Abstract
In this paper, considering real time wind power uncertainties, the strategic behaviors of wind power producers adopting two different bidding modes in day-ahead electricity market is modeled and experimentally compared. These two different bidding modes only provide a wind power output plan and a bidding curve consisting of bidding price and power output, respectively. On the one hand, to significantly improve wind power accommodation, a robust market clearing model is employed for day-ahead market clearing implemented by an independent system operator. On the other hand, since the Least Squares Continuous Actor-Critic algorithm is demonstrated as an effective method in dealing with Markov decision-making problems with continuous state and action sets, we propose the Least Squares Continuous Actor-Critic-based approaches to model and simulate the dynamic bidding interaction processes of many wind power producers adopting two different bidding modes in the day-head electricity market under robust market clearing conditions, respectively. Simulations are implemented on the IEEE 30-bus test system with five strategic wind power producers, which verify the rationality of our proposed approaches. Moreover, the quantitative analysis and comparisons conducted in our simulations put forward some suggestions about leading wind power producers to reasonably bid in market and bidding mode selections.
Highlights
The day-ahead electricity market (EM) is a crucial component in the EM system [1]
If the market clearing procedure were implemented by independent system operator (ISO) without considering enough uncertainties, the reserve capacity of the system dispatched in day-ahead might find it hard to accommodate deviations caused by wind power producer (WPP)’ power output uncertainties in real time, which can seriously affect the security of the system and cause huge extra costs such as wind-abandonment, etc
We present a LSCAC-based day-head EM modeling approach with a robust market clearing mechanism embedded in it, and strategic behaviors of WPPs under two different bidding mode (BM) are successively mimicked and compared by using our proposed approach
Summary
The day-ahead electricity market (EM) is a crucial component in the EM system [1]. In recent years, wind power resources have experienced an unprecedented growth in the day-ahead EMs worldwide. Many references propose that the wind power accommodation can be improved by modifying the market clearing model (MCM) corresponding to ISO in day-ahead EM. Inspired by [20], in this work, no matter which BM WPPs adopt in day-ahead EM bidding, the MCM corresponding to ISO will be modified by using a RO-method in order to make the power system accommodate any deviation caused by real time wind power uncertainties within a certain range. The authors in reference [39] proposed a two-stage stochastic bidding model based on kernel density estimation (KDE) for a BM 2 adopted WPP to obtain the optimal day-ahead bidding strategy. The main novelty of this paper can be summarized as to firstly propose the LSCAC-based day-ahead EM modeling approach for strategic WPPs under robust market clearing conditions.
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