电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2015年
2期
46-52,86
,共8页
徐波%韩学山%刘长银%侯艳权%姚越%牛志强
徐波%韓學山%劉長銀%侯豔權%姚越%牛誌彊
서파%한학산%류장은%후염권%요월%우지강
状态检修%功能关联%关联集分解%机会维修%设备个体损失%系统运行风险
狀態檢脩%功能關聯%關聯集分解%機會維脩%設備箇體損失%繫統運行風險
상태검수%공능관련%관련집분해%궤회유수%설비개체손실%계통운행풍험
condition-based maintenance%functional dependence%association sets decomposition%opportunistic maintenance%expected cost of equipment%system operation risk
状态检修背景下,为有机统筹系统设备间的功能关联性,提出基于关联集分解的系统状态检修的数学模型。该模型在设备状态变化规律已知的前提下,从设备间功能关联出发,给出关联集的概念,研究周期内,以关联集为基本单元进行检修决策。然后,借鉴机会维修的思想,给出关联集加入检修计划以后状态概率的求解方法。从而在此基础上,对由设备检修时机变动而引起的设备个体损失和系统运行风险进行量化。最后,以二者之和最小为目标,计及系统状态检修的约束条件,建立系统状态检修的数学模型,针对该模型采用遗传算法求解。通过算例对所提出模型的可行性和有效性进行了验证。
狀態檢脩揹景下,為有機統籌繫統設備間的功能關聯性,提齣基于關聯集分解的繫統狀態檢脩的數學模型。該模型在設備狀態變化規律已知的前提下,從設備間功能關聯齣髮,給齣關聯集的概唸,研究週期內,以關聯集為基本單元進行檢脩決策。然後,藉鑒機會維脩的思想,給齣關聯集加入檢脩計劃以後狀態概率的求解方法。從而在此基礎上,對由設備檢脩時機變動而引起的設備箇體損失和繫統運行風險進行量化。最後,以二者之和最小為目標,計及繫統狀態檢脩的約束條件,建立繫統狀態檢脩的數學模型,針對該模型採用遺傳算法求解。通過算例對所提齣模型的可行性和有效性進行瞭驗證。
상태검수배경하,위유궤통주계통설비간적공능관련성,제출기우관련집분해적계통상태검수적수학모형。해모형재설비상태변화규률이지적전제하,종설비간공능관련출발,급출관련집적개념,연구주기내,이관련집위기본단원진행검수결책。연후,차감궤회유수적사상,급출관련집가입검수계화이후상태개솔적구해방법。종이재차기출상,대유설비검수시궤변동이인기적설비개체손실화계통운행풍험진행양화。최후,이이자지화최소위목표,계급계통상태검수적약속조건,건립계통상태검수적수학모형,침대해모형채용유전산법구해。통과산례대소제출모형적가행성화유효성진행료험증。
In the context of condition-based maintenance,a condition-based maintenance decision-making model for power system is proposed based on association sets decomposition to coordinate functional dependence among different equipments. To investigate the functional dependence,the definition of equipment association sets is given.With the help of the equipment condition monitoring and prediction system,the instantaneous availability function of equipment association sets is deduced by considering scheduled maintenance and opportunistic maintenance in the preceding period.Furthermore,the quantitative expression of expected cost of equipment and system operation risk are provided.Then the system maintenance model is developed,with the minimized expected cost of equipment and system operation risk as the obj ective while taking maintenance constraints into account.The genetic algorithm is used to solve the model.Test results show the feasibility and validity of the proposed model.