Data processing as a critical part of GIS based mapping of renewable energy perspectives

Kargashin, Pavel; Prasolova, A.I.; Novakovskiy, B. A.; Rafikova, Yulia Yu.; Gorbunov, Roman; Gorbunova, Tatiana

doi:10.1051/matecconf/201817809004

Cited by 3 publications

(3 citation statements)

References 6 publications

(5 reference statements)

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“…[31]). The two final areas of interest that appeared in the review were the application of big data techniques to explore renewable energy potential [32] and the design and operation of heat networks [33].…”

Section: Big Data and Energy Research: The Status Quomentioning

confidence: 99%

Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art?

Bataille

Pye

et al. 2019

Applied Energy

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Energy economy models are central to decision making on energy and climate issues in the 21st century, such as informing the design of deep decarbonisation strategies under the Paris Agreement. Designing policies that are aimed at achieving such radical transitions in the energy system will require ever more in-depth modelling of end-use demand, efficiency and fuel switching, as well as an increasing need for regional, sectoral, and agent disaggregation to capture technological, jurisdictional and policy detail. Building and using these models entails complex trade-offs between the level of detail, the size of the system boundary, and the available computing resources. The availability of data to characterise key energy system sectors and interactions is also a key driver of model structure and parameterisation, and there are many blind spots and design compromises that are caused by data scarcity. We may soon, however, live in a world of data abundance, potentially enabling previously impossible levels of resolution and coverage in energy economy models. But while big data concepts and platforms have already begun to be used in a number of selected energy research applications, their potential to improve or even completely revolutionise energy economy modelling has been almost completely overlooked in the existing literature. In this paper, we explore the challenges and possibilities of this emerging frontier. We identify critical gaps and opportunities for the field, as well as developing foundational concepts for guiding the future application of big data to energy economy modelling, with reference to the existing literature on decision making under uncertainty, scenario analysis and the philosophy of science.

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Section: Big Data and Energy Research: The Status Quomentioning

confidence: 99%

Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art?

Bataille

Pye

et al. 2019

Applied Energy

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show abstract

“…При этом инвестиции в возобновляемую энергетику (ВЭ) достигли рекордного объема в 366 млрд долл. США, что на 6,5 % больше, чем годом ранее 2 Для использования ВИЭ в России чрезвычайно важна инвестиционная привлекательность проектов, а она обусловлена в энергетической сфере, как показывает международный опыт 5 , степенью риска данных проектов [1]. В значительной степени природно-ресурсные риски работы фотоэлектрических станций определяются изменчивостью поступления солнечной радиации и другими природно-климатическими особенностями территории размещения этих станций.…”

Section: Introductionunclassified

“…В значительной степени природно-ресурсные риски работы фотоэлектрических станций определяются изменчивостью поступления солнечной радиации и другими природно-климатическими особенностями территории размещения этих станций. В настоящее время методы геоинформатики активно используются при изучении потенциала солнечной энергии и оценке рисков для различных территорий 6 [2][3][4][5]. Геоинформационные системы (ГИС) открывают возможности для решения ряда важных задач, таких как визуализация ресурсов для расчета величин технического и экономического энергопотенциала по видам ВИЭ, анализ территорий по уровню обеспеченности ресурсами и возможности размещения на них объектов солнечной и ветровой энергетики применительно к разным масштабам территориальных исследований.…”

Section: Introductionunclassified

Assessment of the solar energy development role as a tool for the energy transition in Russia

Нефедова

Rafikova

2023

Vestn. Ross. univ. družby nar., Ser. Èkol. bezop. žiznedeât.

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Based on the characteristics of the current state of the use of renewable energy sources (RES) in the world and in Russia, the role of solar energy in solving one of the urgent problems of the development of modern society - energy transition to the use of low-carbon energy sources is considered. The volumes of electricity produced and the reduction of CO2 emissions at photovoltaic stations operating in the regions of Russia at the beginning of 2022 were evaluated and analyzed. The Republic of Kalmykia and Altai were singled out, which have the largest shares of solar electricity in the energy balances, 35.7 and 23.2%, respectively. The problems of assessing the natural resource risks of using solar resources in the Russian Federation in connection with the climatic zoning of the territory are considered. The authors propose a method for assessing the degree of risk of using solar resources based on calculating the characteristics of the variability of solar radiation on the earth’s surface, assessing and mapping the level of natural resource risks. The levels of resource risks in the development of solar energy for the Orenburg and Astrakhan regions, leaders in the development of solar energy in Russia, were assessed.

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Assessment of the Stability of Solar Energy Resources by Statistical and Geoinformation Methods

Нефедова

Rafikova

2022

Appl. Sol. Energy

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Data processing as a critical part of GIS based mapping of renewable energy perspectives

Cited by 3 publications

References 6 publications

Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art?

Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art?

Assessment of the solar energy development role as a tool for the energy transition in Russia

Assessment of the Stability of Solar Energy Resources by Statistical and Geoinformation Methods

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