基于用户画像与关联规则的全域电力资源调度算法

Global power resource scheduling algorithm based on user portrait and association rules

摘要:

为解决应用调度算法进行全域电力资源调度，资源剩余率依旧较高的问题，提出结合用户画像与关联规则的新型调度算法，实现全域电力资源的合理分配。运用双聚类算法，对整个调度区域内所有用户用电数据进行分析，构建电力用户画像从而描述用户用电个性化需求；以用户画像为基础，建立以满足用户需求为核心的全域资源分配模式；总结全域内资源调度子任务，计算不同子任务之间的支持度和置信度，结合关联规则实现子任务的分组；根据子任务组进行资源分域，在每个分域中设置二级调度中心，再与全域一级调度中心相连接，实现全域资源集中调度。实验结果表明，所提调度算法应用后，电力测试系统每日的全域资源剩余率出现了大幅降低，仅保持在12%左右。该算法具有较好的实际应用价值。

Abstract:

To solve the problem of high resource surplus rate in the application of scheduling algorithms for global power resource scheduling, a new scheduling algorithm combining user profiles and association rules is proposed to achieve reasonable allocation of global power resources. By using the dual clustering algorithm, the electricity consumption data of all users in the entire dispatch area is analyzed, and a power user profile is constructed to describe the personalized electricity consumption needs of users. Based on the user profiles, a global resource allocation model is established centered on meeting user needs. The resource scheduling subtasks are summarized within the entire domain, the support and confidence between different subtasks are calculated, and association rules are combined to achieve grouping of subtasks. The resources are divided into different domains according to the subtasks group. A secondary dispatching center is set up in each domain, and then is connected with the primary dispatching center in the whole domain to realize the centralized scheduling of resources in the whole domain. The experimental results show that after the application of the proposed scheduling algorithm, the daily global resource surplus rate of the power testing system has significantly decreased, only maintaining around 12%. This algorithm has good practical value.