Journal Article10.55959/msu0579-9414.5.78.2.4
Resources availability for solar microgeneration and its economic efficiency in the regions of russia
S. V. Kiseleva
- 09 Jul 2023
TL;DR: In this paper , the authors presented and tested a methodology for assessing the performance and economic efficiency of network photovoltaic stations, depending on physical-geographical and socioeconomic factors.
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Abstract: Measures to support electricity generation at low-power plants using the renewable energy sources as well, which were introduced in the Russian Federation, actualized the task of assessing the effectiveness of such legislative initiatives. The paper presents and tests a methodology for assessing the performance and economic efficiency of network photovoltaic stations, depending on physical-geographical and socio-economic factors. The results of assessing the potential performance of stations in various regions of Russia, obtained on the basis of archives of data on incoming solar radiation for the period from 2010 to 2020, are presented with one hour resolution. It is shown that economic efficiency of Solar Microgeneration Stations (SMS) in the study areas varies widely depending on the combination of such factors as the amount of solar radiation, retail and wholesale electricity tariffs, and the regime of electricity consumption by SMS owners. Despite significant solar energy resources, the payback period of photovoltaic stations in the regions of Southern Siberia (Irkutsk, Ulan-Ude) turned out to be the longest among all areas under study because of the established tariffs for electricity sale and purchase. Optimal conditions for the operation of such stations are characteristic only for the regions of Russia that belong to non-price zones and territorially isolated energy systems of the wholesale market (Magadan and Kaliningrad regions, Kamchatka, Primorsky Krai), where high wholesale electricity prices make the payback expectable within the guaranteed life of the station equipment (20 years).
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References
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105
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56
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