Mathematical model of power system management in conditions of a competitive wholesale electric power (capacity) market in Russia

Davidson, M. R.; Dogadushkina, Yu. V.; Kreines, E. M.; Novikova, N. M.; Селезнев, А. В.; Udal’tsov, Yu. A.; Shiryaeva, L. V.

doi:10.1134/s1064230709020087

Cited by 34 publications

(12 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most sources devoted to the determination of extremal node power in electric power systems assume that the power of all consumers is specified either by condition (4) or by condition (5). Node power maximization methods for these models are reviewed in subsections 3.2 and 3.3, respectively.…”

Section: Main Classes Of Modelsmentioning

confidence: 99%

“…Investigation of the limits on admissible variation of power generated or consumed by different elements in AC electric power systems plays an important role for operating reliability analysis of power systems [1,2], computation of optimal load distribution between power stations [3,4], and solution of pricing problems in power markets [5,6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mathematical methods for computing the extremal power values in the nodes of ac electric power systems

Bogdanov

2012

Comput Math Model

View full text Add to dashboard Cite

show abstract

Section: Main Classes Of Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mathematical methods for computing the extremal power values in the nodes of ac electric power systems

Bogdanov

2012

Comput Math Model

View full text Add to dashboard Cite

show abstract

“…The details of this approach can be found, e.g. in [5,16,26,30]. Computation of LMP prices requires that all market players submit to an ISO their bids for generation and load.…”

Section: Price Volatilitymentioning

confidence: 99%

“…The DayAhead Market is based on the locational marginal pricing, where the hourly prices on electricity are computed for more than 7000 nodes. The mathematical models of the current market, which is functioning since September 2006, and its two-sector predecessor are described in [5]. There are four hubs in the European zone of Russia: Center-Europe, Center-West, Volga and Urals.…”

Section: Electricity Market Of United Energy System Of Russiamentioning

confidence: 99%

Trading Hubs Construction for Electricity Markets

Borisovsky

Eremeev

Grinkevich³

et al. 2009

Optimization in the Energy Industry

View full text Add to dashboard Cite

In this chapter, we consider a problem of constructing trading hubs in the structure of the electricity wholesale markets. The nodes of a trading hub are used to calculate a reference price that can be employed by the market participants for different types of hedging. The need for such a reference price is due to considerable variability of energy prices at different nodes of the electricity grid at different periods of time. The hubs construction is viewed as a mathematical programming problem here. We discuss its connections with clustering problems, consider the heuristic algorithms of solution and indicate some complexity issues. The performance of algorithms is illustrated on the real-life data.

show abstract

“…We included into the model the following regressors (Davidson et al, 2009): trend (t), dummies for the days of week (z (1) -z (6) ) and holidays (z (7) ), the share of working turbines at SayanoShushenskaya power station (essential due to the 2009 year catastrophic accident) (z (8) ), average day temperature (x (1) ) and light day duration (x (2) ) (The Weather Schedule, 2015), adjusted oil (x (3) ) and natural gas (x (4) ) prices (Market and analytics "Finam", 2015), dollar (x (5) ) and euro (x (6) ) exchange rates (Central Bank of Russian Federation, 2015), Russian GDP (x (7) ) (Rosstat, 2015). Some other regressors were excluded from the model due to their insignificant impact on electricity prices.…”

Section: The Daily Equilibrium Price Forecasting At Dammentioning

confidence: 99%

The Day-ahead Energy Market Forecasting in Russian Federation: a Case Study of Siberia

Филатов¹,

Lisin²,

Смирнова³

2015

MJE

View full text Add to dashboard Cite

Recent reforms in Russian power industry and the wholesale electric power and capacity market construction put energy companies into the new competitive conditions. Due to these reforms, the issues of price and quantity forecasting at the dayahead market (DAM) gain special importance. Particularly, the extrapolated values of the prices and quantities at DAM are necessary for the regulator, and also for energy companies to work out the best market strategy.The current Russian wholesale electricity market represents a fundamentally new model of the electric power industry that functions on a competitive basis. The key role in the structure of the wholesale energy trading sector is played by the day-ahead electricity sector that provides up to the 80% of total electricity sales in the country. As a result of the auction clearing, the market price for all points in the supply of electricity is formed and the volume of the market is determined. There is also a need for forecasting the equilibrium price and quantity of electricity sales, which largely determine the strategies of generation companies from the perspective of the use of free electric powers. This paper proposes a method of construction of medium and long-term forecasting of the DAM's main characteristics. Our results that stem from the mathematical model and statistical data reveal the most significant factors and quantified their nature, their extent as well as their effect on the energy market of Siberia.

show abstract

Mathematical model of power system management in conditions of a competitive wholesale electric power (capacity) market in Russia

Cited by 34 publications

References 1 publication

Mathematical methods for computing the extremal power values in the nodes of ac electric power systems

Mathematical methods for computing the extremal power values in the nodes of ac electric power systems

Trading Hubs Construction for Electricity Markets

The Day-ahead Energy Market Forecasting in Russian Federation: a Case Study of Siberia

Contact Info

Product

Resources

About