سیستم اطلاعات جغرافیایی برای مشخص کردن اماکن آینده ذخیره سازی انرژی
ترجمه نشده

سیستم اطلاعات جغرافیایی برای مشخص کردن اماکن آینده ذخیره سازی انرژی

عنوان فارسی مقاله: الگوریتم سیستم اطلاعات جغرافیایی (GIS) برای مشخص کردن اماکن آینده برای ذخیره سازی انرژی هیدروژنی پمپاژ شده
عنوان انگلیسی مقاله: Geographic information system algorithms to locate prospective sites for pumped hydro energy storage
مجله/کنفرانس: انرژی کاربردی – Applied Energy
رشته های تحصیلی مرتبط: مهندسی عمران، مهندسی انرژی
گرایش های تحصیلی مرتبط: سیستم های اطلاعات جغرافیایی
کلمات کلیدی فارسی: سیستم اطلاعات جغرافیایی، ذخیره انرژی، پمپ آبی
کلمات کلیدی انگلیسی: Geographic information system, Energy storage, Pumped hydro
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.apenergy.2018.03.177
دانشگاه: Australian National University – Australia
صفحات مقاله انگلیسی: 13
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2018
ایمپکت فاکتور: 8.301 در سال 2017
شاخص H_index: 140 در سال 2019
شاخص SJR: 3.162 در سال 2017
شناسه ISSN: 0306-2619
شاخص Quartile (چارک): Q1 در سال 2017
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
کد محصول: E9061
فهرست مطالب (انگلیسی)

Abstract

1- Introduction

2- Literature review

3- Models for potential PHES sites

4- GIS algorithms

5- Case study

6- Conclusion and future work

List of acronyms and abbreviations

Acknowledgements

Appendix A

Appendix B

References

بخشی از مقاله (انگلیسی)

Abstract

Pumped hydro energy storage is capable of large-scale energy time shifting and a range of ancillary services, which can facilitate high levels of photovoltaics and wind integration in electricity grids. This study aims to develop a series of advanced Geographic Information System algorithms to locate prospective sites for off-river pumped hydro across a large land area such as a state or a country. Two typical types of sites, dry-gully and turkey’s nest, are modelled and a sequence of Geographic Information System-based procedures are developed for an automated site search. A case study is conducted for South Australia, where 168 dry-gully sites and 22 turkey’s nest sites have been identified with a total water storage capacity of 441 gigalitres, equivalent to 276 gigawatt-hours of energy storage. This demonstrates the site searching algorithms can work efficiently in the identification of off-river pumped hydro sites, allowing high-resolution assessments of pumped hydro energy storage to be quickly conducted on a broad scale. The sensitivity analysis shows the significant influences of maximum dam wall heights on the number of sites and the total storage capacity. It is noted that the novel models developed in this study are also applicable to the deployments of other types of pumped hydro such as the locations of dry-gully and turkey’s nest sites adjacent to existing water bodies, old mining pits and oceans.

Introduction

Photovoltaics (PV) and wind constitute approximately half of the world’s new generation capacity installed in 2014–16. At the end of 2016, the global installations of PV and wind were beyond 300 gigawatts (GW) and 480 GW respectively [1,2]. Rapid growth of PV and wind energy in the electricity sector is expected to continue, driven by a broad range of issues associated with climate change, energy security and economics. High shares of intermittent PV and wind energy in electricity grids bring significant challenges to the economics and security of the system as is the case in South Australia (SA), where nearly half of the state's electricity production come from rooftop PV and wind farms [3]. SA has a low level of interconnection with the rest of the Australian National Electricity Market (NEM) and there is no existing hydroelectric or pumped hydro facility established within the region. This brings significant challenges to power system operation and the state's energy security due to supply intermittency and lack of sufficient inertial energy to support PV and wind electricity, especially in light of continuing rapid growth of PV and wind energy investment. In July 2016, when upgrades to the Heywood interconnector coincided with low wind generation at peak times, the average wholesale electricity prices in SA surged to $229/MWh (Australian dollars per megawatt-hour) with 3 extreme price events on 7, 13 and 14 July beyond $5000/MWh [4]. By contrast, the long-term average price in SA when the interconnector is available to import brown coal electricity from Victoria is $50/MWh. Additionally, a range of system events such as load shedding and islanding occasionally occurred in 2016–17 [5,6]. This included a state-wide blackout on 28 September 2016, when three 275 kilovolts (kV) backbone transmission lines were damaged by a major storm event [7].