Pricing fixed price electricity contracts in the Nordic region
(2018) FMS820 20181Mathematical Statistics
- Abstract
- In a competitive market like electricity retailing it is crucial for energy
providers to estimate risk and cost for ?xed price contracts in order to set
competitive but not unpro?table prices. This report calculate three price
components that covers the wholesale and retail costs. Pro?le price com-
ponent is the expected electricity load to the expected spot prices in every
hour in the delivery period. Correlation price component is added due to
the fact that we do not know the realized outcome of load and spot price,
but from historical data we see that they are highly correlated. The de-
pendence structure between load and spot causes a higher expected cost.
The third component is a risk premium that quanti?es the risk that the
... (More) - In a competitive market like electricity retailing it is crucial for energy
providers to estimate risk and cost for ?xed price contracts in order to set
competitive but not unpro?table prices. This report calculate three price
components that covers the wholesale and retail costs. Pro?le price com-
ponent is the expected electricity load to the expected spot prices in every
hour in the delivery period. Correlation price component is added due to
the fact that we do not know the realized outcome of load and spot price,
but from historical data we see that they are highly correlated. The de-
pendence structure between load and spot causes a higher expected cost.
The third component is a risk premium that quanti?es the risk that the
retailer relieves from the customer.
One retailers portfolio load and electricity spot price in south Sweden,
SE4, is modeled with autoregressive based models and simulated. De-
pending on a customer's risk exposure to the portfolio, this report also
calculate the three price components for individual customers. The time
series model approach was successful in capturing dependence in data.
The results also shows that it is possible to set the three price compo-
nents based on an individual customer's consumption behavior in an e?-
cient way. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8939485
- author
- Levin, Anton
- supervisor
- organization
- course
- FMS820 20181
- year
- 2018
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Fixed price contract, Electricity load, Electricity spot price, vector autoregressive model, RAROC, Pro?le price, Correlation price, Vol- ume risk
- language
- English
- id
- 8939485
- date added to LUP
- 2018-05-11 13:28:23
- date last changed
- 2018-05-11 13:28:23
@misc{8939485, abstract = {{In a competitive market like electricity retailing it is crucial for energy providers to estimate risk and cost for ?xed price contracts in order to set competitive but not unpro?table prices. This report calculate three price components that covers the wholesale and retail costs. Pro?le price com- ponent is the expected electricity load to the expected spot prices in every hour in the delivery period. Correlation price component is added due to the fact that we do not know the realized outcome of load and spot price, but from historical data we see that they are highly correlated. The de- pendence structure between load and spot causes a higher expected cost. The third component is a risk premium that quanti?es the risk that the retailer relieves from the customer. One retailers portfolio load and electricity spot price in south Sweden, SE4, is modeled with autoregressive based models and simulated. De- pending on a customer's risk exposure to the portfolio, this report also calculate the three price components for individual customers. The time series model approach was successful in capturing dependence in data. The results also shows that it is possible to set the three price compo- nents based on an individual customer's consumption behavior in an e?- cient way.}}, author = {{Levin, Anton}}, language = {{eng}}, note = {{Student Paper}}, title = {{Pricing fixed price electricity contracts in the Nordic region}}, year = {{2018}}, }