A hybrid approach based on IGDT–MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market. (July 2015)
- Record Type:
- Journal Article
- Title:
- A hybrid approach based on IGDT–MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market. (July 2015)
- Main Title:
- A hybrid approach based on IGDT–MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market
- Authors:
- Nojavan, Sayyad
Zare, Kazem
Ashpazi, Mohammad Azimi - Abstract:
- Highlights: A hybrid approach based on IGDT–MPSO is applied to solve the optimal bidding strategy. IGDT is used to model the optimal bidding strategy for price-taker generation station. The robustness/opportunity problems to delivering IGDT approach are solved using MPSO. The hybrid method based on IGDT–MPSO has a practical advantage over IGDT–MINLP method. Abstract: This paper considers a price-taker generation station producer that participates in a day-ahead market. The producer behaves as a price-taker participant in the day-ahead electricity market. In electricity market, the price-taker producer could develop bidding strategies to maximize own profits. While making optimal bidding strategy, the market price uncertainty needs to be considered as they have direct impact on the expected profit and bidding curves. In this paper, a hybrid approach based on information gap decision theory (IGDT) and modified particle swarm optimization (MPSO) is used to develop the optimal bidding strategy. Information gap decision theory is used to model the optimal bidding strategy problem. It assesses the robustness/opportunity of optimal bidding strategy in the face of the market price uncertainty while price-taker producer considers whether a decision risk-averse or risk-taking. The optimization problems to delivering IGDT approach are solved using MPSO. It is shown that risk-averse or risk-taking decisions might affect the expected profit and bidding curve to day-ahead electricityHighlights: A hybrid approach based on IGDT–MPSO is applied to solve the optimal bidding strategy. IGDT is used to model the optimal bidding strategy for price-taker generation station. The robustness/opportunity problems to delivering IGDT approach are solved using MPSO. The hybrid method based on IGDT–MPSO has a practical advantage over IGDT–MINLP method. Abstract: This paper considers a price-taker generation station producer that participates in a day-ahead market. The producer behaves as a price-taker participant in the day-ahead electricity market. In electricity market, the price-taker producer could develop bidding strategies to maximize own profits. While making optimal bidding strategy, the market price uncertainty needs to be considered as they have direct impact on the expected profit and bidding curves. In this paper, a hybrid approach based on information gap decision theory (IGDT) and modified particle swarm optimization (MPSO) is used to develop the optimal bidding strategy. Information gap decision theory is used to model the optimal bidding strategy problem. It assesses the robustness/opportunity of optimal bidding strategy in the face of the market price uncertainty while price-taker producer considers whether a decision risk-averse or risk-taking. The optimization problems to delivering IGDT approach are solved using MPSO. It is shown that risk-averse or risk-taking decisions might affect the expected profit and bidding curve to day-ahead electricity market. The IGDT–MPSO method is illustrated through a case study and compared to IGDT–MINLP method. … (more)
- Is Part Of:
- International journal of electrical power & energy systems. Volume 69(2015:Jul.)
- Journal:
- International journal of electrical power & energy systems
- Issue:
- Volume 69(2015:Jul.)
- Issue Display:
- Volume 69 (2015)
- Year:
- 2015
- Volume:
- 69
- Issue Sort Value:
- 2015-0069-0000-0000
- Page Start:
- 335
- Page End:
- 343
- Publication Date:
- 2015-07
- Subjects:
- Optimal bidding strategy -- Information gap decision theory (IGDT) -- Modified particle swarm optimization (MPSO) -- Market price uncertainty
Electrical engineering -- Periodicals
Electric power systems -- Periodicals
Électrotechnique -- Périodiques
Réseaux électriques (Énergie) -- Périodiques
Electric power systems
Electrical engineering
Periodicals
621.3 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01420615 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ijepes.2015.01.006 ↗
- Languages:
- English
- ISSNs:
- 0142-0615
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.220000
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