在全球能源转型加速的背景下,新型电力系统作为实现“碳达峰、碳中和”目标的关键支撑,正成为科技攻关与创新的热点领域。本研究旨在构建一套高效、系统的新型电力系统科技攻关有效性评价体系,通过深入分析科技攻关、有效性的理论基础,识别了影响科技攻关有效性的关键因素及其作用机理,并基于层次分析法(AHP)和模糊综合评价法,构建了包含四个维度(计划制定、实施管理、成果产出、效果应用)及16项具体指标的评价体系。还提出了动态监测、绩效导向、风险预警、成功模式推广及人才培养等策略,以优化科技攻关资源配置,提升科技攻关效率和成果转化率。本研究为电力行业及其他领域的科技攻关有效性评价提供了理论参考和实践指导,助力国家能源转型和科技创新发展。In the context of accelerating global energy transformation, the new power system, as a key support to achieve the goals of “carbon peak and carbon neutrality”, is becoming a hot field of scientific and technological breakthroughs and innovation. This study aims to construct an efficient and systematic effectiveness evaluation system for scientific and technological breakthroughs in new power systems. Through in-depth analysis of the theoretical basis of scientific and technological breakthroughs and effectiveness, this study identifies the key factors affecting the effectiveness of scientific and technological breakthroughs and their action mechanisms. Based on the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method, an evaluation system consisting of four dimensions (plan formulation, implementation management, achievement output, and effect application) and 16 specific indicators is constructed. The study also proposes strategies such as dynamic monitoring, performance orientation, risk warning, promotion of successful models, and talent training to optimize the allocation of resources for scientific and technological breakthroughs and improve the efficiency of scientific and technological breakthroughs and the conversion rate of achievements. This research provides theoretical references and practical guidance for the effectiveness evaluation of scientific and technological breakthroughs in the power industry and other fields and helps national energy transformation and technological innovation development.
本文主要将通过梳理采购批次排程现有流程,定位当前业务痛点、堵点问题,结合业务目标、供应链控制塔理论、求解器等先进的数智化技术,开展批次智能排程模拟。电网企业采购体量庞大,传统的人工排程方式工作效率低下,批次智能排程应用求解器,通过输入约束条件求解出最优解,为决策的制定提供重要支撑,优化供应链计划管理和资源,提高供应链运营质效。This paper will primarily focus on streamlining the existing scheduling process for procurement batches, and identifying the current pain points and bottlenecks in the business operations. Combining business objectives, the theory of the supply chain control tower, solvers, and other advanced digital and intelligent technologies, it will conduct simulations for intelligent batch scheduling. Given the substantial procurement volume of power grid enterprises and the inefficiencies associated with traditional manual scheduling methods, the application of batch intelligent scheduling solvers can derive optimal solutions based on input constraints. This provides critical support for decision-making, optimizes supply chain planning and resource management, and enhances the overall quality and efficiency of supply chain operations.
本文将结合产品碳足迹、电力消耗、低碳产品占比、减碳技术应用占比、产品碳效比、能效等级和性能参数要求等指标构建产品低碳评价模型,运用基于特征的设计目录结构和模糊数学等知识,设计电力产品的低碳评价方案,全面量化评价产品的绿色低碳水平,为电力物资采购提供判断依据,深化绿色采购应用,助力链上企业绿色低碳发展。This paper will combine the product carbon footprint, power consumption, proportion of low carbon products, proportion of carbon reduction technology application, carbon efficiency ratio of products, energy efficiency level and performance parameter requirements and other indicators to build a product low carbon evaluation model. Using feature-based design directory structure and fuzzy mathematics knowledge, low carbon evaluation scheme of power products will be designed to comprehensively and quantitatively evaluate the green and low carbon level of products, providing a judgment basis for the procurement of power materials, deepening the application of green procurement, and helping the green and low-carbon development of enterprises on the chain.
本文将自然语言处理(NLP)、知识图谱、RPA等新技术与电网企业数字化转型过程中的实际业务场景融合,梳理数字助理在电力应急物资调配过程中的功能需求,厘清数字助理的研究内容。通过对电网供应链日常运营管理过程中产生的庞大文本数据的整合与利用,实现数字助理对电力领域俗称、用户意图的准确理解,进而及时响应用户需求,显著提高应急响应过程效率,助力提升供应链韧性。This paper integrates new technologies such as natural language processing (NLP), knowledge graph and RPA with actual working scenarios in the process of digital transformation of power grid enterprises, tease out the functional requirements of digital assistants in the process of electric power emergency supplies deployment, and clarifies the research content of digital assistants. Through the integration and utilization of the huge text data generated in the daily operation and management process of the power supply chain, the digital assistant can accurately understand the common name and user intention in the power field, and then respond to user needs in a timely manner, significantly improve the efficiency of the emergency response process, and help improve the resilience of the supply chain.
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