| dc.description.abstract | The conventional energy grid is being replaced with the new emerging smart grid infras-
tructure. This can be attributed to the fact that it only supports unidirectional energy
ow,
i.e., energy is transmitted from the producer to the consumer. Smart grid addresses issues such
as grid reliability, blackouts, global warming, etc, by implementing various renewable energy
sources readily available for consumer use. The clean electric power can be produced from
local neighbourhoods, individual houses, to large industrial businesses. Therefore, with the im-
plementation of alternative energy sources readily available, users connected to the smart grid
can purchase electric power, enabling groups and individuals to generate a profitable income.
However, challenges persist attributed to user cost, and power management, resulting in active
work to investigate optimization techniques between users in P2P energy trading to enhance the
performance of how users trade energy among each other. Among the various energy trading
mechanisms, auction-based models have demonstrated excellent performance, targetting desir-
able properties for P2P energy trading. In this work, we present three different auction-based
models that can be utilized for practical energy trading. The prosumers (producers and con-
sumers) of energy, play the role as sellers or buyers depending on the current supply and demand.
Sellers with renewable energy sources participate to sell their excess of energy to generate a profit
and satisfy the buyers' demand. We model the interaction with as single-sided and double-sided
auctions, explicitly taking the dynamic nature of both the sellers and buyers into account. We
further propose a profit maximization algorithm that considers power line cost, transmission
capacity, and energy distribution. With theoretical analysis and simulations, we demonstrate
that the proposed auctions are individually rational, truthful, computationally efficient, and
budget-balanced. | en_US |
