IEEE Signal Processing - July 2018 - 91

This article provides an overview of the use of game-theoretic
approaches for P2P energy trading as a feasible and effective
means of energy management. Various game- and auction-theoretic approaches are discussed by following a systematic classification to provide information on the importance of game
theory for smart energy research. This article also focuses on the
key features of P2P energy trading and gives an introduction to
an existing P2P testbed. Furthermore, the article gives specific
game- and auction-theoretic models that have recently been
used in P2P energy trading and discusses important findings
arising from these approaches.

Motivation
In recent years, there has been an urgent pursuit of an alternative energy system in which energy production, transmission,
distribution, and consumption can take place in an environmentally sustainable fashion. As a result, the development of smart,
sustainable, and green solutions is becoming more significant,
including the widespread deployment of distributed energy
resources (DERs) at residences [1], the introduction of electric
vehicles (EVs) [2], and the establishment of various smart energy services, e.g., demand response management [3], for the
effective management of energy resources within the electricity
grid. Consequently, different signal processing techniques, e.g.,
machine learning, artificial intelligence (AI) [4], and game theory [5], have been offered as solutions to consumers.
An important objective of using these signal processing
techniques is to promote the use of renewable energy sources
within the energy grid. For example, machine learning and
AI have been used extensively to forecast the power generated
from solar panels and wind turbines [6]. Due to this innovative
use of signal processing tools as well as extensive rebates from
local governments, a number of existing systems use DERs
as the main or subsidiary source of energy. In particular, the
global market for rooftop solar panels is booming; for instance,
whereas the global market for rooftop solar panels was nearly
US$30 billion in 2016, it is expected to grow by 11% over the
next six years [7]. Meanwhile, the shift toward solar is being
complemented by an increase in residential energy storage system adoptions, whose ability to deliver energy is predicted to
grow from roughly 95 MW in 2016 to more than 3,700 MW
by 2025 [7].
If properly utilized, these energy sources at the edge of
the grid can help manage demand more efficiently; however,
this will only happen if the owners of these power-generating
assets are fully incorporated into the energy market [7]. To
this end, a feed-in-tariff (FiT) scheme is a suitable model that
engages customers to participate in energy trading. In an FiT,
as shown in Figure 1(a), prosumers with DERs, such as rooftop
solar panels, sell their excess solar energy only to the grid and
can buy energy from the grid in case of any energy deficiency.
However, due to the significant disparity between the buying
and selling prices per unit of energy, the benefit to prosumers
for participating in energy trading is not significant enough.
As a result, some of the FiT techniques have been discontinued [8], making it increasingly important to create new energy

markets that allow small-scale participants (users) to actively
trade energy with one another in real time and facilitate a sustainable and reliable balance between the generation and consumption of energy within the community [9].
As such, P2P energy trading is being considered as a potential tool to promote the use of DERs within the energy grid
[9]. The main objective of P2P sharing is to break the centralized infrastructure of the electricity grid by allowing the
direct communication and supply of energy between various
prosumers with DERs within the energy system, as shown in
Figure 1(b). This enables interested consumers to buy renewable energy at a cheaper rate from a peer (or neighbor) with
excess renewable energy (e.g., from rooftop solar), thereby
reducing those consumers' dependence on the grid or a central supplier [10]. The development of such P2P energy trading
has the potential to substantially benefit prosumers in terms of
earning revenues, reducing electricity costs, and lowering their
dependency on the grid. An example of such P2P technology
in real energy systems can be found in the recent development
of the Brooklyn Microgrid Project (BMP) [9].
In energy trading, the direct involvement of the users with
one another and with the grid makes P2P systems unique
when compared to existing FiT schemes. The system poses the
challenge of modeling the decision-making process of each
participant for the greater benefit of the entire energy network
while taking into account human factors, e.g., rationality, motivation, and environmental friendliness. Particularly, in settings where there are many users with conflicting interests
participating, it would be challenging either to integrate such
conflicting interests when designing the decision-making process of each participant or, if necessary, to motivate the users
to cooperate with reducing costs, maximizing revenues, and
pursuing renewable energy objectives. Hence, such trading
needs to be built on signal processing methods that can take
such a diverse set of constraints into consideration and deliver
an energy-management solution that ensures the efficient and
robust operation of heterogeneous and large-scale cyberphysical systems. In this context, and considering the interactive
and conflicting nature of energy trading, game theory is a very
effective tool for modeling the decision-making processes of
the participants in P2P networks.
Game theory has been used extensively for the design and
analysis of energy systems; however, due to the purpose and
framework of P2P energy trading, existing schemes may not
be suitable in this context. This is because 1) in P2P trading,
the main objective is to encourage the participants to trade
energy with one another and, thus, comprise a community of
energy buyers and sellers without any (or nearly any) direct
influence from the grid so that the price signal from the central power station may not affect the performance of the P2P
trading the way it influences the scheduling and trading of
energy in existing systems; and 2) while the energy-trading
schemes in the smart grid have exploited various pricing
schemes including real-time and time-of-use pricing, P2P
trading will necessitate the incorporation of more innovative
pricing schemes. For example, as an independent decision

IEEE Signal Processing Magazine

|

July 2018

|

91



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

Contents
IEEE Signal Processing - July 2018 - Cover1
IEEE Signal Processing - July 2018 - Cover2
IEEE Signal Processing - July 2018 - Contents
IEEE Signal Processing - July 2018 - 2
IEEE Signal Processing - July 2018 - 3
IEEE Signal Processing - July 2018 - 4
IEEE Signal Processing - July 2018 - 5
IEEE Signal Processing - July 2018 - 6
IEEE Signal Processing - July 2018 - 7
IEEE Signal Processing - July 2018 - 8
IEEE Signal Processing - July 2018 - 9
IEEE Signal Processing - July 2018 - 10
IEEE Signal Processing - July 2018 - 11
IEEE Signal Processing - July 2018 - 12
IEEE Signal Processing - July 2018 - 13
IEEE Signal Processing - July 2018 - 14
IEEE Signal Processing - July 2018 - 15
IEEE Signal Processing - July 2018 - 16
IEEE Signal Processing - July 2018 - 17
IEEE Signal Processing - July 2018 - 18
IEEE Signal Processing - July 2018 - 19
IEEE Signal Processing - July 2018 - 20
IEEE Signal Processing - July 2018 - 21
IEEE Signal Processing - July 2018 - 22
IEEE Signal Processing - July 2018 - 23
IEEE Signal Processing - July 2018 - 24
IEEE Signal Processing - July 2018 - 25
IEEE Signal Processing - July 2018 - 26
IEEE Signal Processing - July 2018 - 27
IEEE Signal Processing - July 2018 - 28
IEEE Signal Processing - July 2018 - 29
IEEE Signal Processing - July 2018 - 30
IEEE Signal Processing - July 2018 - 31
IEEE Signal Processing - July 2018 - 32
IEEE Signal Processing - July 2018 - 33
IEEE Signal Processing - July 2018 - 34
IEEE Signal Processing - July 2018 - 35
IEEE Signal Processing - July 2018 - 36
IEEE Signal Processing - July 2018 - 37
IEEE Signal Processing - July 2018 - 38
IEEE Signal Processing - July 2018 - 39
IEEE Signal Processing - July 2018 - 40
IEEE Signal Processing - July 2018 - 41
IEEE Signal Processing - July 2018 - 42
IEEE Signal Processing - July 2018 - 43
IEEE Signal Processing - July 2018 - 44
IEEE Signal Processing - July 2018 - 45
IEEE Signal Processing - July 2018 - 46
IEEE Signal Processing - July 2018 - 47
IEEE Signal Processing - July 2018 - 48
IEEE Signal Processing - July 2018 - 49
IEEE Signal Processing - July 2018 - 50
IEEE Signal Processing - July 2018 - 51
IEEE Signal Processing - July 2018 - 52
IEEE Signal Processing - July 2018 - 53
IEEE Signal Processing - July 2018 - 54
IEEE Signal Processing - July 2018 - 55
IEEE Signal Processing - July 2018 - 56
IEEE Signal Processing - July 2018 - 57
IEEE Signal Processing - July 2018 - 58
IEEE Signal Processing - July 2018 - 59
IEEE Signal Processing - July 2018 - 60
IEEE Signal Processing - July 2018 - 61
IEEE Signal Processing - July 2018 - 62
IEEE Signal Processing - July 2018 - 63
IEEE Signal Processing - July 2018 - 64
IEEE Signal Processing - July 2018 - 65
IEEE Signal Processing - July 2018 - 66
IEEE Signal Processing - July 2018 - 67
IEEE Signal Processing - July 2018 - 68
IEEE Signal Processing - July 2018 - 69
IEEE Signal Processing - July 2018 - 70
IEEE Signal Processing - July 2018 - 71
IEEE Signal Processing - July 2018 - 72
IEEE Signal Processing - July 2018 - 73
IEEE Signal Processing - July 2018 - 74
IEEE Signal Processing - July 2018 - 75
IEEE Signal Processing - July 2018 - 76
IEEE Signal Processing - July 2018 - 77
IEEE Signal Processing - July 2018 - 78
IEEE Signal Processing - July 2018 - 79
IEEE Signal Processing - July 2018 - 80
IEEE Signal Processing - July 2018 - 81
IEEE Signal Processing - July 2018 - 82
IEEE Signal Processing - July 2018 - 83
IEEE Signal Processing - July 2018 - 84
IEEE Signal Processing - July 2018 - 85
IEEE Signal Processing - July 2018 - 86
IEEE Signal Processing - July 2018 - 87
IEEE Signal Processing - July 2018 - 88
IEEE Signal Processing - July 2018 - 89
IEEE Signal Processing - July 2018 - 90
IEEE Signal Processing - July 2018 - 91
IEEE Signal Processing - July 2018 - 92
IEEE Signal Processing - July 2018 - 93
IEEE Signal Processing - July 2018 - 94
IEEE Signal Processing - July 2018 - 95
IEEE Signal Processing - July 2018 - 96
IEEE Signal Processing - July 2018 - 97
IEEE Signal Processing - July 2018 - 98
IEEE Signal Processing - July 2018 - 99
IEEE Signal Processing - July 2018 - 100
IEEE Signal Processing - July 2018 - 101
IEEE Signal Processing - July 2018 - 102
IEEE Signal Processing - July 2018 - 103
IEEE Signal Processing - July 2018 - 104
IEEE Signal Processing - July 2018 - 105
IEEE Signal Processing - July 2018 - 106
IEEE Signal Processing - July 2018 - 107
IEEE Signal Processing - July 2018 - 108
IEEE Signal Processing - July 2018 - 109
IEEE Signal Processing - July 2018 - 110
IEEE Signal Processing - July 2018 - 111
IEEE Signal Processing - July 2018 - 112
IEEE Signal Processing - July 2018 - 113
IEEE Signal Processing - July 2018 - 114
IEEE Signal Processing - July 2018 - 115
IEEE Signal Processing - July 2018 - 116
IEEE Signal Processing - July 2018 - 117
IEEE Signal Processing - July 2018 - 118
IEEE Signal Processing - July 2018 - 119
IEEE Signal Processing - July 2018 - 120
IEEE Signal Processing - July 2018 - 121
IEEE Signal Processing - July 2018 - 122
IEEE Signal Processing - July 2018 - 123
IEEE Signal Processing - July 2018 - 124
IEEE Signal Processing - July 2018 - 125
IEEE Signal Processing - July 2018 - 126
IEEE Signal Processing - July 2018 - 127
IEEE Signal Processing - July 2018 - 128
IEEE Signal Processing - July 2018 - 129
IEEE Signal Processing - July 2018 - 130
IEEE Signal Processing - July 2018 - 131
IEEE Signal Processing - July 2018 - 132
IEEE Signal Processing - July 2018 - 133
IEEE Signal Processing - July 2018 - 134
IEEE Signal Processing - July 2018 - 135
IEEE Signal Processing - July 2018 - 136
IEEE Signal Processing - July 2018 - 137
IEEE Signal Processing - July 2018 - 138
IEEE Signal Processing - July 2018 - 139
IEEE Signal Processing - July 2018 - 140
IEEE Signal Processing - July 2018 - Cover3
IEEE Signal Processing - July 2018 - Cover4
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201809
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201807
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201805
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201803
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_201801
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1117
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0917
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0717
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0517
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0317
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0117
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1116
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0916
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0716
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0516
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0316
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0116
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1115
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0915
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0715
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0515
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0315
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0115
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1114
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0914
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0714
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0514
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0314
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0114
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1113
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0913
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0713
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0513
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0313
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0113
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1112
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0912
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0712
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0512
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0312
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0112
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1111
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0911
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0711
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0511
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0311
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0111
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1110
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0910
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0710
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0510
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0310
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0110
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1109
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0909
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0709
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0509
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0309
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0109
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_1108
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0908
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0708
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0508
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0308
https://www.nxtbook.com/nxtbooks/ieee/signalprocessing_0108
https://www.nxtbookmedia.com