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Fuzzy-GA based algorithm for optimal placement and sizing of distribution static compensator (DSTATCOM) for loss reduction of distribution network considering reconfiguration 被引量:1
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作者 Mohammad Mohammadi Mahyar Abasi A.Mohammadi Rozbahani 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第2期245-258,共14页
This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devic... This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devices and the cost of system operation, namely, energy loss cost due to both reconfiguration and DSTATCOM placement, are combined to form the objective function to be minimized. The distribution system tie switches, DSTATCOM location and size have been optimally determined to obtain an appropriate operational condition. In the proposed approach, the fuzzy membership function of loss sensitivity is used for the selection of weak nodes in the power system for the placement of DSTATCOM and the optimal parameter settings of the DFACTS device along with optimal selection of tie switches in reconfiguration process are governed by genetic algorithm(GA). Simulation results on IEEE 33-bus and IEEE 69-bus test systems concluded that the combinatorial method using DSTATCOM and reconfiguration is preferable to reduce power losses to 34.44% for 33-bus system and to 45.43% for 69-bus system. 展开更多
关键词 distribution FACTS (DFACTS) distribution static compensator (DSTATCOM) network reconfiguration genetic algorithm fuzzy membership function power loss reduction
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Distributed blackboard decision-making framework for collaborative planning based on nested genetic algorithm 被引量:4
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作者 Yaozhong Zhang Lei Zhang Zhiqiang Du 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2015年第6期1236-1243,共8页
A distributed blackboard decision-making framework for collaborative planning based on nested genetic algorithm (NGA) is proposed. By using blackboard-based communication paradigm and shared data structure, multiple... A distributed blackboard decision-making framework for collaborative planning based on nested genetic algorithm (NGA) is proposed. By using blackboard-based communication paradigm and shared data structure, multiple decision-makers (DMs) can collaboratively solve the tasks-platforms allocation scheduling problems dynamically through the coordinator. This methodo- logy combined with NGA maximizes tasks execution accuracy, also minimizes the weighted total workload of the DM which is measured in terms of intra-DM and inter-DM coordination. The intra-DM employs an optimization-based scheduling algorithm to match the tasks-platforms assignment request with its own platforms. The inter-DM coordinates the exchange of collaborative request information and platforms among DMs using the blackboard architecture. The numerical result shows that the proposed black- board DM framework based on NGA can obtain a near-optimal solution for the tasks-platforms collaborative planning problem. The assignment of platforms-tasks and the patterns of coordination can achieve a nice trade-off between intra-DM and inter-DM coordination workload. 展开更多
关键词 distributed collaborative planning BLACKBOARD decision maker (DM) nested genetic algorithm (NGA).
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Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm 被引量:2
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作者 李利华 符卓 +1 位作者 周和平 胡正东 《Journal of Central South University》 SCIE EI CAS 2013年第9期2625-2634,共10页
Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of t... Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision. 展开更多
关键词 uncertainty interval planning hierarchical OD logistics network design genetic algorithm
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Distribution network planning based on shortest path 被引量:2
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作者 路志英 高山 姚丽 《Journal of Central South University》 SCIE EI CAS 2012年第9期2534-2540,共7页
In order to form an algorithm for distribution network routing,an automatic routing method of distribution network planning was proposed based on the shortest path.The problem of automatic routing was divided into two... In order to form an algorithm for distribution network routing,an automatic routing method of distribution network planning was proposed based on the shortest path.The problem of automatic routing was divided into two steps in the method:the first step was that the shortest paths along streets between substation and load points were found by the basic ant colony algorithm to form a preliminary radial distribution network,and the second step was that the result of the shortest path was used to initialize pheromone concentration and pheromone updating rules to generate globally optimal distribution network.Cases studies show that the proposed method is effective and can meet the planning requirements.It is verified that the proposed method has better solution and utility than planning method based on the ant colony algorithm. 展开更多
关键词 distribution network planning shortest path ant colony algorithm PHEROMONE
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The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller 被引量:8
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作者 CHENQing-Geng WANGNing HUANGShao-Feng 《自动化学报》 EI CSCD 北大核心 2005年第4期646-650,共5页
Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by co... Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by competition between distribution populations to reduce the search zone.This method is applied to design of optimal parameters of PID controllers with examples, and thesimulation results show that satisfactory performances are obtained. 展开更多
关键词 遗传算法 PID控制器 优化设计 参数设置
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Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties 被引量:9
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作者 Sajad Najafi Ravadanegh Mohammad Reza Jannati Oskuee Masoumeh Karimi 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第8期1837-1849,共13页
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a... This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration. 展开更多
关键词 optimal reconfiguration renewable energy resources sitting and sizing capacitor allocation electric distribution system uncertainty modeling scenario based-stochastic programming multi-objective genetic algorithm
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Application of Interval Algorithm in Rural Power Network Planning
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作者 GU Zhuomu ZHAO Yulin 《Journal of Northeast Agricultural University(English Edition)》 CAS 2009年第3期57-60,共4页
Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization r... Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality. 展开更多
关键词 rural power network optimization planning load uncertainty interval algorithm genetic/tabu search combination algorithm
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Target distribution in cooperative combat based on Bayesian optimization algorithm 被引量:6
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作者 Shi Zhi fu Zhang An Wang Anli 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2006年第2期339-342,共4页
Target distribution in cooperative combat is a difficult and emphases. We build up the optimization model according to the rule of fire distribution. We have researched on the optimization model with BOA. The BOA can ... Target distribution in cooperative combat is a difficult and emphases. We build up the optimization model according to the rule of fire distribution. We have researched on the optimization model with BOA. The BOA can estimate the joint probability distribution of the variables with Bayesian network, and the new candidate solutions also can be generated by the joint distribution. The simulation example verified that the method could be used to solve the complex question, the operation was quickly and the solution was best. 展开更多
关键词 target distribution Bayesian network Bayesian optimization algorithm cooperative air combat.
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Optimal transmission lines assignment with maximal reliabilities in multi-source multi-sink multi-state computer network 被引量:1
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作者 章筠 徐正国 +2 位作者 王文海 卢建刚 孙优贤 《Journal of Central South University》 SCIE EI CAS 2013年第7期1868-1877,共10页
The optimal transmission lines assignment with maximal reliabilities (OTLAMR) in the multi-source multi-sink multi-state computer network (MMMCN) was investigated. The OTLAMR problem contains two sub-problems: the MMM... The optimal transmission lines assignment with maximal reliabilities (OTLAMR) in the multi-source multi-sink multi-state computer network (MMMCN) was investigated. The OTLAMR problem contains two sub-problems: the MMMCN reliabilities evaluation and multi-objective transmission lines assignment optimization. First, a reliability evaluation with a transmission line assignment (RETLA) algorithm is proposed to calculate the MMMCN reliabilities under the cost constraint for a certain transmission lines configuration. Second, the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to find the non-dominated set of the transmission lines assignments based on the reliabilities obtained from the RETLA algorithm. By combining the RETLA and the NSGA-II algorithms together, the RETLA-NSGA II algorithm is proposed to solve the OTLAMR problem. The experiments result show that the RETLA-NSGA II algorithm can provide efficient solutions in a reasonable time, from which the decision makers can choose the best solution based on their preferences and experiences. 展开更多
关键词 multi-state network reliability evaluation transmission lines assignments multi-objective optimization non-dominatedsorting genetic algorithm II
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Multi-objective coordination optimal model for new power intelligence center based on hybrid algorithm 被引量:1
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作者 刘吉成 牛东晓 乞建勋 《Journal of Central South University》 SCIE EI CAS 2009年第4期683-689,共7页
In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a... In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network. 展开更多
关键词 power intelligence center (PIC) coordination optimal model power network planning hybrid algorithm
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Study on Optimal Topology for Computer Local Double Loop Networks
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作者 Li LayuanWuhan University of Water Transportation Engineering, Wuhan 430063, P.R.China 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1992年第4期37-52,共16页
A dist ributed optimal local double loop (DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definition... A dist ributed optimal local double loop (DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions and theorems are described and proved. An algorithm which can optimize the double loop networks is presented. The optimal values of the topologic parameters for the DOLDL have been obtained by the algorithm, and these numerical results are analyzed. The study shows that the bounds of the optimal diameter d and average hop distance a for this class of networks are [3N- 2]≤d≤[3N ] and (5N/9 (N-1))-(3N -1.8)<a<(5N/9(N-1)) (3N -0.9),respectively (N is the number of nodes in the network ). A class of the distributed routing algorithms for the DOLDL and the implementation procedure of an adaptive fault-tolerant algorithm are proposed and analyzed. The correctness of the algorithm has also been verified by simulating. 展开更多
关键词 Local networks Loop networks optimal topology Distributed routing algorithm.
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基于GA-LSTM的桥梁缆索腐蚀钢丝力学性能预测模型 被引量:5
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作者 缪长青 吕悦凯 万春风 《东南大学学报(自然科学版)》 北大核心 2025年第1期140-145,共6页
为了精准捕捉桥梁缆索腐蚀钢丝的时变规律并预测其力学性能,开发了一种基于遗传算法(genetic algorithm, GA)优化的长短期记忆(long short-term memory, LSTM)神经网络模型。该模型利用GA依次优化LSTM模型的迭代次数、隐藏层层数、神经... 为了精准捕捉桥梁缆索腐蚀钢丝的时变规律并预测其力学性能,开发了一种基于遗传算法(genetic algorithm, GA)优化的长短期记忆(long short-term memory, LSTM)神经网络模型。该模型利用GA依次优化LSTM模型的迭代次数、隐藏层层数、神经元数量、窗口大小4个超参数,以预测不同腐蚀特征状态下钢丝的力学性能。将其与传统LSTM和GA-反向传播模型的预测结果进行比较。结果表明,GA-LSTM模型具有更高的预测精度和鲁棒性。在屈服强度与极限强度预测效果方面,均方根误差(root mean square error, RMSE)、平均绝对误差(mean absolute error, MAE)、决定系数分别提高约44%~61%、43%~57%、35%~92%。在屈服应变与极限应变预测效果方面,RMSE、MAE、决定系数分别提高约0~46%、7%~49%、12%~229%。所建立的模型可以作为一个有用的工具支持桥梁缆索腐蚀安全性评估工作。 展开更多
关键词 桥梁缆索腐蚀钢丝 力学性能预测 时序预测 神经网络 遗传算法 超参数优化
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基于层级分解的前围声学包多目标优化 被引量:1
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作者 杨帅 吴宪 薛顺达 《振动与冲击》 北大核心 2025年第3期267-277,共11页
搭建了前围声学包多层级目标分解架构,提出GAPSO-RBFNN(genetic algorithm particle swarm optimization-radial basis function neural network)预测模型,并将其应用于多层级目标分解架构。将材料数据库、覆盖率、泄漏量作为优化的变... 搭建了前围声学包多层级目标分解架构,提出GAPSO-RBFNN(genetic algorithm particle swarm optimization-radial basis function neural network)预测模型,并将其应用于多层级目标分解架构。将材料数据库、覆盖率、泄漏量作为优化的变量范围,以PBNR(power based noise reduction)均值作为约束,以质量和成本作为优化目标,采用非支配排序遗传算法(nondominated sorting genetic algorithm II,NSGA-II)进行多目标优化,得到Pareto多目标解集。并从中选取满足设计目标的最佳组合方案(材料组合、覆盖率、前围过孔密封方案选型)。结果显示,该模型最终的优化结果与实测结果接近,误差分别为0.35%,1.47%,1.82%,相较于初始声学包方案,优化后的结果显示,PBNR均值提升3.05%,其质量降低52.38%,成本降低15.15%,验证了所提方法的有效性和准确性。 展开更多
关键词 GAPSO-RBFNN 声学包 PBNR NSGA-II Pareto多目标解集
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基于GA-BP神经网络的烟叶打叶风分工艺参数优化
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作者 田斌强 付龙 +5 位作者 唐剑宁 刘辉 夏凡 黄沙 刘莉艳 郭筠 《河南农业大学学报》 北大核心 2025年第3期508-515,共8页
【目的】获得烤烟烟叶在打叶风分中的最佳工艺参数,进一步优化叶片结构。【方法】选取打叶复烤工艺中的前5级打叶转速和第7、第8风机频率共7个因素,每个因素设3个水平开展正交试验,以正交试验结果确定较优的工艺参数组合为数据样本集构... 【目的】获得烤烟烟叶在打叶风分中的最佳工艺参数,进一步优化叶片结构。【方法】选取打叶复烤工艺中的前5级打叶转速和第7、第8风机频率共7个因素,每个因素设3个水平开展正交试验,以正交试验结果确定较优的工艺参数组合为数据样本集构建GA-BP神经网络模型,并结合NSGA-Ⅱ的方法对工艺参数进一步优化。【结果】正交试验确定较高的大中片率最佳工艺参数为:第1至5级打叶转速分别为493、471、620、798、794 r·min^(-1),第7、第8级风机频率分别为49、45 Hz,较低的碎片率和叶中含梗率的最优工艺参数为:第1至5级打叶转速分别为503、489、621、792、792 r·min^(-1),第7、第8级风机频率分别为50、46 Hz。经GA-BP神经网络模型优化后为第1至5级打叶转速分别为485、474、620、796、794 r·min^(-1),第7、第8级风机频率分别为49、46 Hz,在此条件下,大中片率提升了1.52个百分点,叶中含梗率、碎片率分别降低了0.09和0.08个百分点。【结论】在正交试验的基础上,通过GA-BP神经网络模型优化多工艺参数,叶片结构更为合理,可为提升烟叶叶片加工质量提供参考。 展开更多
关键词 叶片结构 BP神经网络 遗传算法 打叶风分 参数优化
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基于动态区域划分的配电网台区三相不平衡治理策略
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作者 陈晓龙 徐颖 李斌 《电力自动化设备》 北大核心 2025年第8期208-216,共9页
传统三相不平衡治理仅关注变压器关口处的三相不平衡情况,忽略了台区内部不平衡特征,且多采用静态调相策略,难以适应灵活源荷接入下低压配电网运行状态的动态变化。为此,提出了一种基于动态区域划分的三相不平衡治理策略。提出基于分区... 传统三相不平衡治理仅关注变压器关口处的三相不平衡情况,忽略了台区内部不平衡特征,且多采用静态调相策略,难以适应灵活源荷接入下低压配电网运行状态的动态变化。为此,提出了一种基于动态区域划分的三相不平衡治理策略。提出基于分区评价指数与阈值触发机制的动态分区方法,以划定后续相序优化的区域范围。建立考虑多类型灵活调节资源的双层优化模型,上层以各分区三相不平衡度最小为目标优化相序配置,下层构建以运行成本最小为目标的电压优化模型。采用基于云模型改进的遗传算法和Gurobi求解器分别求解上下层模型。基于改进的IEEE 123节点系统和0.38 kV实际配电网台区进行仿真,验证了所提策略的有效性与优越性。 展开更多
关键词 配电网 三相不平衡 动态分区 双层优化模型 相序优化 云模型 遗传算法
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基于模拟退火遗传算法的舰船编队网络优化调度方法
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作者 陆青梅 赵山林 高媛 《舰船科学技术》 北大核心 2025年第10期155-160,共6页
舰船编队网络是一个复杂的通信系统,为减少通信延迟,确保信息的及时传递,提高整个编队的反应速度和作战效能,提出基于模拟退火遗传算法的舰船编队网络优化调度方法。以最小通信总延迟与总能耗为目标函数,通过设置约束条件,建立舰船编队... 舰船编队网络是一个复杂的通信系统,为减少通信延迟,确保信息的及时传递,提高整个编队的反应速度和作战效能,提出基于模拟退火遗传算法的舰船编队网络优化调度方法。以最小通信总延迟与总能耗为目标函数,通过设置约束条件,建立舰船编队网络优化调度模型。利用模拟退火遗传算法求解调度模型,实现最小通信总延迟与总能耗的舰船编队网络优化调度。实验结果表明,应用本文方法后,舰船编队网络的通信总延迟在0~80 ms之间,能耗保持在580 kWh以下。说明本文方法可以有效提升舰船编队网络通信的稳定性和效率,显著增强了编队的作战适应性和应变能力,为海军作战和海上安全提供更为可靠的支撑。 展开更多
关键词 模拟退火 遗传算法 舰船编队网络 优化调度 适应性 应变能力
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应急电源车派遣联合网络重构的电网故障预案
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作者 谢敏 谢宇星 +4 位作者 董凯元 卢燕旋 张世平 宁楠 刘明波 《电网技术》 北大核心 2025年第7期3031-3041,I0109-I0114,共17页
在电网故障预案中,考虑应急电源车派遣与网络重构进行联合优化对故障进行恢复,可以防止失电孤电网的形成并大幅减少故障电网的停电成本。针对主配网故障,提出了应急电源车派遣联合网络重构的电网故障预案。首先,提出路径权值的概念并改... 在电网故障预案中,考虑应急电源车派遣与网络重构进行联合优化对故障进行恢复,可以防止失电孤电网的形成并大幅减少故障电网的停电成本。针对主配网故障,提出了应急电源车派遣联合网络重构的电网故障预案。首先,提出路径权值的概念并改进Dijkstra算法构建最短路径权值矩阵,建立电力-交通网耦合模型。其次,对应急电源车派遣成本和网络重构成本进行量化,提出应急电源车派遣模型和网络重构模型。然后,基于电力-交通网耦合模型与故障恢复元件模型,考虑主配网协同优化,以网损、购电成本、停电成本、应急电源车派遣成本、网络重构成本为优化目标,提出了应急电源车派遣联合网络重构的电网故障预案模型。最后,通过算例分析进行验证,结果表明,联合应急电源车派遣和网络重构的电网故障预案对不同电网故障场景均有显著的恢复效果。 展开更多
关键词 故障预案 应急电源车派遣 网络重构 联合优化 主配协同 最短路径权值矩阵
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基于水力响应时间的灌区实时渠系优化配水模型
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作者 张运鑫 郭邦 +3 位作者 樊煜 高占义 杨芸 刘洁 《节水灌溉》 北大核心 2025年第5期39-44,50,共7页
在实际情况中灌区配水条件不是一成不变的,灌区供水流量的变化以及水流运动时间的大小对配水方案的制定和渠道精准配水有着重要影响,因此需要建立相应的模型进行优化渠系配水。考虑到灌区供水流量实时变化以及水流运动时间对配水方案的... 在实际情况中灌区配水条件不是一成不变的,灌区供水流量的变化以及水流运动时间的大小对配水方案的制定和渠道精准配水有着重要影响,因此需要建立相应的模型进行优化渠系配水。考虑到灌区供水流量实时变化以及水流运动时间对配水方案的影响,建立了基于水力响应时间的实时优化配水模型。当供水流量变大或变小时,模型提供2种配水方式:方式1为优先调节流量,再调节配水渠道数量;方式2为增加或减少下级配水渠道的数量。模型以各配水支渠的配水流量、开始配水时间和结束配水时间为决策变量,以配水历时最短和渠道输水损失最小为目标函数,通过精英策略的非支配排序遗传算法(NSGA-Ⅱ)进行求解。结果表明:2种方式的配水流量均在流量上下限之间,满足配水要求,响应时间的计算提供了更精准的配水时间;方式1可以保证所有渠道不间断配水,但出现了部分渠道配水流量较小的情况,配水历时为128.66 h;方式2中所有渠道均大流量配水,且配水流量大小能保持稳定,配水历时为122.13 h,但部分渠道会中断配水。水力响应时间的灌区实时渠系优化配水模型能够在供水流量变化时提供配水方案,方式1比方式2的配水流量波动大,渠道输水损失大,且配水时间多6.54 h。2种方式都考虑了水力响应时间对配水方案的影响,从而增加配水时间的准确性,可为灌区的配水工作提供指导。 展开更多
关键词 渠系配水 水力响应时间 优化配水模型 遗传算法 实时配水
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A hybrid genetic algorithm to the program optimization model based on a heterogeneous network
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作者 CHEN Hang DOU Yajie +3 位作者 CHEN Ziyi JIA Qingyang ZHU Chen CHEN Haoxuan 《Journal of Systems Engineering and Electronics》 2025年第4期994-1005,共12页
Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and ... Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm. 展开更多
关键词 program optimization heterogeneous network genetic algorithm portfolio selection.
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基于动态虚拟故障行波定位原理的配电网故障定位装置优化配置
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作者 李泽文 张一鸣 +3 位作者 夏翊翔 冯译萱 王远川 葛俊辰 《电力系统及其自动化学报》 北大核心 2025年第3期129-138,共10页
为提高行波定位装置的利用率,提出一种基于动态虚拟故障行波定位原理的配电网故障定位装置优化配置方法。首先针对配电网的结构特点进行可测性分析,提出总体优化配置原则;然后以装置配置数最少为目标函数建立数学模型,并通过自适应遗传... 为提高行波定位装置的利用率,提出一种基于动态虚拟故障行波定位原理的配电网故障定位装置优化配置方法。首先针对配电网的结构特点进行可测性分析,提出总体优化配置原则;然后以装置配置数最少为目标函数建立数学模型,并通过自适应遗传算法求解;最后根据冗余度评价得出最优配置方案,并以贪心策略确定行波定位装置的动态装设顺序。仿真验证结果表明,该方法在保证较高定位精度的前提下,可有效减少行波定位装置的配置数量,具有较高的经济性。 展开更多
关键词 配电网 行波 故障定位 优化配置 遗传算法
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