A Stochastic Model for Medium-Term Distribution System Planning Considering CO2 Emissions

2020 International Conference on Smart Energy Systems and Technologies (SEST) Pub Date : 2020-09-01 DOI:10.1109/SEST48500.2020.9203563

M. A. Mejia, Leonardo H. Macedo, G. Muñoz-Delgado, J. Contreras, A. Padilha-Feltrin

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引用次数: 4

Abstract

This paper presents a new two-stage stochastic mixed-integer linear programming model for the medium-term expansion planning of power distribution systems considering the uncertainty associated with renewable energy sources, demand, and energy prices at substations. Investment decisions comprise the installation of both 1) classical alternatives such as conductors, capacitor banks, and voltage regulators, and 2) modern alternatives such as renewable distributed generation and energy storage units. Moreover, unlike conventional planning models, the proposed approach includes a voltage-dependent load representation. The proposed model aims to find a planning strategy that minimizes the investment and operating costs while meeting network operational constraints and CO2 emissions requirements. Tests are carried out with a 69-node distribution system and the results demonstrate the effectiveness and applicability of this model as an effective means of promoting an efficient, sustainable, and environmentally-friendly network.

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考虑CO2排放的配电系统中期规划随机模型

考虑变电站可再生能源、需求和能源价格的不确定性，提出了一种新的配电系统中期扩容规划的两阶段随机混合整数线性规划模型。投资决策包括安装1)传统替代方案，如导体、电容器组和电压调节器，以及2)现代替代方案，如可再生分布式发电和储能单元。此外，与传统的规划模型不同，所提出的方法包括电压相关负载表示。提出的模型旨在找到一种规划策略，在满足网络运行限制和二氧化碳排放要求的同时，将投资和运营成本最小化。在69个节点的配电系统中进行了测试，结果表明该模型作为促进高效、可持续和环境友好型网络的有效手段的有效性和适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2020 International Conference on Smart Energy Systems and Technologies (SEST)

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