基于无重访NSGA-Ⅱ算法的配电网多目标重构

将基于空间二叉分割理论的无重访机制与基于多目标Pareto最优化思想的第二代非支配排序遗传算法（Non-dominated Sorting Genetic Algorithm-Ⅱ,NSGA-Ⅱ）相结合,构建了无重访NSGA-Ⅱ算法,并应用于求解同时考虑网损降低和供电可靠性提高的多目标配电网络重构问题。所构建的无重访NSGA-Ⅱ算法实现了严格意义上的不重复搜索,避免了重复方案的潮流及可靠性计算,节约了计算资源。IEEE16、IEEE33测试系统的计算结果表明能够在较少的迭代次数下得到每个目标方向上的最优解以及包含若干非支配解的Pareto最优前沿解集。根据网损与可靠性目标之间的关联关系及相应重构...

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Bibliographic Details
Published in:电力系统保护与控制 Vol. 44; no. 23; pp. 10 - 16
Main Author: 程虹 高元海 王淳 杨为群 朱文广 彭莉萍 罗路平 敖鑫
Format: Journal Article
Language:Chinese
Published: 国网江西省电力公司经济技术研究院,江西南昌,330043%江西省电力设计院,江西 南昌,330096%南昌大学,江西 南昌,330031%国网江西省电力公司,江西 南昌,330077 2016
Subjects:
NSGA-
Pareto最优
可靠性
无重访
空间二叉分割
网络重构
NSGA-II
binary space partitioning
无重访
Pareto最优
空间二叉分割
reliability
non-revisiting
Pareto optimality
network reconfiguration
可靠性
网络重构
ISSN:1674-3415
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Summary:将基于空间二叉分割理论的无重访机制与基于多目标Pareto最优化思想的第二代非支配排序遗传算法（Non-dominated Sorting Genetic Algorithm-Ⅱ,NSGA-Ⅱ）相结合,构建了无重访NSGA-Ⅱ算法,并应用于求解同时考虑网损降低和供电可靠性提高的多目标配电网络重构问题。所构建的无重访NSGA-Ⅱ算法实现了严格意义上的不重复搜索,避免了重复方案的潮流及可靠性计算,节约了计算资源。IEEE16、IEEE33测试系统的计算结果表明能够在较少的迭代次数下得到每个目标方向上的最优解以及包含若干非支配解的Pareto最优前沿解集。根据网损与可靠性目标之间的关联关系及相应重构方案的拓扑结构分析表明在解空间的全局范围内网损与可靠性目标具有较明显的一致关联性,不论对于网损还是可靠性的优化,网络拓扑都应该接近广度优先树而规避深度优先树。
Bibliography:network reconfiguration; reliability; non-revisiting; NSGA-II; binary space partitioning; Pareto optimality
A non-revisited NSGA-II algorithm, which integrates BSP （binary space partitioning）-based non-revisiting mechanism and the non-dominated sorting genetic algorithm-II （NSGA-II） based on the ideology of multi-objective Pareto optimization, is constructed and is then used to solve the problem of distribution networks multi-objective reconfiguration with the consideration of loss minimization and the improvement of reliability. The proposed algorithm achieves a strictly non-revisited research, which avoids the recalculation of power flow and reliability of revisited schemes and saves the computing resources. The test results of IEEE 16-bus and IEEE 33-bus sample systems indicate that the proposed method can obtain the optimal solution in every target direction as well as an optimal Pareto frontier aggregates including a lot of non-dominated solutions in less iterations. According to incidence relations betwe
ISSN:1674-3415
DOI:10.7667/PSPC160354