Risk-Constrained Bidding Strategy for a Joint Operation of Wind Power and CAES Aggregators

Abstract

This paper proposes a coordinated strategy of a hybrid power plant (HPP) which includes a wind power aggregator (WPA) and a commercial compressed air energy storage (CAES) aggregator to participate in three electricity markets (day-ahead, intraday and balancing markets). The CAES aggregator has an extra ability which is called a simplecycle mode operation which makes it works like a gas turbine when is needed which helps the HPP to economically handle the miscalculations of the wind power and electricity price predictions. The coordinated strategy of the HPP is formulated as a three-stage stochastic optimization problem. To control the financial risks, the conditional value-at-risk model is added to the optimization problem. Moreover, the proposed offering method is capable of submitting both bidding quantity and curves to the day-ahead market. A mixed integer linear programming formulation is written for the problem which can be easily solved by commercially available software such as GAMS. The results which were tested on a realistic-based case study located in Spain show the applicability of the suggested method to increase the joint operation profit, and decrease the financial risks.

Stochastic Up to Congestion Bidding Strategy in the Nodal Electricity Markets Considering Risk Management

“…In the electricity market, the participants needs to face various uncertainties, such as the electricity prices [21], renewable power productions [22]- [23], and the electric demands of electricity consumers, such as [24]- [27]. To develop the bidding strategy considering these uncertainties in the market, stochastic optimization, robust optimization and information gap decision theory (IGDT) techniques were utilized by the participants [21]- [26].…”

Optimal Bidding Strategy for Offshore Wind Farms Equipped with Energy Storage in the Electricity Markets

“…In [3], the authors proposed a model that provides the possibility of bidding in the day-ahead market to wind farm owners aiming at maximizing their profit. Intraday, day-ahead, and balancing markets were considered in [4] for the participation of a wind power aggregator equipped with compressed air energy storage aggregator to maximize their profit. Maximizing the profit of a wind power producer by bidding in day-ahead and real-time markets were investigated in [5].…”

“…This method needs a large number of scenarios to result in a proper outcome, which in turn increases the size of the problem and makes it intractable. To address this issue and to enhance the computation efficiency without loss of generality, scenario reduction techniques have been used in some studies [1], [4]. A stochastic programming method was implemented in [7] to handle the uncertainties of a wind farmbased problem.…”

“…Pairing a wind farm with an energy storage system may increase the profit of wind farm owners by providing adequate flexibility to participate in different electricity markets. In [3], [4] and [8] storage has been considered in the problem, which has been coupled with wind farms. The impacts of using storage devices on the profit of wind farm owners participating in the day-ahead market were studied in [3].…”

“…However, the balancing market was neglected. Authors in [4] considered a hybrid power plant, consisting of a wind farm and storage, to bid in different electricity markets. The wind farm considered in [4] was a small-scale one, which is not the real case that an electricity market may face with.…”