Научная статья на тему 'ОЦЕНКА ВЛИЯНИЯ ОПТИМАЛЬНОГО ПОВЕДЕНИЯ ТЕПЛОЭЛЕКТРОСТАНЦИЙ, ПРОИЗВОДЯЩИХ ЭЛЕКТРОЭНЕРГИЮ, НА ТАРИФ ЭЛЕКТРОЭНЕРГИИ В РА.'

ОЦЕНКА ВЛИЯНИЯ ОПТИМАЛЬНОГО ПОВЕДЕНИЯ ТЕПЛОЭЛЕКТРОСТАНЦИЙ, ПРОИЗВОДЯЩИХ ЭЛЕКТРОЭНЕРГИЮ, НА ТАРИФ ЭЛЕКТРОЭНЕРГИИ В РА. Текст научной статьи по специальности «Экономика и бизнес»

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Ключевые слова
ПРОИЗВОДСТВЕННАЯ СТАНЦИЯ / ТАРИФНАЯ МАРЖА / ОПТИМИЗАЦИОННАЯ МОДЕЛЬ / СРЕДНИЙ ТАРИФ НА ЭЛЕКТРОЭНЕРГИЮ / ОКОНЧАТЕЛЬНЫЙ СРЕДНИЙ РОЗНИЧНЫЙ ТАРИФ / PRODUCTION STATION / TARIFF MARGIN / OPTIMIZATION MODEL / AVERAGE ELECTRICITY TARIFF / FINAL AVERAGE RETAIL TARIFF

Аннотация научной статьи по экономике и бизнесу, автор научной работы — Барсегян Тагуи

Исследовано влияние оптимального поведения производящих станций на тарифную маржу и средний тариф на покупку электроэнергии. Во-первых, были оценены функции топливных расходов станций Еревана и Раздана в зависимости от объемов соответствующего производства, затем подсчитаны их среднемесячные оптимальные объемы посредством вариационных неравенств. Было оценено влияние общих расходов, необходимых для производства соответствующих станций, на средний тариф продаваемой производственными станциями электроэнергии. Было подсчитано влияние тарифной маржи на окончательный тариф электроэнергии и расчетная величина продажи электроэнергии. Согласно нашим оценкам, тарифная маржа меньше, чем фактическая стоимость, и в результате это снижает окончательный средний тариф на электроэнергию, продаваемую потребителям.

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A SSESSMENT OF THE IMPACT OF OPTIMAL BEHAVIOR OF THERMAL POWER GENERATING STATIONS ON THE ELECTRICITY TARIFF IN THE REPUBLIC OF ARMENIA

The influence of the optimal behavior of generating stations on the tariff margin and the average tariff for the purchase of electricity is studied. First, the functions of fuel consumption in Yerevan and Hrazdan generating stations were estimated depending on the volume of the corresponding production, then their average monthly optimal volumes were calculated using variational inequalities. The total costs required for production by the respective stations were estimated for the average tariff of electricity sold by the production stations. Then the impact of the average tariff on the tariff margin was determined. The impact of the tariff margin on the final electricity tariff and the estimated value of electricity sales were calculated. According to our estimates, the tariff margin is less than the actual cost, and, as a result, this reduces the final average tariff for electricity sold to consumers.

Текст научной работы на тему «ОЦЕНКА ВЛИЯНИЯ ОПТИМАЛЬНОГО ПОВЕДЕНИЯ ТЕПЛОЭЛЕКТРОСТАНЦИЙ, ПРОИЗВОДЯЩИХ ЭЛЕКТРОЭНЕРГИЮ, НА ТАРИФ ЭЛЕКТРОЭНЕРГИИ В РА.»

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11 Sb'u <Ö4< тшрЫ|ш1| hm2qbLnqnLf3jriL'Utibp, http://www.psrc.am/am/activities/annual-reports

12 https://www.microsoft.com/en-us/:

13 Sb'u Uuipni|ujiuti, t[bL|uipmt'übpc|.|imj[i 15шипш1|шршр[1 шргцпЛшфип t[ujpß[i i|hp|nLÔnLpjnL-liQ t[bL|inpmtljbpq|nujj|n JuJuiujljujpujpiJmli 2T.pujjnLj, CC ung|iiu[-intiinbuujljujtj L)ujjnLti qujp-qmgJujli h[iiJliuj[uliri.[iplibpp, Я-[ипш1|ш1| hnr]i|iuôtibpfi d"nqni[mônL 4(20), bpLimli[i «lilimli[iuj C|npiul|iug|i» JfigLuqqujjfili hmpujpbpnLpjnLlilibpfi hujJuj[umpmli, bp., 4(20), 2013, t2 116-120:

14 http://www.ena.am/Aboutlls.aspx7idH 3&lang=1

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15 http://ytpc.am/%d5%b0%d5%a1 %d5%b7%d5%be%d5%a5%d5%bf%d5%be%d5%b8%d6%82%d5%a 9%d 5%b5%d5%b8%d6%82%d5%b6/; https://www.raztes.am/arm/

16 Sb'u Voronin S., Partanen J., Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks, Energies 2013, 6, tg 58975920, Gao X., Gengfeng Li., Zhang X., An Iteration Method for Optimal Energy Flow of Combined Heating and Electricity System, Energy Internet (ICEI), IEEE International Conference on 2019, tg 328-332:

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18 http://www.psrc.am/am/sectors/electric/tariffs

20 Sb'u Angerhofer B.J., Angelides M.C., System Dynamics Modelling in Supply Chain Management: Research Review, 2000. Winter Simulation Conference Proceedings (Cat,

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Uiuu2|iti £iuj|ji hiuiiiuÖiujlT qliiuhiuini|hL t шртшг|.рпг[ L|iujiutilihp|"r bpluu-1ф St4-|i Li <piuqr|.iuli|i St4-|i L|nqiî|ig i|iunb|J"igh ôiufuu|i L|iufui|iuönL[ajnLliQ h ш diu ii| ш in urn fu luti iupiniur|.pnLtajiuli ôiui|iu|tihp|ig: П-|шлшр1)1|Ь[ bli i|iuQb[|ip|i ôiufuu|i Li iupiniur|.pnL|3jiuli ôiui|iu|ji ini|jiu|tihpli iuiîuiuL|ujIi ^тр^шдртС 2009-

bpliiuli|i St4-|i r}bii|pnLd L"-1 LlLuq-nLjtli lupryrulipp uiniugi[b[ t f)iuniuL|nL-uiuj|ili dnr}b[|i hiudiup.

С y = -0,0012 * (ft + 0,363 . Qy + 3,195 (6)

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Unqh|nLd r|.binbpd|iliiug|iiuj|i qnpôiuL||igli ш.1ф li2iuliiuL|iu|ji iupdt¡p 0,651: lirumuiuLi 2-md inpi|iuô bb iuliL|iufu i(ini(infuiuL|iuli|i Li hiuuiniumni.tj|i t i|ji6iu-L|iuli|iljbpp, npnlip piugiupÖiuL| iupdt¡pni[ dbô bli 2-|ng: 9-ôiuii|iuinL|bp 1-md libp-L|iujiugi[iuô t dnr}b[p liL|iupiuqpnrL фтХЩд^ш^, npb т.1ф 2Р24Ш& ьцшршрпф inbup: <binLiiupiup, bpLiiuli|i fit;4-|i i[iunb|jif2h ôwfuubpp piupöpiubrnd bli d|ib-^Li hiudiuii|iuiniuufbiiulj iuniui|b|iuqnLjtj lupdbp iupiniur}pnLpjiulj ôiui[iu|jig L|iufui|iuô, lujlirnhbinLi uL|urnJ bli tii|iuqhL:

LLrynLuiul) 2

bpbiubfi Stb-fi óiufuubp[i qtiuihiuipduih шргутЬрЬЬрр

R2 =0,651, F =73,158, Г-^шЬшЦшфтттЬ = 0,000

Фпфп[иш1|ш1|

bpluutifi ЙЬЧ bpliiutih ЙЬЧ**2 СшитштпЛ

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0,368 -0,0012 3,195

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t- фбш1|ш1ф 5,84 1,91

t - 4h6lul|lutinL 1|2шЪшЦш[|пП Lpj n Ltl

0,00 0,00 0,012

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21 Sb'u <Ö4< 1лшрЫ|ш1| hm2ilbini[nLp-jnLbbbp, http://www.psrc.am/am/activities/annual-reports:

CULPU3hL tJUn-U3nhra-3nKLLbn 129

<piuqqiuti|i StH-li hiudiup lluL^Luq.nLjtJ qtiiuhiuiniul|iutjtibpp uiniugi|bL bti Power db|anqni[ qtjiuhiuindiutj qbu|j)ni.d: lLpiniuqpni.|ajiuti &iui|iu|ji L|nnL|nn|xiLU-l|iuli|i qtjiuhiuiniul|iutjp li2LuliLul|LULh t t = 20,123, piupSp t tiiuli. qbinbpd|itjiu-g|nuj|i qnp&iul|g|i Lupct■bpp, 0,823, F = 400,1 (lurynLuiuLi 3): lijuuibif q&iuu|iuin-L)bp 2-rud <piuqqiuti|i StH-li 6iufuubp|i !|>ni.til|g|iiutj iu6nq f ui p in wqp mp-jui b &wi|iu|jig l|iufui|w&, L|iupb[|n t iibl|tiwpiutibL l|iujiuti|i uiup£>iui|npnLiilibp|i iIai2i|uj6nLfajujiJp U wpqjnLliwi|binnL|3jiuti giu&p iliul|wpqwl|ni|;

CH = 0,9013-QW* (7)

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Liryniuuil| 3

<puiqi}iuti[i St^-fi diufuubpli qtiuihuiipduiti lupiynihplibpp

R2 =0,823, F = 400,1, F-^uiliwlfUJtlinipjniti = 0,000

<t>ni|in|uwl|wti 9-npSwlilngtibp Uiniutir|.wpin 2br|ni.J t- i|]i6iul|iuti|i t - l[|l6lul|lutinL ti2iuti lu L| lu [|n n l|aj n lIi

<puiqr>uiti[i St«H 0,891 0,056 15,91 0,00

<UlUU1UlUinLll 0,9013 0,135 6,674 0,04

210 V 100

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22 Sb'u Nagurney A., Qiang Q., Fragile Networks: Identifying Vulnerabilities and Synergies in an Uncertain World, Newjersy, 2009, Aussel D., Gupta Rachana, Mehra A., Evolutionary Variational Inequality Formulation of the Generalized Nash Equilibrium Problem, Journal of Optimization Theory and Applications, 2016, tg 74-90:

23 Sb'u Bazar T., Lecture Notes on Non-Cooperative Game Theory, 2010, Javadi M., Marzband M. Domingues-Garcia J. I., Moghaddam M. M., Non-cooperative Game Theory Based Energy Management Systems for Energy District in the Retail Market Considering DER Uncertainties, the Institution of Engineering and Technology, 2016, tg 2999-3009::

130 PUTjPbP C^SC 2020.4

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<binliiupiup, <piuqqiuli|i L bpluutj|i StH-bpli hiudiup (8) fulir|.|ipp, plir|.-hiulirup wndiudp, L|nlIjbtilu hbinlijLU[ inbupp. Tjii|iuiniul|iuj|iti $nLtjl|g|W

(9)

U lu h Jaib lu ijiai L| n l Jb bp"

^ s "Jfli , (10)

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bpliiuli|i U <pwqqiuti|i StH-bpli hiudiup l|rulibtjiulip hbinlijiu[ i|iup|iiu-g|inll LUtlhLUL[LUULUpnLf3jnLtjQ.

(0,363 - 0,0024 . Qy - plVXQv - Qy ) + (0,303 * Q~°-109 ~pui){Qh - Qlf) > 0; (13)

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iniug|i J|i2|ilj iuduiul|iuli t[bL|lnplutlJbpq.|nluj|n LupinujqpnLpjnLljp, uijli t' 47,94

Sb'u Nagurney A., Qiang Q., Fragile Networks: Identifying Vulnerabilities and Synergies in an Uncertain World, ISBN: 978-0-470-50112-2, 2009, tg 146:

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<luiIlu5lujIi bppnpq fiLujiJV wlihpiud~b2in t qtiiuhwinbL wpuiujqpnq 1|wjluIi-tibp|i l|nqd|ig t|bl|Lnpiuttibpq|iiuj|i qbdiuti d|i2hb uiul|Luqti|i l|iufui|w&ni.|ajnLtjp q|iLnaipL|L[nq l|iujwtjtibp|i L|wnb|jif2h pbqhiutinLp &iufuu|ig: LLju qbaiprnd oqinui-qnp6i|b[ bb 2009-2018 fafa. miupbl|Lutj inL|jiu|tjbpp b l|iujiutitjbp|i l|nqd|ig l|lu-nbLhph inwpbl|iuti &iufuubpp:

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«Miiiuiti ilh2h^ uuil|iuq.[iti = -146,703 + 9,27 * In (Gtiqhuitinip duifuu): (14)

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lirynLUUll| 4

Q-tiduiti till £ fib uiuljuiqb[i U [ibq.hiubnip duifvufi qbiuhuiipifiub

ujpqjnibgbbpQ

R2 =0,459, F = 6,78, F-tyiuijujIjUJilinipjmb = 0,031

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<iuumiumniti -146,703 63,056 -2,327 0,048

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Uuil|uiqtiuijhíi lïuipdui = -0,033 * 4ütfmti_tfti2hÍJ-ululllu{lhi,,'2+1>167*

9Ли1ш1|_1$ti2fiti_uuiliuiq.fiti -0,202 +4,139 *х: (15)

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ТАГУ И БАРСЕГЯН

Преподаватель АГЭУ

Оценка влияния оптимального поведения теплоэлектростанций, производящих электроэнергию, на тариф электроэнергии в РА.- Исследовано влияние оптимального поведения производящих станций на тарифную маржу и средний тариф на покупку электроэнергии. Во-первых, были оценены функции топливных расходов станций Еревана и Раздана в зависимости от объемов соответствующего производства, затем подсчитаны их среднемесячные оптимальные объемы посредством вариационных неравенств. Было оценено влияние общих расходов, необходимых для производства соответствующих станций, на средний тариф продаваемой производственными станциями электроэнергии. Было подсчитано влияние тарифной маржи на окончательный тариф электроэнергии и расчетная величина продажи электроэнергии. Согласно нашим оценкам, тарифная маржа меньше, чем фактическая стоимость, и в результате это снижает окончательный средний тариф на электроэнергию, продаваемую потребителям.

Ключевые слова: производственная станция, тарифная маржа, оптимизационная модель, средний тариф на электроэнергию, окончательный средний розничный тариф. \Е1: 194, 043

TAGUHIBARSEGHYAN

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Lecturer at ASUE

Assessment of the Impact of Optimal Behavior of Thermal Power Generating Stations on the Electricity Tariff in the Republic of Armenia.- The influence of the optimal behavior of generating stations on the tariff margin and the average tariff for the purchase of electricity is studied. First, the functions of fuel consumption in Yerevan and Hrazdan generating stations were estimated depending on the volume of the corresponding production, then their average monthly optimal volumes were calculated using variational inequalities. The total costs required for production by the respective stations were estimated for the average tariff of electricity sold by the production stations. Then the impact of the average tariff on the tariff margin was determined. The impact of the tariff margin on the final electricity tariff and the estimated value of electricity sales were calculated. According to our estimates, the tariff margin is less than the actual cost, and, as a result, this reduces the final average tariff for electricity sold to consumers.

Key words: production station, tariff margin, optimization model, average electricity tariff, final average retail tariff. JEL: L94, Q43

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