运筹与管理
運籌與管理
운주여관리
OPERATIONS RESEARCH AND MANAGEMENT SCIENCE
2014年
3期
209-218
,共10页
曾鸣%薛松%史慧%欧阳邵杰
曾鳴%薛鬆%史慧%歐暘邵傑
증명%설송%사혜%구양소걸
新能源管理规划%混合蛙跳决策算法%智能配电网%分布式发电
新能源管理規劃%混閤蛙跳決策算法%智能配電網%分佈式髮電
신능원관리규화%혼합와도결책산법%지능배전망%분포식발전
new energy management planning%shuffled frog leaping decision-making algorithm%distributed generation%smart distribution grid
分布式光伏的大量接入智能配电网后,可能导致三相电流的失衡,进而破坏配电系统的安全稳定性。对此,本文构建了以电流不平衡和电能损失最小化为目标的含分布式光伏的配电网优化的多目标模型,旨在解决大规模分布式光伏发电并网后配电网相位平衡的问题;然后,用随机单纯形法对混合蛙跳算法进行优化,改进了蛙跳算法求解优化问题时极易陷入局部最优以及计算效率较低的缺点,并和决策算法相结合,提出适用本文算例的改进的多目标混合蛙跳决策算法,确保能以极快的搜索速度和较高的计算精度得到最优解;最后,以IEEE-123节点三相不平衡测试系统为例,通过控制变量的相关操作实现配电系统的三相平衡。对比分析基础案例和优化算例的差异,验证了本文所提算法的先进性和实用性。
分佈式光伏的大量接入智能配電網後,可能導緻三相電流的失衡,進而破壞配電繫統的安全穩定性。對此,本文構建瞭以電流不平衡和電能損失最小化為目標的含分佈式光伏的配電網優化的多目標模型,旨在解決大規模分佈式光伏髮電併網後配電網相位平衡的問題;然後,用隨機單純形法對混閤蛙跳算法進行優化,改進瞭蛙跳算法求解優化問題時極易陷入跼部最優以及計算效率較低的缺點,併和決策算法相結閤,提齣適用本文算例的改進的多目標混閤蛙跳決策算法,確保能以極快的搜索速度和較高的計算精度得到最優解;最後,以IEEE-123節點三相不平衡測試繫統為例,通過控製變量的相關操作實現配電繫統的三相平衡。對比分析基礎案例和優化算例的差異,驗證瞭本文所提算法的先進性和實用性。
분포식광복적대량접입지능배전망후,가능도치삼상전류적실형,진이파배배전계통적안전은정성。대차,본문구건료이전류불평형화전능손실최소화위목표적함분포식광복적배전망우화적다목표모형,지재해결대규모분포식광복발전병망후배전망상위평형적문제;연후,용수궤단순형법대혼합와도산법진행우화,개진료와도산법구해우화문제시겁역함입국부최우이급계산효솔교저적결점,병화결책산법상결합,제출괄용본문산례적개진적다목표혼합와도결책산법,학보능이겁쾌적수색속도화교고적계산정도득도최우해;최후,이IEEE-123절점삼상불평형측시계통위례,통과공제변량적상관조작실현배전계통적삼상평형。대비분석기출안례화우화산례적차이,험증료본문소제산법적선진성화실용성。
A large amount of distributed photovoltaic accessing to smart distribution grid may lead to an imbalance in the three-phase current , and then could damage the security and stability of the distribution system .So this paper constructs a distribution multi-objective optimization model , the objectives of which are current imbalance minimization and energy loss minimization .This model aims at solving phase balance problems of distribution network after large-scale distributed PV into grid .Then, Shuffled Frog Leap Algorithm is optimized by Random Nelder Mead , improving shortcomings of SFLA .Combining it with decision algorithm , this paper proposes improved multi-objective decision-shuffled frog leaping algorithm for the numerical example .IMO-SLFDA can ensure it obtains the optimal solution in an extremely fast search speed and high accuracy .Last, this paper takes the IEEE 123-bus three phase unbalanced test system as the numerical example , and three phase balance of the distribution system is achieved by controlling the variables related operations .Making the comparative analysis of the difference between base case and optimized example , the proposed algorithm is verified , advanced and practical .