APLUS Energy Investment Technology Consultancy. Short-term and mid-term price forecasting in Turkey Istanbul Energy Day September 08, 2015

Transcription

1 APLUS Energy Investment Technology Consultancy Short-term and mid-term price forecasting in Turkey Istanbul Energy Day September 08, 2015

2 CONTENT 1) FACTORS EFFECTING DAY AHEAD MARKET PRICE 2) SHORT & MID- TERM PRICE FORECAST METHODS 3) RESULTS

3 FACTORS AFFECTING THE DAY AHEAD MARKET PRICE Three main factors affecting the DAMP (Day Ahead Market Price) has been noted as; Generation from Thermal Power Plants Availability of Thermal Power Plants Natural Gas Prices Factors affecting the Generation from Thermal Power Plants are listed below Electricity Demand o Economic developments o Temperature effect Generation from Hydropower Plants o Power plants to be commissioned o Rainfall (possible drought seasons) Generation from Wind Power Plants o Power plants to be commissioned o Wind availability & temperature 3

4 FACTORS AFFECTING THE DAY AHEAD MARKET PRICE Factors affecting the Availability of Thermal Power Plants are Power plants to be commissioned Temperature Seasonality of maintenance periods Factors affecting the Natural Gas Prices are Brent oil prices USD exchange rate Political matters (election schedule and etc.) Gas supply issues (political and/or technical) 4

5 UNCERTAINTY OF MARKET PRICES 2014 started with low precipitation rates, even explained as severely dry by the Turkish State Meteorological Service but the overall year stayed within the average precipitation rates. It is though, difficult to predict the same for year The unpredictable nature of the meteorological conditions make forecasting efforts for renewable generation (especially hydropower generation) more difficult, leading to a higher uncertainty in price forecasts. Although the year 2014 stayed within the average precipitation rates, the drought season in winter months resulted in a significant decrease in hydro generation. The hydro capacity factor in 2014 was 39% lower than the capacity factor in % 60% 50% 40% 30% 20% 10% 0% January February March April May Hydro Capacity Factor (%) June July August September October November December Source:

6 UNCERTAINTY OF MARKET PRICES Can peak-demand reach (or exceed) 41,000 MW (act.43,289 MW) level due to above-normal temperatures in 2015 summer? Columbia University s International Research Institute for Climate and Society (IRI) predicts that Turkey will experience above-normal temperatures in 2015 summer and indicates the probability of this case as 70%. A possible natural gas crisis in winter months due to low temperature? There are no forecasts available until December 2015, therefore the uncertainty of a natural gas supply crisis is high, but the expectation in the market is high. Kaynak: 6

7 UNCERTAINTY OF MARKET PRICES A possible increase in price of natural gas in 2015? BOTAŞ gas sales tariff sits around 322 USD/tcm including the special consumption tax. Falling oil prices, a new agreement with Russia s Gazprom (on February 26, 2015) to cut down the gas price by 10.25% indicate a possible decrease in the gas tariffs. However, since BOTAŞ is planning to recover its loss in previous years and pay back some of its debt, the gas pipeline company is not eager to provide any discount on the natural gas price. BOTAŞ is also suffering from a sharp increase in exchange rates in favor of US dollar, which sits at a rate of 3.03 against the Turkish lira, adding to the reasons why BOTAŞ is not willing to decrease its tariffs. USD/1,000 scm Russian Gas Price at German Border 300 jan.13 feb.13 mar.13 apr.13 mai.13 jun.13 jul.13 aug.13 sep.13 okt.13 nov.13 des.13 jan.14 feb.14 mar.14 apr.14 mai.14 jun.14 jul.14 aug.14 sep.14 okt.14 nov.14 des.14 jan.15 Source: Months 7

8 UNCERTAINTY OF MARKET PRICES Can there be a delay or earlier-than-expected commissioning in the new power plant investments in Turkish energy market? The installed capacity development is a critical factor when providing price projections. Any delay in commissioning date of a large-scale power plant can cause further uncertainty in price analysis. Likewise, any power plant becoming operational earlier than its planned commissioning date can affect prices. Such cases were experienced when RWE s Denizli power plant s commissioning was delayed for some months, leading to a higher error rate in price projections. On the contrary, İzdemir Enerji s Aliağa coal-fired power plant was commissioned earlier than expected. 8

9 FACTORS AFFECTING THE DAY AHEAD MARKET PRICE Similar examples affecting the DAMP are illustrated below: Parameter Temperature in Winter* Factors Thermal Generation Thermal Availability Natural Gas Price DAMP Temperature in Summer* Rainfall New Investments Natural Gas Price Increase Economic Developments * Temperature difference compared to season normal averages 9

10 CONTENT 1) FACTORS EFFECTING DAY AHEAD MARKET PRICE 2) PRICE FORECAST METHODS 3) RESULTS

11 PRICE FORECAST MODELS There are numerous methods for Electricity Price Forecast Modelling. A fundamental model is the simulation of a spot market which works if there is sufficient, accurate and continuous data source. Less Than 1 Month Fundamental Models Statistical Models More Than 1 Month 11

12 FUNDAMENTAL MODEL - PRICE FORECASTING METHODOLOGY The methodology of the long term electricity price forecasting study has a complex and detailed structure Includes various factors ranging from features of power plants to macroeconomic variables

13 SHORT TERM PRICE FORECASTING APLUS Enerji provides short term price forecasts by using three different methods Artificial Neural Networks SARIMA (Seasonal ARIMA) Expert System Delta Model

14 COMPARISON OF FUNDAMENTAL MARKET MODEL vs. SHORT TERM FUNDAMENTAL MARKET MODEL SHORT TERM FORECAST METHODS Provides forecasts for mid-long term Provides forecasts for short-term (<14 days) A comprehensive database and frequent update required Applicable for investment decision-making process and portfolio management Meteorological forecasts depend on the past years seasonality and subject to changes for a given year Long-term forecast of generation from renewable power plants is less reliable due to assumptions made Long term natural gas tariffs is lesspredictable Relies on data from past few days, in close relation with the data profile Applicable for short-term electricity trading activities Better meteorological forecasts used Short-term forecast of generation from renewable power plants more reliable since it is derived from realized data within few days Possible changes in natural gas tariffs is closely monitored

15 ELECTRICITY MARKET RISK MANAGEMENT A probabilistic price forecasting approach enable the companies to improve their competitiveness in energy trading activities, to limit the risks and thus maximize the profits. Vulnerability to Risks Uncertainty Risk Management Decision Support System Manual Entry Expert Experiences Automation Mathematical Models + Expert Experiences 15

16 ELECTRICITY MARKET RISK MANAGEMENT Monte Carlo simulator that allows the users to define and set intervals in the input parameters of a fundamental model and generate hourly probabilistic Price Forward Curve. The required inputs for the simulation are: Demand forecast Availability of thermal power plants Capacity factor of renewable power plants Hydrology (incoming water amount to hydro power plants) Natural gas price increase Commissioning dates of power plants Sufficient, Accurate and Continuous Data Flow (SACDF) Fundamental Model Monte Carlo Probabilistic Price Forward Curve 16

17 ELECTRICITY MARKET RISK MANAGEMENT The Monte Carlo simulation considers all inputs entered by the user. Then it runs at least 400 times and generate hourly probabilistic Price Forward Curve TL/MWh Hours Mean Lower Limit Upper Limit Actual 17

18 CONTENT 1) FACTORS EFFECTING DAY AHEAD MARKET PRICE 2) PRICE FORECAST METHODS 3) RESULTS

19 RESULTS A complete Price Forecasting and Probabilistic Forward Curve Approach Mitigate the risks stemming from: o Natural gas prices o Weather conditions o Maintenance cycle of power plants o Natural gas crisis during winter period o Change in electricity demand Help in determining the true hedging strategy. o Bilateral Agreements (OTC) vs. Spot Market Allows establishing the optimal portfolio which drives through profit maximization 19

20 CONTENT

21 CONTACT Süleyman Seba Caddesi, BJK Plaza A-Blok Kat 1 Beşiktaş/İstanbul Tel: Fax: info@aplusenerji.com.tr