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基于改进雪融优化算法的含可再生能源分布式电源和电动汽车充电站的并网型微电网中D-STATCOM最优集成
Optimal integration of D-STATCOMs in grid-tied microgrid consisting of renewable DGs and EV charging stations using improved snow ablation optimizer
| 作者 | Lohit Kumar Sahoo · Sivkumar Mishr · Subrat Kumar Dashb |
| 期刊 | Applied Energy |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 381 卷 |
| 技术分类 | 电动汽车驱动 |
| 技术标签 | 充电桩 微电网 |
| 相关度评分 | ★★★★ 4.0 / 5.0 |
| 关键词 | Improved snow ablation optimizer (i-SAO) is developed for addressing global optimization problems. |
语言:
中文摘要
本文针对并网型微电网(GTMG)中D-STATCOM的最优集成问题,提出了一种基于改进雪融优化器(i-SAO)的求解方法。通过改进的层次分析法(i-AHP),将平均有功功率损耗降低、系统平均最小电压提升、平均最大电压稳定性增强以及平均期望未供电能量(AEENS)减少等指标综合构成多目标函数。采用箱线图分析、Wilcoxon符号秩检验以及基于CEC 2020基准函数的收敛特性分析等严格的统计分析方法,验证了i-SAO算法的有效性与优越性。分析结果表明,在解决标准69节点配电系统中D-STATCOM与分布式电源(DG)的单独及协同最优配置以最小化有功功率损耗的问题时,i-SAO相较于其他七种竞争算法表现出更优的性能。随后,将所提方法应用于一个69节点的并网型微电网。不同场景下的计算结果表明,在D-STATCOM经过优化配置后,各项评估指标均得到显著改善。研究分析进一步揭示,D-STATCOM的最优配置使得并网型微电网在5年、10年和15年的规划周期内实现了更加安全、可靠、高效且经济的运行。
English Abstract
Abstract In this paper, the optimal integration of D-STATCOMs in a grid-tied microgrid (GTMG) is performed considering an improved snow ablation optimizer (i-SAO). The indices of average real power loss reduction, average minimum system voltage improvement, average maximum voltage stability enhancement and average expected energy not served (AEENS) reduction are combined through an improved analytic hierarchy process (i-AHP) for constituting the multi objective function. The feasibility of i-SAO is established through rigorous statistical analysis, including box plot analysis, Wilcoxon signed rank tests , and convergence characteristics analysis through CEC 2020 benchmark functions. The analysis reveals the superlative performance of i-SAO against seven other competitive algorithms in solving separate and simultaneous optimal allocation of D-STATCOMs and DGs to minimize real power loss of a standard 69 bus distribution system. The proposed methodology is then applied to a 69 bus GTMG. The results for different scenarios show appreciable attainment of considered indices in presence of optimally allocated D-STATCOMs. The analysis reveals the optimal allocation of D-STATCOMs resulted in a more secure, reliable, efficient and economic operation of a GTMG over a planning period of 5, 10 and 15 years.
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SunView 深度解读
该研究对阳光电源微电网解决方案具有重要参考价值。D-STATCOM优化配置技术可应用于ST系列储能变流器的无功补偿功能增强,结合SG逆变器构建的并网微电网系统,特别适用于含充电桩场景。改进的雪消融优化算法为iSolarCloud平台的智能调度算法提供创新思路,可优化分布式光伏、储能与充电站的协同控制策略,提升电压稳定性和降低网损。该多目标优化方法可集成到阳光电源微网能量管理系统,增强含大规模充电桩的工商业微网经济性与可靠性。