Transmission Expansion Planning using Binary Differential Evolution considering forecasted solar Photovoltaic generation

被引:1
|
作者
Somchit, Siripat [1 ]
Chatthaworn, Rongrit [1 ]
机构
[1] Khon Kaen Univ, Dept Elect Engn, Fac Engn, Khon Kaen 40002, Thailand
关键词
Binary Differential Evolution; Long Short-Term Memory; Solar Photovoltaic; Transmission Expansion Planning; MODEL; AC;
D O I
10.1016/j.egyr.2023.05.176
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Transmission Expansion Planning (TEP) can be essentially affected by solar Photovoltaic (PV) penetration because its generation is uncertain depending on weather and the environment at a specific time. This uncertainty can impact transmission expansion planning because the uncertain generation of solar PV causes difficulty to expand transmission lines with secure system operations. The aim of the proposed TEP method is to construct transmission lines to handle the increase in solar PV sources and electricity demand while ensuring that the power system constraints are not violated. The goal of the objective function is to minimize the total cost of the system, which comprises both the investment cost and the operating cost of generation. Hourly resolution values of solar PV generation and electricity demand are considered in the planning. Moreover, to obtain accurate values of solar PV generation for planning a system with secure operations, this paper proposes a Long Short-Term Memory (LSTM) for forecasting solar PV generation. The Binary Differential Evolution (BDE) algorithm is applied to solve the TEP problem. The proposed TEP method is tested through an IEEE 24 bus test system. The results from the proposed method show that the obtained expansion plan provides the minimum total system cost without system violations. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:1101 / 1107
页数:7
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