and radial layouts for the collection system of OWFs. For the former, a two-stage stochastic optimization program based on a mixed integer linear programming (MILP) model is developed, while for the latter, a hop-indexed full binary model is used. The purpose of the framework is to provide a common base for assessing both designs economically, using the same underlying contingency treatment. A discrete Markov model is implemented for calculating the cable failure probability, useful for estimating the time under contingency for multiple power generation scenarios. The objective function supports simultaneous optimization of (i) initial investment (network topology and cable sizing), (ii) total electrical power loss costs and (iii) operation costs due to energy curtailment from cable failures. Constraints are added accounting for common engineering aspects. The applicability of the full method is demonstrated by tackling three differently sized real-world OWFs. Results show that (i) the profitability of either topology type depends strongly on the project size and wind turbine rating. Closed loop may be a competitive solution for large-scale projects where large amounts of energy are potentially curtailed. (ii) The stochastic model presents low tractability to tackle large-scale instances, increasing the required computing time and memory resources. (iii) Strategies must be adopted in order to apply stochastic optimization for modern OWFs, intending analytically or numerically simplification of mathematical models. 相似文献
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Reliability evaluation of power‐generating systems gives a mechanism to guarantee proper system operations in the face of different uncertainties including equipment failures. It is regularly not attainable to identify all possible failure states to figure the reliability indices because of the large number of system states engaged with system operations. Therefore, a hybrid optimization technique is required to analyse the reliability of the power system. This paper proposes a hybrid optimization technique to evaluate the reliability of a power system for the generation expansion planning incorporating wind energy source. The proposed hybrid methodology is the joined execution of both ant lion optimization algorithm (ALO) and lightning search algorithm (LSA), and it is named as ANLSA. ALO searching behavior is enhanced by LSA. Through the inherent convergence mechanisms, ANLSA search the meaningful system states. The most probable failure states contribute reliability indices of power generating system including mean down time (MDT), loss of load probability (LOLP), loss of load expectation (LOLE), loss of load frequency (LOLF), and expected demand not supplied (EDNS). Furthermore, ANLSA is utilized to assess the reliability of system under normal condition, integration of wind farm with capacity of 150 MW, and considering spinning reserve requirement (SRR). By then, the proposed work is actualized in MATLAB/Simulink platform and it is demonstrated on IEEE reliability test system (IEEE RTS‐79). Furthermore, the statistical analysis of proposed and existing techniques such as Monte Carlo simulation (MCS) and discrete convolution (DC) is considered. The comparison results demonstrate that proposed approach confirms its ability for evaluating the power system reliability. 相似文献
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Energy shortages and environmental problems associated with nonrenewable energy generation techniques have become increasingly prominent worldwide. Solar photovoltaic power generation is able to supply clean, environmentally friendly, and inexhaustible energy. Together with issues related to the expansion of scale, strong stochastic volatility and unpredictability have posed huge challenges to the stability and reliability of this power generation system. The present study proposed a reliable method to evaluate the stationary distribution probability based on the Markov chain method. First, the solar generation system was modeled based on the solar battery. Second, the stochastic property of the solar energy output power was derived and the simulation experiment adopted to verify the feasibility of results. Third, the energy storage device discharge process was modeled based on the Markov chain method and the evaluation method for the reliability of the solar power generation system obtained. Finally, validity of the method was simulated and verified. 相似文献
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大规模海上风电场集群并网将对电力系统静态电压稳定产生影响。文章通过研究电网侧发生电压跌落或者上升,提出含柔性直流输电海上风电场集群的协同无功控制策略。该策略以电网故障节点电压快速恢复为目标,考虑了柔性直流输电方式的特点,充分利用交流海底电缆的输电特性,采用就地控制和远方控制相结合的无功控制策略。该策略首先确定含交直流柔性输电系统中的无功控制节点,并计算各节点相对电压跌落或上升节点的电压/无功灵敏度,然后基于无功补偿装置的运行状态、系统潮流分布,求解各节点控制的最大容量,最后利用遗传算法确定各控制节点的无功控制量。以改进IEEE 39节点系统为算例进行了仿真分析,结果表明,该策略提高了海上风电场集群对电网电压的支撑作用。 相似文献
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以欧洲Lillgrund海上风电场为例,建立基于Larsen尾流模型及线性叠加模型的风电场输出功率及发电量计算模型;考虑风电机组偏航偏差等风向不确定性的影响,建立基于高斯平均方法的风电场计算功率修正模型;结合风电场实测数据及发电量计算收敛过程分析,研究了修正模型对风电场功率及发电量计算的影响。结果表明,所建立的尾流作用下的风电场功率计算模型能够较好地反应实际风电场的尾流影响特征,高斯平均修正方法进一步提高了尾流作用下风电场功率计算精度,并提高了发电量计算的收敛速度。在风电场年发电量计算中考虑风向不确定性的影响,对于提高模型评估与验证的准确性具有重要意义。 相似文献