面向可靠性提升的关联规则驱动下配电网投资规划优选模型与方法

随着清洁能源的接入、供需交互的加深,当前计及完备潮流方程与网络安全约束的投资规划优化模型在面对大量改造措施决策时,存在计算繁琐、收敛性差的问题。提出了一种基于改造措施与可靠性指标关联规则取代潮流与网络安全约束的配电网投资规划优选模型与方法,该模型中配电网可靠性指标与改造措施间的关联关系通过选择合适的机器学习算法实现。分析了可靠性与改造措施的关联规则,分别以可靠性提升最大和投资费用最少为目标建立基于关联规则驱动的配电网投资规划优选模型,考虑各类改造措施对配电网可靠性指标的提升效益,实现配电网投资规划方案优选。通过实例验证了所提投资规划优选优化模型和求解方法的快速性、可行性与有效性。

Optimization model and method of distribution network investment planning driven by correlation rules for reliability improvement

With the access of clean energy and the deepening of the interaction between supply and demand, the current investment planning optimization models with complete power flow equations and network security constraints have the problems of cumbersome calculation and poor convergence in the face of a large number of reconstruction measurements. An optimization model and method for distribution network investment planning is proposed based on the correlation rules between reconstruction measurements and reliability index instead of power flow and network security constraints. In this model, the correlation rules between the reliability index of distribution network and reconstruction measurements is realized by choosing appropriate machine learning algorithm. Based on the analysis of correlation rules between reliability and reconstruction measurements, the optimization model of distribution network investment planning driven by correlation rules is established with the objective of the maximum reliability improvement and the minimum investment cost respectively, and the improvement benefit of various reconstruction measurements to the reliability index of distribution network is considered to realize the optimized decision of distribution network investment planning scheme. An example is given to verify the feasibility and effectiveness of the proposed optimization model and solution method.