Risk-constrained offering strategy for a hybrid power plant consisting of wind power producer and electric vehicle aggregator

A Multiagent Competitive Bidding Strategy in a Pool-Based Electricity Market With Price-Maker Participants of WPPs and EV Aggregators

“…Numerous cooperative models have been proposed based on collaborators' compensation for peak shaving [6][7][8]. Although the cooperative model in [9] has improved the common interests of EVs and WPPs on account of their energy coordination during different time slots, this model depends highly on the centralized control and scheduling of a central aggregator who owns lots of bidding information of EVs and WPPs. In this way, the communication requirement between EVs and WPPs is high, the privacy of EVs and WPPs cannot be guaranteed, and WPPs and EV aggregators have little flexibility to cope with any self-decisions.…”

“…So far, to the best of authors' knowledge, there is few study considering the renewable WPPs and EV aggregators as oligopolists for developing a competitive multi-agent bidding strategy in a pool-based day-ahead (DA) market without either any information of opponents or calculating any equilibrium point. Based on the previous work to propose a bi-level stochastic optimization model of central controlled offering strategy for an aggregated WPP-EV hybrid power plant (HPP) as a price maker in the DA market considering the uncertainties of energy production and the spot price in real-time (RT) market [9], a new competitive DA market model for oligopoly players WPPs and EV aggregators with incomplete information to develop bidding strategy and consider uncertainties in their maximal power productions and bid prices of other players is first proposed in this paper, and then efficiently solved using a recently developed multi-agent decentralized Win or Learn Fast Policy Hill Climbing (WoLF-PHC) [31] method, based on an easy average policy instead of the equilibrium policy, which could not only meet the requirements of respecting individual privacy and the autonomy of energy providers but also accommodate the complex bidding behaviors of energy suppliers, to maximize revenues of WPPs and EV aggregators.…”

A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets

“…By establishing the linear affine function between the electricity market price, the wind power predicted output deviation, and the power of the ESS charge and discharge, the stochastic optimization declaration strategy of WT was proposed. In [12], considering both the randomness of the wind power output and the uncertainty of the spot price, a hybrid power plant's two-level stochastic optimization model consisting of wind power suppliers and electric vehicles was proposed, which could effectively reduce the bidding risk and increase the profit of the hybrid power plant.…”

Risk‐constrained offering strategies for a large‐scale price‐maker electric vehicle demand aggregator

“…In addition, the coordinated operation of aggregated EVs with renewable resources, especially wind power producers, has been investigated in several studies [10–13]. This joint operation can mitigate the inherent uncertainties in the power generation of these resources and facilitate their integration in the power system.…”