Suzhou Electric Appliance Research Institute
期刊號: CN32-1800/TM| ISSN1007-3175

SUBSCRIPTION MANAGEMENT

發(fā)行征訂

首頁 >> 發(fā)行征訂 >> 征訂方式

基于改進(jìn)DBO算法的儲能容量配置優(yōu)化研究

來源:電工電氣發(fā)布時間:2026-01-04 15:04瀏覽次數(shù):9
基于改進(jìn)DBO算法的儲能容量配置優(yōu)化研究
 
王崎1 ,楊雯2
(1 上海電力大學(xué) 經(jīng)濟(jì)與管理學(xué)院,上海 201306; 2 國網(wǎng)上海市電力公司長興供電公司,上海 201913)
 
    摘 要 :風(fēng)光互補(bǔ)微電網(wǎng)能夠提升可再生能源利用率,保障配電網(wǎng)運(yùn)行穩(wěn)定,然而其容量配置優(yōu)化通常涉及高維非線性約束,求解難度較大。構(gòu)建了以全生命周期成本最優(yōu)為目標(biāo)的風(fēng)光混合儲能微電網(wǎng)容量配置模型,并引入改進(jìn)蜣螂優(yōu)化算法 (DBO) 進(jìn)行求解,通過慣性權(quán)重因子和動態(tài)邊界收縮機(jī)制的協(xié)同作用,提升了在復(fù)雜約束下的搜索精度與收斂性能。仿真結(jié)果表明,所提方法能夠在典型日場景下有效降低系統(tǒng)經(jīng)濟(jì)成本,并在不同季節(jié)性工況下保持較高的供電可靠性與運(yùn)行穩(wěn)定性。基于改進(jìn)DBO的配 置方案為風(fēng)光儲能微電網(wǎng)的工程應(yīng)用提供了可行的技術(shù)路徑,未來可進(jìn)一步拓展至更大規(guī)模多能互補(bǔ)系 統(tǒng)并結(jié)合實(shí)際運(yùn)行需求完善動態(tài)約束設(shè)計(jì)。
    關(guān)鍵詞 : 改進(jìn)蜣螂優(yōu)化算法 ;風(fēng)光混合儲能 ;容量配置 ;微電網(wǎng) ;全生命周期成本
    中圖分類號 :TM715 ;TM734     文獻(xiàn)標(biāo)識碼 :A     文章編號 :1007-3175(2025)12-0016-06
 
Research on Optimization of Energy Storage Capacity Configuration Based on Improved DBO Algorithm
 
WANG Qi1 , YANG Wen2
(1 School of Economics and Management, Shanghai University of Electric Power, Shanghai 201306, China;
2 State Grid Shanghai Electric Power Co., Ltd. Changxing Power Supply Company, Shanghai 201913, China)
 
    Abstract: Wind-solar hybrid microgrids can enhance renewable energy utilization rates and ensure stable operation of distribution grids. However, optimizing their capacity configuration typically involves high-dimensional nonlinear constraints, making the solution process quite challenging. A capacity configuration model for wind-solar hybrid energy storage microgrids targeting the optimization of the whole-life cycle cost is constructed, and an improved dung beetle optimization (DBO) algorithm is introduced for solving. Through the synergistic effect of the inertia weight factor and the dynamic boundary contraction mechanism, the search accuracy and convergence performance under complex constraints are improved. Simulation results show that the proposed method can effectively reduce the system economic cost under typical daily scenarios and maintain high power supply reliability and operational stability under different seasonal operating conditions. The configuration scheme based on the improved DBO provides a feasible technical path for the engineering application of wind-solar energy storage microgrids. In the future, it can be further extended to larger-scale multi-energy complementary systems and the dynamic constraint design can be improved in combination with actual operational requirements.
    Key words: improved dung beetle optimization algorithm; wind-solar hybrid energy storage; capacity configuration; microgrid; whole-life cycle cost
 
參考文獻(xiàn)
[1] 林旗力,陳珍,王曉虎,等 . 基于“電-氫-電”過 程的規(guī)模化氫儲能經(jīng)濟(jì)性分析 [J]. 儲能科學(xué)與技術(shù), 2024,13(6) :2068-2077.
[2] 李偉,王師鵬,王英旭 . 考慮源荷匹配的含風(fēng)光能源微 電網(wǎng)儲能容量配置 [J]. 電工技術(shù),2025(10) :94-97.
[3] 王亞平,王雨田,李永毅,等 . 基于MOPSO算法的 風(fēng)光氫燃?xì)廨啓C(jī)互補(bǔ)系統(tǒng)優(yōu)化研究 [J]. 熱力發(fā)電, 2025,54(1) :35-45.
[4] 智筠貽,凌浩恕,吳昊,等 . 風(fēng)光儲多能互補(bǔ)能源系統(tǒng)容量配置優(yōu)化 [J]. 儲能科學(xué)與技術(shù),2024, 13(11) :3874-3888.
[5] 孔令國,范乃文,石振宇,等 . 風(fēng)-儲-氫-燃機(jī) 協(xié)同平抑功率波動運(yùn)行配置策略 [J]. 高電壓技術(shù), 2025,51(5) :2125-2136.
[6] 段晨,何鑫,何其新,等 . 基于改進(jìn)蜣螂優(yōu)化算法的微電網(wǎng)經(jīng)濟(jì)調(diào)度模型 [J]. 電工材料,2025(3) :63-67.
[7] 陳慶明,廖鴻飛,孫穎楷,等 . 改進(jìn)的蜣螂優(yōu)化算法及光伏發(fā)電功率預(yù)測應(yīng)用 [J]. 太陽能學(xué)報(bào),2025, 46(9) :445-454.
[8] 何思敏,李偉,劉立,等 . 基于隨機(jī)規(guī)劃的風(fēng)光柴儲容量配比優(yōu)化方法 [J] . 水電與新能源,2023, 37(2) :74-78.
[9] 許翔 . 風(fēng)電光伏并網(wǎng)儲能容量的配置優(yōu)化 [J]. 能源與 節(jié)能,2025(4) :4-6.
[10] 王劍波,陳會周,高運(yùn)動 . 考慮新能源消納的電網(wǎng)儲能容量配置研究 [J]. 微型電腦應(yīng)用,2025,41(3) : 105-109.
[11] 劉斌,羅異,孫周,等 . 基于用能自洽的高速服務(wù)區(qū)微網(wǎng)光儲組合優(yōu)化配置 [J]. 綜合智慧能源,2025, 47(2) :50-59.
[12] 陳慧麗 . 多策略增強(qiáng)型蜣螂優(yōu)化算法求解路徑規(guī)劃問題 [J]. 機(jī)械設(shè)計(jì)與制造,2025(5) :242-250.