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

Содержание

1. The Day-Ahead Energy Market Forecasting in Russian Federation: a Case-Study of
2. Introduction. Russian Reforms of Electricity MarketVertically Integrated
3. Introduction. The Structure of Electricity MarketWholesale electricity
4. The Price and Quantity Forecasting at DAM
5. The Data (14.09.2007-31.12.2015, 3025 obs.)
6. High volatility.Spikes.Autocorrelation.Seasonality.The Electricity Price Features
7. Regressors:t - time;
8. Pearson Criterion:The Normal Distribution:
9. The Distributed Lagged Model. Koyck Lag StructureThe
10. The Daily Quantity Forecasting at DAMThe Modelhere
11. The Hourly Price Forecasting at DAM MA(3): MA(5):Electricity Price in 2010, Fact and Forecast
12. Extrapolation Based on the Maximum Likeness ModelInitial
13. Optimal Solution of the Maximum Likeness Method
14. Danke für die Aufmerksamkeit!
15. Скачать презентанцию

Introduction. Russian Reforms of Electricity MarketVertically Integrated Monopoly (Before 2003)Competitive Unbundled Structure (From 2003)Competitive Generation:Territorial Generating Companies.Wholesale Generating Companies.RosAtom (Nuclear Plants).RusHydro (Hydro Plants).Transmission:Government-Granted «Regulated» Transmission MonopolyCompetitive Distribution and Salea)

Главная
Разное
The Day-Ahead Energy Market Forecasting in Russian Federation: a Case-Study of

Слайды и текст этой презентации

Слайд 1The Day-Ahead Energy Market Forecasting in Russian Federation: a Case-Study of

Siberia
Alexander Filatov
(Irkutsk State University, Far East Federal University, alexander.filatov@gmail.com)
Evgenya

Smirnova
(Irkutsk State University, smirnovevgen-91@mail.ru)

The Institute for East and Southeast European Studies, Regensburg, 5-th of April, 2016

The Day-Ahead Energy Market Forecasting in Russian Federation: a Case-Study of Siberia Alexander Filatov(Irkutsk State University, Far

Слайд 2Introduction. Russian Reforms of Electricity Market
Vertically Integrated Monopoly (Before 2003)
Competitive

Unbundled Structure (From 2003)

Competitive Generation:
Territorial Generating Companies.
Wholesale Generating Companies.
RosAtom (Nuclear

Plants).
RusHydro (Hydro Plants).

Transmission:
Government-Granted «Regulated» Transmission Monopoly

Competitive Distribution and Sale

a) b)

Introduction. Russian Reforms of Electricity MarketVertically Integrated Monopoly (Before 2003)Competitive Unbundled Structure (From 2003)Competitive Generation:Territorial Generating Companies.Wholesale

Слайд 3Introduction. The Structure of Electricity Market
Wholesale electricity and power market
Retail
DAM
BM
BCM
Popu-lation
Plants

and
other consumers
DAM – Day-Ahead Market
BCM – Bilateral Contract Market
BM –

Balancing Market

Introduction. The Structure of Electricity MarketWholesale electricity and power marketRetailDAMBMBCMPopu-lationPlants andother consumersDAM – Day-Ahead MarketBCM – Bilateral

Слайд 4The Price and Quantity Forecasting at DAM Provides:
The effective regimes

of the power plants work.
The Improvement of the generating companies

business planning.
The best option choice between trade operations at DAM, long-term bilateral contracts, and forward contracts that allow risk hedging.

Introduction. Auction Clearing

The Price and Quantity Forecasting at DAM Provides:The effective regimes of the power plants work.The Improvement of

Слайд 5The Data (14.09.2007-31.12.2015, 3025 obs.)

Слайд 6High volatility.
Spikes.
Autocorrelation.
Seasonality.
The Electricity Price Features

Слайд 7
Regressors:
t - time;
-

dummies for days of week; - dummy

for holidays;
- share of the working turbines at Sayano-Shushenskaya power station
- average day temperature; - light day duration;
- oil and natural gas prices;
- dollar and euro exchange rates;
- GDP of Russia
The Regression Model:

The Autoregression Model AR(1):

The Daily Price Forecasting at DAM

Regressors:t - time; - dummies for days of week;

Слайд 8Pearson Criterion:
The Normal Distribution:
=

225,76 >> = 33,41.
The

Logistic Distribution:
= 77,73 > = 33, 41.

The Distribution of Errors

Pearson Criterion:The Normal Distribution: = 225,76 >>

Слайд 9The Distributed Lagged Model. Koyck Lag Structure
The general distributed lagged

model:

Let

, 0 < λ < 1.
Then:

The final model: ,
Stage 1. Elimination of trend, seasonality and real factors except price of natural gas

Stage 2. Koyck lag structure for the price of natural gas.

Слайд 10The Daily Quantity Forecasting at DAM
The Model

here

– dummies for the half-year

– DAM price.

Quantity dynamics at DAM

Logistic function for the long-term forecast of the DAM quantities:

The Daily Quantity Forecasting at DAMThe Modelhere – dummies for the half-year

Слайд 11The Hourly Price Forecasting at DAM

MA(3):

MA(5):
Electricity Price in

2010, Fact and Forecast

Слайд 12Extrapolation Based on the Maximum Likeness Model
Initial time series:
The extrapolation

for the period
The initial vector:
The likeness measure:
The likeness function:
The maximization:

:
Extrapolation: ,
Error: ;

Extrapolation Based on the Maximum Likeness ModelInitial time series:The extrapolation for the periodThe initial vector:The likeness measure:The

Слайд 13Optimal Solution of the Maximum Likeness Method

Слайд 14Danke für die Aufmerksamkeit!

Скачать презентацию

Разделы презентаций