Potential scales of structural transformation of the Russian electric power system based on low-carbon distributed generation

A. Khorshev, I. Erokhina, F. Veselov
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引用次数: 1

Abstract

This article considers conditions and scenarios of transformation of the traditional structure of generating capacity in the Russian electric power system in the next 10-15 years considering the mass decommissioning of operating thermal power plants (TPPs) and active development of low-carbon distributed generation (DG) technologies. For this purpose, the ultimate development potential of Russia's key distributed cogeneration technology was assessed, taking into account the forecast of capacity balance situation in the national electric power system. In addition to it, the possible scales of the involvement of renewable power (RES) plants, as well as the potential impact of consumer’s demand response (DR) programs to replace large-scale generating facilities are considered.
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基于低碳分布式发电的俄罗斯电力系统结构转型的潜在规模
本文考虑了未来10-15年俄罗斯电力系统传统发电能力结构转型的条件和情景,考虑到运行中的火电厂(TPP)的大规模退役和低碳分布式发电(DG)技术的积极发展。为此,考虑到对国家电力系统容量平衡情况的预测,评估了俄罗斯关键分布式热电联产技术的最终发展潜力。除此之外,还考虑了可再生能源(RES)发电厂参与的可能规模,以及消费者需求响应(DR)计划取代大型发电设施的潜在影响。
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来源期刊
Advances in Systems Science and Applications
Advances in Systems Science and Applications Engineering-Engineering (all)
CiteScore
1.20
自引率
0.00%
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0
期刊介绍: Advances in Systems Science and Applications (ASSA) is an international peer-reviewed open-source online academic journal. Its scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome. ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public governance, finance, and many others.
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