Short-Term Trading for a Wind Power Producer

Abstract

This paper presents a technique to derive the best offering strategy for a wind power producer in an electricity market that includes various trading floors. Uncertainty pertaining to wind availability, market prices at the different trading stages, and balancing energy needs are properly taken into account. Risk on profit variability is suitably controlled at the cost of a small reduction in expected profit. The proposed technique translates into a linear programming problem of moderate size, which is readily solvable using commercially available software. A variety of numerical case studies demonstrate the interest and effectiveness of the proposed technique. Appropriate conclusions are duly drawn.

Optimal Bidding Strategies of Wind-Thermal Power Producers

“…The variable cost,  , is normally considered to be described by an exponential function. This exponential function is estimated by a piecewise linear formulation as in [2] stated as:…”

“…Mechanisms and policies provide subsidy and incentive for renewable energy conversion into electric energy [1], for instance, wind power conversion. But as the wind power technology matures and achieves breakeven costs, subsidy is due to be less significant and wind power conversion has to face the electricity markets for better profit [2]. Also, the incentives for wind power exploitation are feasible for low penetration levels but will become flawed as wind power integration rises [3].…”

Pool strategy of a producer coordinated with vehicle-to-grid services to maximize profitability

“…CVaR is included to control high trading risks which are arisen from uncertainties due to high wind penetration and EVs [9,24]. 6) The Load-side entities (LSEs) submit bid prices for energy and curtailment (to be elastic) to the day-ahead and real market but not strategically [6,[25][26].…”

Use of wind power forecasting in operational decisions.

“…This is framed as a profit-maximization problem with simple representations of uncertainties in wind power predictions and prices (intra-day and balancing). Morales et al [106] propose a stochastic programming model for wind power trading in multiple consecutive markets. Uncertainty in wind power and prices are represented as seasonal ARIMA models.…”