IEEE Signal Processing - July 2018 - 109

our focus to recent game-theoretic energy-management models that have been proposed and implemented in P2P energy
networks. Here, instead of providing an overview, we have
given a detailed discussion of a specific game-theoretic
approach in each of the domains of a P2P network. The purpose has been to present how different game-theoretic models
can be designed to solve energy-trading problems in the P2P
energy network and what the key criteria or properties are that
need to be considered during the implementation. Finally, we
have shown some interesting results from the game-theoretic
models, and we have discussed and summarized the interpretation of those outcomes for a better understanding of participants' behavior in P2P energy management.
Energy-management research for P2P networks is relatively
new, and, currently, all of the developments of P2P energytrading platforms are in a pilot phase. Hence, much work is yet
to be done before the integration of P2P energy trading into the
current energy system. In this context, game theory may play a
significant role in future research endeavors.
■ A consumer-centric model: The design of the P2P energytrading schemes need to be consumer-centric, i.e., consumers must benefit from participating in P2P energy trading.
Note that some recent energy-trading models and pilot
projects have been discontinued as they were not accepted
by consumers. To avoid this, the users' interests and benefits must be taken into consideration. One potential way to
do this is to explore cooperative games to demonstrate that
users can always benefit from cooperating. For instance, a
user may choose to be a part of the entire network (i.e., the
grand coalition in a canonical coalition game) or dynamically change its position to a different small coalition
(coalition formation game) to come to an agreement with
other network peers for energy trading.
■ The demonstrated benefit to the grid: In most of the current P2P energy-trading pilot projects, the physical transfer
of energy takes place through the distribution network,
which is set up by the traditional grid [9]. Hence, expecting
that P2P energy trading will completely exclude the grid
from any energy-related activities with local consumers
could be impractical, since trading, itself, is conducted
using the grid's assets. One way to address this problem is
to demonstrate that P2P energy trading is also beneficial
for the grid and that a grid may also participate in P2P
energy trading if necessary. This will also help the regulatory board to understand the importance of P2P energy
trading to both the grid and the local users, paving the way
for this new approach to be approved as a part of the energy system. The Stackelberg game, where the grid can participate either as a leader or a follower depending on the
context of the model and can interact with other users to
decide on various energy-trading parameters across different times, could be an ideal candidate to model this trading.
■ High security and low computational complexity: Due to
the reduced involvement of a centralized authority in P2P
trading, the security and privacy of participants is a critical
issue. In P2P networks, an EU (buyer) does not want to

reveal his/her identity during a transaction with a seller,
whereas the seller does not want the buyer to misuse the
traded energy, e.g., for illegal purposes. Therefore, there is
a strong need for an energy-trading distribution mechanism
in P2P networks that does not pose security and privacy
threats to the sellers and EUs, respectively. The advancement of blockchain technology has solved this problem. A
blockchain is a continuously growing list of records, called
blocks, that are linked and secured using cryptography.
Most of the current pilot projects on P2P energy trading in
the United States, Europe, and Australia are based on
blockchain-based information platforms. Hence, how to
integrate blockchain with game theory is a potential future
research direction of significant importance. However,
using blockchains for privacy protection in P2P trading
may require high computational power; therefore, the integration of blockchain with game theory needs to consider
this particular stipulation with care and design trading
mechanisms that are efficient and have lower computational complexity to provide users with the desired services.
■ Energy trading with incomplete information: Incomplete
information can be defined as a lack of information concerning the real-time demand of prosumers and P2P trading prices because of a problem in the network, e.g., a
packet loss in the communication network. Such incomplete information can potentially damage the performance
of the P2P energy-trading technique, creating the need to
design energy-management solutions that can properly
handle such scenarios. One promising way to address this
is to design an energy-trading mechanism for a P2P network with incomplete game information. One example
is the Bayesian game, where the solution is a Bayesian
Nash equilibrium.
■ The incorporation of physical laws in the game model: An
important aspect that governs the power flows and couples
DERs and aggregators on the physical network is
Kirchhoff's laws, which are not properly modeled in most
studies. The presence of physical laws may greatly complicate energy-trading analysis and has a significant impact on
how the market should be designed and operated. The idea
of how to incorporate the impact of Kirchhoff's laws into
the game-theoretic model for P2P energy trading needs considerable attention. One solution could be to include a common constraint between the players of the game (similar to
what is done in a generalized Nash game) that will be influenced by Kirchhoff's laws. Regardless, in-depth investigation is required to decide how to introduce such a common
coupling constraint.
The potential application of game-theoretic approaches in
P2P energy trading and their subsequent implications for the
participating users is significant. The purpose of this article
has been to put a small drop in that large vessel by showing the
importance of game theory for such networks by demonstrating what it is capable of and how it has been used so far, as well
as to provide the reader with some ideas on how they might
contribute to this emerging energy domain.

IEEE Signal Processing Magazine

July 2018

109

Table of Contents for the Digital Edition of IEEE Signal Processing - July 2018