2,587 research outputs found
Feasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid
This paper investigates the feasibility of using a discriminate pricing
scheme to offset the inconvenience that is experienced by an energy user (EU)
in trading its energy with an energy controller in smart grid. The main
objective is to encourage EUs with small distributed energy resources (DERs),
or with high sensitivity to their inconvenience, to take part in the energy
trading via providing incentive to them with relatively higher payment at the
same time as reducing the total cost to the energy controller. The proposed
scheme is modeled through a two-stage Stackelberg game that describes the
energy trading between a shared facility authority (SFA) and EUs in a smart
community. A suitable cost function is proposed for the SFA to leverage the
generation of discriminate pricing according to the inconvenience experienced
by each EU. It is shown that the game has a unique sub-game perfect equilibrium
(SPE), under the certain condition at which the SFA's total cost is minimized,
and that each EU receives its best utility according to its associated
inconvenience for the given price. A backward induction technique is used to
derive a closed form expression for the price function at SPE, and thus the
dependency of price on an EU's different decision parameters is explained for
the studied system. Numerical examples are provided to show the beneficial
properties of the proposed scheme.Comment: 7 pages, 4 figures, 3 tables, conference pape
Improving the Scalability of a Prosumer Cooperative Game with K-Means Clustering
Among the various market structures under peer-to-peer energy sharing, one
model based on cooperative game theory provides clear incentives for prosumers
to collaboratively schedule their energy resources. The computational
complexity of this model, however, increases exponentially with the number of
participants. To address this issue, this paper proposes the application of
K-means clustering to the energy profiles following the grand coalition
optimization. The cooperative model is run with the "clustered players" to
compute their payoff allocations, which are then further distributed among the
prosumers within each cluster. Case studies show that the proposed method can
significantly improve the scalability of the cooperative scheme while
maintaining a high level of financial incentives for the prosumers.Comment: 6 pages, 4 figures, 2 tables. Accepted to the 13th IEEE PES PowerTech
Conference, 23-27 June 2019, Milano, Ital
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