电力系统保护与控制
電力繫統保護與控製
전력계통보호여공제
POWER SYSTM PROTECTION AND CONTROL
2014年
2期
35-42
,共8页
陈亮%顾雪平%贾京华
陳亮%顧雪平%賈京華
진량%고설평%가경화
电力系统恢复%扩展黑启动%恢复安全裕度%多目标优化%快速非支配排序遗传算法%病毒进化
電力繫統恢複%擴展黑啟動%恢複安全裕度%多目標優化%快速非支配排序遺傳算法%病毒進化
전력계통회복%확전흑계동%회복안전유도%다목표우화%쾌속비지배배서유전산법%병독진화
power system restoration%extended black-start%restoration security margin%multi-objective optimization%fast and elitist non-dominated sorting genetic algorithm (NSGA-II)%virus evolution
为了保证黑启动小系统的安全恢复和合理兼顾多目标优化方法的快速搜索与局部搜索，提出基于病毒进化改进NSGA-II算法的综合功率支持和恢复安全裕度的扩展黑启动方案多目标优化方法。以初期阶段内发电量加权和最大化、电压稳定裕度最大化和维持节点电压在满意水平为目标建立多目标优化模型。在快速非支配排序遗传算法（NSGA-II）的染色体中引入生物病毒机制和病毒感染操作，利用病毒的横向感染对解空间进行局部搜索，避免强化全局寻优时的前沿退化。然后结合基于病毒进化改进NSGA-II算法与最短路径法对扩展黑启动方案求解出Pareto最优解集。以新英格兰10机39节点系统和河北南网实际系统为算例验证所提方法的有效性，该方法为决策者提供了更全局性的选择空间，从而保证扩展黑启动小系统安全可靠地恢复更多出力。
為瞭保證黑啟動小繫統的安全恢複和閤理兼顧多目標優化方法的快速搜索與跼部搜索，提齣基于病毒進化改進NSGA-II算法的綜閤功率支持和恢複安全裕度的擴展黑啟動方案多目標優化方法。以初期階段內髮電量加權和最大化、電壓穩定裕度最大化和維持節點電壓在滿意水平為目標建立多目標優化模型。在快速非支配排序遺傳算法（NSGA-II）的染色體中引入生物病毒機製和病毒感染操作，利用病毒的橫嚮感染對解空間進行跼部搜索，避免彊化全跼尋優時的前沿退化。然後結閤基于病毒進化改進NSGA-II算法與最短路徑法對擴展黑啟動方案求解齣Pareto最優解集。以新英格蘭10機39節點繫統和河北南網實際繫統為算例驗證所提方法的有效性，該方法為決策者提供瞭更全跼性的選擇空間，從而保證擴展黑啟動小繫統安全可靠地恢複更多齣力。
위료보증흑계동소계통적안전회복화합리겸고다목표우화방법적쾌속수색여국부수색，제출기우병독진화개진NSGA-II산법적종합공솔지지화회복안전유도적확전흑계동방안다목표우화방법。이초기계단내발전량가권화최대화、전압은정유도최대화화유지절점전압재만의수평위목표건립다목표우화모형。재쾌속비지배배서유전산법（NSGA-II）적염색체중인입생물병독궤제화병독감염조작，이용병독적횡향감염대해공간진행국부수색，피면강화전국심우시적전연퇴화。연후결합기우병독진화개진NSGA-II산법여최단로경법대확전흑계동방안구해출Pareto최우해집。이신영격란10궤39절점계통화하북남망실제계통위산례험증소제방법적유효성，해방법위결책자제공료경전국성적선택공간，종이보증확전흑계동소계통안전가고지회복경다출력。
To ensure the safe recovery of the black-start system and well synthesize the quick search and local search of multi-objective optimization method, an extended black-start multi-objective optimization method based on virus evolution improved NSGA-II algorithm considering power support and restoration security margin comprehensively is proposed. The optimization goals are designed to maximize the total weighted power generation output (MWh) of the black-start system, to maximize voltage stability margin and to maintain bus voltage at a satisfactory level. Biological virus mechanism and the infection-based operation are introduced into the chromosome of the fast and elitist non-dominated sorting genetic algorithm (NSGA-II). Horizontal infection of the virus is applied to improve local search capability in solution space and avoid the frontier degradation. The virus evolution improved NSGA-II algorithm and the Dijkstra algorithm are employed to solve the Pareto-optimal solutions of the extended black-start schemes. The effectiveness of the proposed method is validated by the optimization results on the New England 10-unit 39-bus power system and the southern power system of Hebei province. The method can provide decision-makers with greater choice of space and guarantee the extended initial black-start power system to recover more power generation output safely and reliably.
