Non-cooperative game-theoretic model of demand response aggregator competition for selling stored energy in storage devices

Stochastic risk-constrained decision-making approach for a retailer in a competitive environment with flexible demand side resources

“…Decision‐making strategies for retailer participating in electricity markets have also been investigated in several research works. Some of these works address decision‐making problem of EVs aggregator as a retailer to participate in energy market . For example, a bi‐level programming approach has been proposed in Lujano‐Rojas et al based on the Stackelberg game model.…”

“…Some of these works address decision-making problem of EVs aggregator as a retailer to participate in energy market. [11][12][13][14][15] For example, a bi-level programming approach has been proposed in Lujano-Rojas et al 10 based on the Stackelberg game model. In Yang et al, 12 a bidding strategy for EV aggregator has been proposed to minimize the expected electricity costs considering price volatility.…”

A stochastic bi‐level decision‐making framework for a load‐serving entity in day‐ahead and balancing markets

“…However, the effect of PEVs' scheduling in decision‐making of LSEs is not addressed. A market model has been provided based on game‐theoretical implications in Motalleb and Ghorbani where DR aggregators compete against each other to sell energy stored in consumers' storage devices. Therefore, optimal bidding decision for each aggregator to maximize its own payments despite incomplete information in the game and remarkable changes in market circumstance is provided.…”

“…Therefore, optimal bidding decision for each aggregator to maximize its own payments despite incomplete information in the game and remarkable changes in market circumstance is provided. However, in Motalleb and Ghorbani, the tendency towards optimal payments for the energy requirement derived from loads and PEV use for movement is not considered. This matter could highly affect the customer's choice to select the fairest aggregator for its energy requirements.…”

“…Table 1 addresses a systematic comparison between the contributions of this paper and some of the recent works in the same subject area. As can be observed, most of the recent works (ie, see previous studies [6][7][8][9][10][11][13][14][15][16] ) did not consider the PEVs' charging and discharging management in the optimization problems of LSEs, and they mainly investigated only impacts of DR programs on the other types of responsive loads. To the best of the authors' knowledge, there are some limited works addressing the decision-making problem of LSE by considering both PEVs' and customers' participation in DR programs, simultaneously, however, they did not consider competitive trading floor (ie, Momber et al 12 ).…”