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Decentralized Autonomous Optimal Operation of Multi-Energy System with Multiple Community Integrated Energy Stations

机译:具有多个社区综合能源站的多能源系统的分散自主最优运行

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With large scale renewable generation integrated, future power system is confronted with huge pressure of renewable consumption. To solve the wind power curtailment problem brought by central district heating in north China, this paper proposed a novel architecture and decentralized dispatching framework for multi-energy system with multiple community integrated energy systems (CIES) connected via power distribution and existing heating networks. As load clusters and local operators, CIESs are modeled based on conventional heat exchange stations and distribution substations for adaption to existing central heating system. Besides, extra peak shaving equipment such as electric boilers and energy storage is applied to CIESs. A decentralized algorithm based on Analytic Target Cascading (ATC) is presented to solve the optimal dispatching problem by dividing the problem into subproblems of upper-level system and lower-level CIESs. They are optimized locally with exchange power coordination to obtain a final converged optimal operation plan for the whole system. Case study shows effectiveness of the proposed system architecture and dispatching framework on renewable energy consumption and system economic operation.
机译:随着大规模可再生能源发电的整合,未来的电力系统将面临巨大的可再生能源消费压力。为了解决华北中部地区集中供热带来的风电削减问题,本文提出了一种新的架构和分散式配电框架,用于通过配电和现有供热网络连接多个社区集成能源系统的多能源系统。作为负荷集群和本地运营商,CIES是基于常规热交换站和配电变电站进行建模的,以适应现有的中央供暖系统。此外,CIES还使用了额外的调峰设备,例如电锅炉和储能装置。提出了一种基于分析目标级联(ATC)的分散算法,通过将该问题分为上层系统和下层CIES的子问题来解决最优调度问题。通过交换电源协调对它们进行本地优化,以获得整个系统的最终融合最佳运行计划。案例研究表明,所提出的系统架构和调度框架对可再生能源消耗和系统经济运行的有效性。

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