Price spike forecasting in a competitive day-ahead energy market
Voronin, Sergey (2013-11-01)
Väitöskirja
Voronin, Sergey
01.11.2013
Lappeenranta University of Technology
Acta Universitatis Lappeenrantaensis
Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-265-462-5
https://urn.fi/URN:ISBN:978-952-265-462-5
Tiivistelmä
Electricity price forecasting has become an important area of research in the aftermath
of the worldwide deregulation of the power industry that launched competitive
electricity markets now embracing all market participants including generation and
retail companies, transmission network providers, and market managers.
Based on the needs of the market, a variety of approaches forecasting day-ahead
electricity prices have been proposed over the last decades. However, most of the
existing approaches are reasonably effective for normal range prices but disregard price
spike events, which are caused by a number of complex factors and occur during
periods of market stress.
In the early research, price spikes were truncated before application of the forecasting
model to reduce the influence of such observations on the estimation of the model
parameters; otherwise, a very large forecast error would be generated on price spike
occasions. Electricity price spikes, however, are significant for energy market
participants to stay competitive in a market. Accurate price spike forecasting is
important for generation companies to strategically bid into the market and to optimally
manage their assets; for retailer companies, since they cannot pass the spikes onto final
customers, and finally, for market managers to provide better management and planning
for the energy market.
This doctoral thesis aims at deriving a methodology able to accurately predict not only
the day-ahead electricity prices within the normal range but also the price spikes. The
Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and
its structure is studied in detail.
It is almost universally agreed in the forecasting literature that no single method is best
in every situation. Since the real-world problems are often complex in nature, no single
model is able to capture different patterns equally well. Therefore, a hybrid
methodology that enhances the modeling capabilities appears to be a possibly
productive strategy for practical use when electricity prices are predicted.
The price forecasting methodology is proposed through a hybrid model applied to the
price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select
the optimal input set of the explanatory variables.
The numerical studies show that the proposed methodology has more accurate behavior
than all other examined methods most recently applied to case studies of energy markets
in different countries. The obtained results can be considered as providing extensive and
useful information for participants of the day-ahead energy market, who have limited
and uncertain information for price prediction to set up an optimal short-term operation
portfolio.
Although the focus of this work is primarily on the Finnish price area of Nord Pool
Spot, given the result of this work, it is very likely that the same methodology will give
good results when forecasting the prices on energy markets of other countries.
of the worldwide deregulation of the power industry that launched competitive
electricity markets now embracing all market participants including generation and
retail companies, transmission network providers, and market managers.
Based on the needs of the market, a variety of approaches forecasting day-ahead
electricity prices have been proposed over the last decades. However, most of the
existing approaches are reasonably effective for normal range prices but disregard price
spike events, which are caused by a number of complex factors and occur during
periods of market stress.
In the early research, price spikes were truncated before application of the forecasting
model to reduce the influence of such observations on the estimation of the model
parameters; otherwise, a very large forecast error would be generated on price spike
occasions. Electricity price spikes, however, are significant for energy market
participants to stay competitive in a market. Accurate price spike forecasting is
important for generation companies to strategically bid into the market and to optimally
manage their assets; for retailer companies, since they cannot pass the spikes onto final
customers, and finally, for market managers to provide better management and planning
for the energy market.
This doctoral thesis aims at deriving a methodology able to accurately predict not only
the day-ahead electricity prices within the normal range but also the price spikes. The
Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and
its structure is studied in detail.
It is almost universally agreed in the forecasting literature that no single method is best
in every situation. Since the real-world problems are often complex in nature, no single
model is able to capture different patterns equally well. Therefore, a hybrid
methodology that enhances the modeling capabilities appears to be a possibly
productive strategy for practical use when electricity prices are predicted.
The price forecasting methodology is proposed through a hybrid model applied to the
price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select
the optimal input set of the explanatory variables.
The numerical studies show that the proposed methodology has more accurate behavior
than all other examined methods most recently applied to case studies of energy markets
in different countries. The obtained results can be considered as providing extensive and
useful information for participants of the day-ahead energy market, who have limited
and uncertain information for price prediction to set up an optimal short-term operation
portfolio.
Although the focus of this work is primarily on the Finnish price area of Nord Pool
Spot, given the result of this work, it is very likely that the same methodology will give
good results when forecasting the prices on energy markets of other countries.
Kokoelmat
- Väitöskirjat [1037]