考虑 5G 基站自适应聚合的配电网络优化调度模型

IF 5 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC International Journal of Electrical Power & Energy Systems Pub Date : 2024-08-09 DOI:10.1016/j.ijepes.2024.110170
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引用次数: 0

摘要

利用 5G 基站储能(BSES)的可调度性,不仅能使移动网络运营商(MNO)获得额外收入,还能促进配电网(DN)中可再生能源的整合。然而,由于 BSES 和 DN 由不同的利益相关者拥有,因此将 BSES 整合到 DN 运营中会带来巨大挑战。为此,本文提出了一种 DN 优化调度模型,该模型通过合作博弈框架将 5G 基站(BS)的自适应聚合纳入其中。首先,对 BSES 的可调度性进行分析和建模。考虑到难以对每台设备进行最优调度,建立了 5G BS 的自适应聚合模型,将电耦合度和通信业务相似度作为综合指标。在此基础上,构建基于合作博弈的 DN 优化调度模型,将 5G BS 和 DN 的总运营成本作为特征函数。在优化过程中,5G BS 集群的数量和聚合结果会进行自适应调整。使用亲和传播(AP)聚类算法实现 5G BS 的优化聚类。此外,为了以更高的计算效率求解 DN 的优化调度模型,采用了粒子群优化算法与二阶锥编程(PSO-SOCP)相结合的方法。调度结束后,使用 Shapley 值法和等额利润法在移动网络运营商和配电系统运营商之间进行利益分配,以获得整个分配范围的结果。最后,进行了仿真,结果证明了所提方法的有效性。
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An optimal dispatch model for distribution network considering the adaptive aggregation of 5G base stations

Leveraging the dispatchability of 5G base station energy storage (BSES) not only enables the mobile network operator (MNO) to gain additional revenue, but also facilitates the integration of renewable energy sources in distribution network (DN). However, since BSES and DN are owned by different stakeholders, integrating BSES into DN operations poses significant challenges. In this regard, this paper proposes a DN optimal dispatch model that incorporates the adaptive aggregation of 5G base stations (BSs) through a cooperative game framework. Firstly, the dispatchability of BSESs is analyzed and modelled. Considering it is difficult to dispatch every single unit optimally, an adaptive aggregation model of 5G BSs is established, where the electrical coupling degree and the communication service similarity are taken as comprehensive metrics. On this basis, an optimal dispatch model of DN based on cooperative game is constructed, where the total operational costs of 5G BSs and DN are considered as the characteristic function. The number of 5G BS clusters and the aggregating results are adjusted adaptively during optimization. The optimal aggregation of 5G BSs is achieved using the Affinity Propagation (AP) clustering algorithm. Furthermore, to solve the optimal dispatch model of the DN with enhanced computational efficiency, the particle swarm optimization algorithm integrated with second-order cone programming (PSO-SOCP) is employed. After dispatching, the benefit allocation between MNO and distribution system operator (DSO) is conducted using the Shapley value method and the Equal Profit Method to obtain an entire range of allocation results. Finally, simulations are carried out with results proving the effectiveness of the proposed method.

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来源期刊
International Journal of Electrical Power & Energy Systems
International Journal of Electrical Power & Energy Systems 工程技术-工程:电子与电气
CiteScore
12.10
自引率
17.30%
发文量
1022
审稿时长
51 days
期刊介绍: The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces. As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.
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