利用气象预报数据优化并网混合能源系统的规模

IF 1 4区 工程技术 Q4 INSTRUMENTS & INSTRUMENTATION
MAPAN Pub Date : 2024-07-06 DOI:10.1007/s12647-024-00758-x
Priyanka Anand, Bandana Sharma, Mohammad Rizwan
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引用次数: 0

摘要

对于努力实现可持续发展的国家来说,采用混合能源系统(HES)来确保获得清洁、可靠和具有成本效益的能源是必要的。通过利用来自预测的精确气象数据,混合能源系统可以变得更加精确。因此,本文的研究首先采用了四种机器学习方法,如高斯过程回归(GPR)、支持向量回归、极梯度提升和决策树,对一年内的气象数据进行每小时预测。结果表明,高斯过程回归的效果优于其他三种预测模型。因此,在确定 HES 的规模时,采用了从 GPR 获取的预测气象数据。调谐蜂群算法(TSA)是最近开发的一种方法,被用于对能够满足印度北方邦偏远地区能源需求的 HES 进行规模优化。在对 TSA、粒子群优化和和谐搜索进行比较研究后,TSA 被证明能产生更好的结果。此外,模拟结果表明,当预测数据成为系统规模优化的基础时,单位能源成本降低了 0.33%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Size Optimization of Grid-Tied Hybrid Energy System by Employing Forecasted Meteorological Data

Size Optimization of Grid-Tied Hybrid Energy System by Employing Forecasted Meteorological Data

Embracing hybrid energy systems (HES) to ensure access to clean, reliable, and cost-effective energy is necessary for nations that are striving for sustainable development. By leveraging precise meteorological data from forecasts, the HES can be rendered more accurate. Thus, firstly, the research presented here employed four machine learning approaches, such as Gaussian process regression (GPR), support vector regression, extreme gradient boosting, and decision trees, to carry out hourly forecasting of meteorological data over a year. The results obtained revealed that the GPR outperformed the other three forecasting models. For this reason, the forecasted meteorological data acquired from GPR is employed in the sizing of the HES. Tunicate swarm algorithm (TSA), a recently developed method, is applied to perform the size optimization of HES capable of meeting the energy necessities at remote sites in the Indian province of Uttar Pradesh. Following a comparative study of TSA, particle swarm optimization, and harmony search, TSA proved to yield a better outcome. Additionally, the simulation result showed a 0.33% cut in the per-unit cost of energy when forecasted data becomes the basis for the optimization of system size.

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来源期刊
MAPAN
MAPAN 工程技术-物理:应用
CiteScore
2.30
自引率
20.00%
发文量
91
审稿时长
3 months
期刊介绍: MAPAN-Journal Metrology Society of India is a quarterly publication. It is exclusively devoted to Metrology (Scientific, Industrial or Legal). It has been fulfilling an important need of Metrologists and particularly of quality practitioners by publishing exclusive articles on scientific, industrial and legal metrology. The journal publishes research communication or technical articles of current interest in measurement science; original work, tutorial or survey papers in any metrology related area; reviews and analytical studies in metrology; case studies on reliability, uncertainty in measurements; and reports and results of intercomparison and proficiency testing.
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