| Faced with the double pressure of resources and supply side reformation,the power industry urgently needs to transform its original operation mode to a more environmentally friendly,low-carbon,more reliable and more intelligent one.Factors like the increasing proportion of new energy resources,the increasing types of new equipment and the diversification of active management measures in distribution network make distribution network programming face more uncertain challenges.Therefore,in view of active distribution network programming,how to fully consider the uncertain factors brought by new energy and then formulate more effective expansion scheme has great engineering significance and application value.As a result,an active distribution network expansion programming model based on uncertain network theory is proposed,which provides a new way to solve the uncertainty of new energy sources.Firstly,the mathematical concept of uncertain network theory is introduced,then its modeling and solving methods in active distribution network planning is elaborated in detail.Modeling the extended planning of active distribution network based on the minimum spanning tree problem in uncertain network theory,starting with the obtaining of the uncertainty weight factors of the extended power lines based on economical and reliable sub programming models.The concept of tree in uncertain network corresponding to the connected radial network tree set in planning program.Then the sub-programming models are built as follows.The first step,probabilistic uncertain set of time-block correlations is determined considering the time correlation between load and distributed power output.For the reliability weight part,established a component failure rate model that takes into account the type of equipment and its lifetime over the planned life,and in order to solve the problem of diversification of power supply paths caused by new types of equipment,active management measures and the increasing complexity of operation constraints,a two-stage overall optimal reliability method based on fault removal and power restoration is proposed,which can provide a more reasonable and reliable power restoration strategy and realize the overall utilization of power.The effectiveness of the proposed model is validated by examples.For the economical weight part,aiming at the whole process economy,an economical sub-programming model is proposed to coordinate the upgrade,new-built and active distribution management of the equipment,including distributed generation,network,static VAR compensation(SVC),substation and on-load tap changer(OLTC).The second step,to solve the proposed model quickly,the second order cone(SOC)algorithm is applied to transform the original models into mixed integer second order cone programming(SOCP)problem.The multi-stage economic and comprehensive reliability uncertainties measure distributions are obtained respectively and taken as the weights of the network tree.Then,the optimal planning scheme which is closest to the ideal network tree is searched by the minimum spanning tree theory in uncertain networks using the sinusoidal mutual entropy as a measure.Finally,the effectiveness of the proposed model is validated by the modified IEEE 33-node system Compared with the traditional planning model,the planning scheme can have long-term benefits by weighing the reliability and economy with large measures,and improve the objective function under the scene value in the traditional planning expectation model.The data underutilization caused by the large difference.Through the analysis of the performance of the algorithm,the model satisfies the convergence accuracy requirements and can significantly improve the computational efficiency by using the second-order cone relaxation.In addition,the IEEE-69 node system is used to verify that the model is still applicable to large power systems. |
