DataSheet1_A decision framework for orderly power utilization based on a computationally enhanced algorithm.PDF

In 2022, China faced unusually high temperatures, leading to a lack of hydropower in the southwest and increased power demand in the east. This incongruity exerted substantial strain on the power system. To tackle this, a structured method called orderly power utilization (OPU) is suggested as an effective approach to manage short-term power shortages and prevent recurring blackouts. However, typical OPU strategies tend to overlook the principles of fairness, openness, and justice (OEJ), potentially causing problems for various users, especially major industries. Herein, we introduce a comprehensive OPU framework. According to the demand difference in OPU plans in different periods, the optimization cycle is divided into several intervals to achieve computational enhancement. Furthermore, in the interest of judiciously managing the manifold OPU resources characterized by heterogeneous parameters, we introduce an aggregated operational model underpinned by the formalism of zonotopic sets. Numerical simulation results indicate the great potential of the proposed method to solve power shortage problems while upholding the imperatives of OEJ.2022年，中国遭遇异常高温天气，引发西南地区水电供应不足、东部地区电力需求攀升，此种供需失衡给电力系统带来了巨大运行压力。为破解这一难题，一种名为有序用电（orderly power utilization, OPU）的结构化管控方法被提出，作为应对短期电力短缺、防范停电事故反复发生的有效手段。然而，传统有序用电策略往往忽视公平、公开、公正（fairness, openness, and justice, OEJ）三大原则，可能给各类用户尤其是大型工业企业带来诸多困扰。为此，本文提出一套完整的有序用电框架：针对不同时段有序用电方案的需求差异，将优化周期划分为多个子区间以提升计算效率；此外，为合理管控参数异构的多类有序用电资源，本文提出一种基于zonotopic集（zonotopic sets）形式化框架的聚合运行模型。数值仿真结果表明，所提方法在解决电力短缺问题的同时，能够切实恪守公平、公开、公正原则，具备良好的应用前景。