Models for Load and Price Formation in Deregulated Electricity Markets
Session
Computer Science and Communication Engineering
Description
In an electricity market, generation companies and electricity consumers need to meet in a marketplace to agree on the quantity of electricity to be produced and consumed and its relevant price. In the electricity sector, the decision-making process needs to be based on accurate forecasts of electricity demand and system load. For this reason, forecasting electricity demand and prices has emerged as one of the major research fields of interest in electricity markets. An underestimation of energy demand by a supplier may lead to higher operational costs because the additional demand needs to be met by procuring energy in the market, potentially at an unfavourable balancing price. Load forecasting is thus at the core of all the decisions made in energy markets as it is vitally important for determination of spot prices, production optimisation and cost-effective supply to all end users.
To participate in the market, a decision-maker needs an accurate estimate of how much energy is needed at a certain time. Supply and demand fluctuation, often related to changes in weather conditions, may cause energy prices to increase by a factor of ten or more during peak hours.
Over the past 20 years, the electricity industry has been subject to significant restructuring. The old concept of a centralised and monopolised industry, where electricity supply was seen as a public service, has been replaced by the idea that a competitive market is the most appropriate mechanism to supply energy to consumers while maintaining a high level of reliability and improving overall cost-effectiveness. The restructuring of electricity markets removes price controls and encourages entrance into a free market. Producers, retailers, and consumers are able to interact in a market where the common target is to maximise their profits. The process of deregulation and the introduction of competitive markets have totally reshaped the landscape of the traditionally monopolistic and state-controlled power sectors. Generation is deregulated as competition develops between a sufficient number of companies to promote an efficient wholesale electricity market. Load forecasting is a necessity for all consumers or retailers because actual consumption in real time may differ from expectations, implying that additional volumes may have to be sold or procured in short-term markets (e.g. balancing markets) at unfavourable prices, incurring an accounting or opportunity loss. Also, as generators are keen to optimise their hydropower and thermal power plants, variations in demand will alter spot prices and their optimum production plans. In light of the above, the purpose of this paper is to present a brief consideration of models and methods for load and price forecasting. It will provide sufficient grounds for proposing adequate models of load and price dynamics.
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-550-50-5
Location
UBT Kampus, Lipjan
Start Date
29-10-2022 12:00 AM
End Date
30-10-2022 12:00 AM
DOI
10.33107/ubt-ic.2022.274
Recommended Citation
Karapici, Valbona and Gjipali, Arsena, "Models for Load and Price Formation in Deregulated Electricity Markets" (2022). UBT International Conference. 282.
https://knowledgecenter.ubt-uni.net/conference/2022/all-events/282
Models for Load and Price Formation in Deregulated Electricity Markets
UBT Kampus, Lipjan
In an electricity market, generation companies and electricity consumers need to meet in a marketplace to agree on the quantity of electricity to be produced and consumed and its relevant price. In the electricity sector, the decision-making process needs to be based on accurate forecasts of electricity demand and system load. For this reason, forecasting electricity demand and prices has emerged as one of the major research fields of interest in electricity markets. An underestimation of energy demand by a supplier may lead to higher operational costs because the additional demand needs to be met by procuring energy in the market, potentially at an unfavourable balancing price. Load forecasting is thus at the core of all the decisions made in energy markets as it is vitally important for determination of spot prices, production optimisation and cost-effective supply to all end users.
To participate in the market, a decision-maker needs an accurate estimate of how much energy is needed at a certain time. Supply and demand fluctuation, often related to changes in weather conditions, may cause energy prices to increase by a factor of ten or more during peak hours.
Over the past 20 years, the electricity industry has been subject to significant restructuring. The old concept of a centralised and monopolised industry, where electricity supply was seen as a public service, has been replaced by the idea that a competitive market is the most appropriate mechanism to supply energy to consumers while maintaining a high level of reliability and improving overall cost-effectiveness. The restructuring of electricity markets removes price controls and encourages entrance into a free market. Producers, retailers, and consumers are able to interact in a market where the common target is to maximise their profits. The process of deregulation and the introduction of competitive markets have totally reshaped the landscape of the traditionally monopolistic and state-controlled power sectors. Generation is deregulated as competition develops between a sufficient number of companies to promote an efficient wholesale electricity market. Load forecasting is a necessity for all consumers or retailers because actual consumption in real time may differ from expectations, implying that additional volumes may have to be sold or procured in short-term markets (e.g. balancing markets) at unfavourable prices, incurring an accounting or opportunity loss. Also, as generators are keen to optimise their hydropower and thermal power plants, variations in demand will alter spot prices and their optimum production plans. In light of the above, the purpose of this paper is to present a brief consideration of models and methods for load and price forecasting. It will provide sufficient grounds for proposing adequate models of load and price dynamics.