电力系统保护与控制
電力繫統保護與控製
전력계통보호여공제
Power System Protection and Control
2015年
17期
57-62
,共6页
配电网重构%网络抗毁性%机会约束规划%蚁群算法%Pareto最优解
配電網重構%網絡抗燬性%機會約束規劃%蟻群算法%Pareto最優解
배전망중구%망락항훼성%궤회약속규화%의군산법%Pareto최우해
distribution network reconfiguration%network survivability%chance constrained programming%ant colony algorithm (ACO)%Pareto optimality
为了提高配电网的供电可靠性,从网络自然连通性角度,引入网络抗毁性指标作为配电网重构的一个新目标函数。同时考虑风电出力的随机性与间歇性,根据风速区间及风速概率密度函数构建多个风电出力随机变量,以及对应概率。在此基础上,以开关状态为优化变量、风电出力为随机变量以及在置信水平下的网络损耗最小为另一个目标函数建立了基于机会约束规划的含风电的配电网多目标重构模型。应用改进蚁群算法,结合生成树策略保证蚂蚁路径满足网络辐射状网络拓扑约束,求解所建配网重构模型,并利用Pareto寻优得到最优解集。IEEE33节点和PG&E69节点系统算例仿真结果验证了该模型和算法的有效性。
為瞭提高配電網的供電可靠性,從網絡自然連通性角度,引入網絡抗燬性指標作為配電網重構的一箇新目標函數。同時攷慮風電齣力的隨機性與間歇性,根據風速區間及風速概率密度函數構建多箇風電齣力隨機變量,以及對應概率。在此基礎上,以開關狀態為優化變量、風電齣力為隨機變量以及在置信水平下的網絡損耗最小為另一箇目標函數建立瞭基于機會約束規劃的含風電的配電網多目標重構模型。應用改進蟻群算法,結閤生成樹策略保證螞蟻路徑滿足網絡輻射狀網絡拓撲約束,求解所建配網重構模型,併利用Pareto尋優得到最優解集。IEEE33節點和PG&E69節點繫統算例倣真結果驗證瞭該模型和算法的有效性。
위료제고배전망적공전가고성,종망락자연련통성각도,인입망락항훼성지표작위배전망중구적일개신목표함수。동시고필풍전출력적수궤성여간헐성,근거풍속구간급풍속개솔밀도함수구건다개풍전출력수궤변량,이급대응개솔。재차기출상,이개관상태위우화변량、풍전출력위수궤변량이급재치신수평하적망락손모최소위령일개목표함수건립료기우궤회약속규화적함풍전적배전망다목표중구모형。응용개진의군산법,결합생성수책략보증마의로경만족망락복사상망락탁복약속,구해소건배망중구모형,병이용Pareto심우득도최우해집。IEEE33절점화PG&E69절점계통산례방진결과험증료해모형화산법적유효성。
To improve the reliability of power supply distribution network, network survivability index is introduced as a new objective function of the distribution network reconfiguration, from the point of network connectivity. At the same time, considering the randomness and intermittent of the output of the wind power generations (WPG), this paper builds up wind power output random variables and their corresponding probability based on wind speed and wind speed probability density function. On this basis, taking the switch state as optimization variables, the output of WPG as random variables, the minimum network loss higher than confidence level as another objective function, a chance constrained programming based distribution network multi-objective reconfiguration model with WPG is built. It applies the improved ant colony algorithm, combines with the strategy of spanning tree which ensure that the ants path to meet the structure of the distribution network, to solve the built model. And then, the Pareto optimality is used to evaluate the result to get the optimal solution set. The results of IEEE33 system and PG&E69 system verify the validity of the model and algorithm.