Optimal Wind Bidding Strategies in Day-Ahead Markets

Gomes, Isaías L. R.; Pousinho, Hugo Miguel Inácio; Melício, Rui; Mendes, V.M.F.

doi:10.1007/978-3-319-31165-4_44

Cited by 2 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The procedure in the Iberian electricity market is to subject the producer to a price for the positive energy imbalance and another price for negative energy imbalance. In the Iberian electricity market the procedures for computing these prices are reported in [19]. The imbalance incurred by a power producer with a power plant k in a disjoint assessment in time t is stated as follows:…”

Section: Profit Descriptionmentioning

confidence: 99%

Stochastic Optimization for the Daily Joint Operation of Wind/PV and Energy Storage

Gomes

Pousinho

Melício

et al. 2017

IFIP Advances in Information and Communication Technology

Self Cite

View full text Add to dashboard Cite

Abstract. This paper deals with the problem of optimal bidding in a day-ahead market of electricity for a power producer having joint operation of wind with photovoltaic power systems and storage of energy. Uncertainty, not only on electricity market prices, but also on wind and photovoltaic powers, has to be faced in order to achieve optimal bidding. The problem is viewed as a sort of a two-stage stochastic optimization problem formulated by mix-integer linear programming. A case study with data from the Iberian Peninsula is presented and a comparison between joint and disjoint operations is discussed, allowing concluding that the joint operation attenuates the economic impact of disjoint operation volatility.

show abstract

Section: Profit Descriptionmentioning

confidence: 99%

Stochastic Optimization for the Daily Joint Operation of Wind/PV and Energy Storage

Gomes

Pousinho

Melício

et al. 2017

IFIP Advances in Information and Communication Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Approaches for producing generation schedules have been suggested [2][3][4]. Reference [2] proposed a bidding strategy where wind farms offer energy jointly compared with bidding strategies that consider each wind farm separately.…”

Section: Introductionmentioning

confidence: 99%

“…Reference [3] proposed a bidding strategy by using a non-cooperative game approach based on bi-level optimization with utility companies and power producers of thermal, solar, and wind power. Reference [4] proposed a bidding strategy based on a stochastic linear mathematical programming to maximize profit.…”

Section: Introductionmentioning

confidence: 99%

Scheduling method of wind power generation for electricity market using state-of-charge transition and forecast error

Kikuchi

Ito

Hayashi

2019

Journal of International Council on Electrical Engineering

View full text Add to dashboard Cite

This study focuses on the trade of power from wind power plants (WPPs) at an electricity market. To trade power, operators should produce generation schedules for bids and then supply the same amount of energy as the schedules. However, power from WPPs tends to fluctuate, which complicates scheduling. This paper proposes three scheduling methods with an energy storage system (ESS) to solve this problem. The first method considers state-of-charge (SOC) transition to maintain the appropriate SOC and minimize the imbalance between supplied and scheduled energy. The second and third methods consider SOC transition and forecast errors. The second method uses a linear regression model to estimate forecast errors. The third method adopts a bagged trees model, which is a machine learning method, to directly estimate the adjusted forecast data considering errors. Five patterns of the rated power of the ESS are assumed, and these three methods are simulated on each power. In comparison with the basic method, whose schedules are the same as the forecast, the third method can reduce 84% of the imbalance from the schedules when the rated power of the ESS is the minimum. The proposed methods help develop further correct and practical scheduling methods.

show abstract

Optimal Wind Bidding Strategies in Day-Ahead Markets

Cited by 2 publications

References 22 publications

Stochastic Optimization for the Daily Joint Operation of Wind/PV and Energy Storage

Stochastic Optimization for the Daily Joint Operation of Wind/PV and Energy Storage

Scheduling method of wind power generation for electricity market using state-of-charge transition and forecast error

Contact Info

Product

Resources

About