A Multi-objective Transmission Expansion Model Considering Renewable Energy Resources for Alternating Current Power Systems

2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES) Pub Date : 2022-12-09 DOI:10.1109/SPIES55999.2022.10082708

Wenhui Pei, Xuexia Zhang, Chuanyu Liu

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Abstract

A new Transmission Network Expansion Planning (TEP) problem based on alternating current (AC) network aiming at optimizing system operation is proposed in this paper. TEP based on AC model (AC-TEP) can provide more accurate planning results compared to that based on direct current model (DC-TEP). In this paper, a multi-objective AC-TEP issue is analyzed dealing with investment problem and uncertainty problem. A multi-objective evolutionary algorithm (MOEA) based on an enhanced inverted generational distance indicator (AR-MOEA), is used to handle the multi-objective TEP. In this paper, IEEE-24 bus test system and China 52-bus system are utilized to perform the numerical analysis. To prove the superiority of AR-MOEA algorithm, the obtained results are compared with that of MOEA based on decomposition (MOEA/D). The results confirm the superior performance of AR-MOEA for solving multi-objective TEP problem, and validate the applicability and capability of AC-TEP model to cope with middle and larger power systems.

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考虑可再生能源的交流电力系统多目标输电扩展模型

提出了一种新的以优化系统运行为目标的基于交流网络的输电网络扩展规划问题。与直流模型(DC-TEP)相比，基于交流模型(AC-TEP)的TEP可以提供更准确的规划结果。本文分析了一个涉及投资问题和不确定性问题的多目标AC-TEP问题。采用一种基于增强型倒代距离指示器的多目标进化算法(MOEA)来处理多目标TEP。本文利用IEEE-24总线测试系统和中国52总线系统进行数值分析。为了证明AR-MOEA算法的优越性，将得到的结果与基于分解的MOEA算法(MOEA/D)进行了比较。结果证实了AR-MOEA在解决多目标TEP问题上的优越性能，验证了AC-TEP模型在应对中大型电力系统中的适用性和能力。

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2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)

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