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Blockchain based Balancing of Electricity Demand and Supply

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The growing number of Renewable Energy Sources (RES) in the energy system provides new market approaches according to price and decentralized generation of electricity. Local markets, on which consumers and prosumers can trade locally with each other by produced renewable generation directly within their community. This approach creates a balance between generation and consumption in a decentralized manner. In this paper, a distributed technology of Blockchain is used, which highlights the decentralized nature of local market. Thus, provides a decentralized market platform for trading locally without the need of central intermediary through Periodic Double Auction (PDA) mechanism. With the introduction of Smart Grid (SG) systems, there have been improvements in how utility companies interact with customers with regards of electricity usage. However, since the readings are done through the internet, there is a tendency for the data to be compromised. However, customers do not know why they pay huge amount of bills. In this proposed system, users are able to do trading through PDA and get access of their own previous history.The Blockchain technology provides transparency and is utilized to mitigate the above mentioned problems. Smart contacts, are used to exclude the third party to provide a transparent system between users on the network.
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Blockchain Based Balancing of Electricity
Demand and Supply
Maheen Zahid, Ishtiaq Ali, Raja Jalees Ul Hussen Khan, Zainib Noshad,
Atia Javaid, and Nadeem Javaid(B
)
COMSATS University Islamabad, Islamabad, Pakistan
maheen.zahid2017@gmail.com, ishiali503@gmail.com, jalees106@gmail.com,
zainabnoshad@yahoo.com, atiajavaid477@gmail.com,
nadeemjavaidqau@gmail.com
Abstract. The growing number of Renewable Energy Sources (RES) in
the energy system provides new market approaches according to price
and decentralized generation of electricity. Local market, in which con-
sumers and prosumers can trade locally by generation of electricity
through RES directly within their community. This approach creates
a balance between generation and consumption in a decentralized man-
ner. In this paper, a distributed technology of Blockchain is used, which
highlights the decentralized nature of local market. It provides a decen-
tralized market platform for trading locally without the need of central
intermediary through Periodic Double Auction (PDA) mechanism. With
the introduction of Smart Grid (SG) systems, there have been improve-
ments in how utility companies interact with customers with regards of
electricity usage. However, there is a tendency for the data of users to
be compromised in SG. In this proposed system, users are able to do
trading through PDA and get access of their own previous history. The
blockchain provides transparency, traceability and is utilized to mitigate
the above mentioned problems. Smart contacts, are used to exclude the
third party to provide a transparent system between users in the network.
Keywords: Smart Grid ·Blockchain ·Electricity trading ·Periodic
Double Auction
1 Introduction
Electricity plays a vital role in the development of the latest technologies. It is the
basic necessity for the economic development of any country. It is helpful in var-
ious areas: transportation, education, banking and computing etc and it enables
several revolutions. The integration of Information and Communication Technol-
ogy (ICT) in the traditional grid it becomes Smart Grid (SG). SG is an emerging
technology of this modern era [1]. It provides the facility of bi-directional com-
munication between the utility and its consumers. It introduces the recently
advanced energy generation ways such as solar panels and charging/discharging
of Electric Vehicles (EV) [2]. Smart Home (SH) is an important entity to make
c
Springer Nature Switzerland AG 2020
L. Barolli et al. (Eds.): BWCCA 2019, LNNS 97, pp. 185–198, 2020.
https://doi.org/10.1007/978-3-030-33506-9_17
186 M. Zahid et al.
any city smart. The SH directly communicates with SG through Smart Meter
(SM) to get electricity according to its demand. SG enables consumers to prop-
erly manage their electricity consumption through the Home Energy Manage-
ment System (HEMS) [3]. The data recorded from the SM is transmitted directly
to SG in real-time through communication medium. SM’s data is stored in the
SG database and used for billing and also available for research purpose [4,5].
However, SG is a centralized system and it does not provide data access to the
users. Furthermore, the data stored in the SG systems may easily be tempered
by malicious attacks, which tend to increase the amount of electricity bill with-
out knowing the consumer and utility companies. Users do not know why they
are paying huge amount of bills. There are also many issues facing by consumer
and SG about users data such that: traceability, authorization, immutability,
security of data and single point of failure. To solve the above aforementioned
issues, a new emerging technology of blockchain is introduced.
A scientist named Satoshi Nakamoto gives the idea of “Bitcoin” digital cur-
rency, a form of electronic cash in 2008. A concept of Peer-to-Peer (P2P) online
trading of digital currency is introduced without the need of an intermediary
party [6]. For electronic payments on the Internet, a trusted third party is
required as a financial institution. Moreover, for P2P trading digital signatures
are used as an initiator to verify the existence of both parties. The crypto-
graphic proof is necessary to build trust that shows the willingness and trust-
worthiness of two parties. In this article, Satoshi proposed the system of P2P
trading. However, this concept is beneficial for online trading, when any com-
pany or enterprise wants to use it practically. So, to implement this concept in
a real-time environment, an idea proposed about the innovative technology [7]
named “Blockchain” in 2015. According to this, Blockchain technology changed
the vision of the business model all over the world. It is an innovative disruption
in the world of computers, social networks. It is defined as structural database
for decentralized storage of data [8]. A block is a collection of data containing
related information known as transactions [9].
A timestamp shows the creation time of a block, when many transactions
are done and after that, a block is generated. A block comprises of header and
body. A header contains hash of the previous block, through which the current
block is combined with the previous one and current block knows about its
previous block through its hash. The body contains all the transactions and
their hashes. Once a block is a part of the chain then, it is very difficult to
be tempered. When block is created and validated then, it becomes the part
of the chain due to its hash. Blockchain is classified into three types: public,
private and consortium blockchain. Public is open, anyone can be a part of
this. Private has some restrictions so, only authorized nodes are the part of the
network. Consortium blockchain contains half features of public and half features
of private. Its data is publicly available to users for read-only, while the write
access is available to just authorized nodes [10]. Different characteristics of these
three types of Blockchain are shown in Table1.
Blockchain Based Balancing of Electricity Demand and Supply 187
Different consensus mechanisms are also used for the validation of blocks
and after consensus the block becomes the part of the chain. There are different
kinds of consensus mechanisms which are as following: Proof of Work (POW),
Proof of Stake (POS), Proof of Identity (POI) and Proof of Authority (POA)
[10]. The base of all other types of consensus mechanisms are POW.
Table 1. Characteristics of blockchain types
Type Openness Decentralization Wri te Read
Public Anyone Complete Any one Everyone
Private Specific individuals Partially Specific nodes Specific
Consortium Specific groups Partially Specific nodes Anyone
Now-a-days Blockchain is used in different paradigms: in health monitoring,
data sharing, getting feedback from users, decentralized trading. To minimize
the chances of single point failure, unauthorized persons are not the part of any
network to prevent malicious attacks.
In this paper, the solution of blockchain based different smart contracts are
proposed that creates a system of P2P trading through Periodic Double Auction
(PDA). Authorized users are just able to get access to their own data history.
Due to immutability, the users can easily see their original record file and this
data is not altered by anyone. Different smart contracts are used to eliminated
the third party concept. It is beneficial for users to prevent them to pay the huge
amount of taxes in their bills. Due to the deployment of smart contracts, the
users pay a small amount of ethers for the transaction.
Section 2described and discussed the related work. In Sect. 3, provided the
implementation details of the proposed model. Section 4summarized the main
finding of this paper.
2 Related Work
In [11], Blockchain based P2P energy trading platform is proposed for efficient
transaction of power between prosumers and consumers. The suggested platform
is used two different types of P2P trading scenarios: one is Pure P2P and the
other is Hybrid P2P. In Pure P2P trade, energy is used as a transaction item
and in Hybrid P2P, energy tag is used as a transaction. A Tag is assigned to
block for validation and transaction. The production of electrical energy from
different domains are divided into ten different categories. Some of them are
consumer-oriented and some of them are supply-oriented.
In [12], the authors presented the concept of sovereign Blockchain technology,
which prevents data tempering from any malicious source. It also maintained the
records of tempered data in side Blockchain. Consumers send their requests of
electricity according to their demand to SG through SM. The users monitored
188 M. Zahid et al.
their usage and also know about how much electricity they demand. If the tem-
pering happened then, the record of this tempered data is also kept in side chain
of the sovereign Blockchain.
Authors in [13], discussed the idea of distributed trading of electricity in
which nodes are used as: consumers and prosumers for P2P trading. They pro-
posed a model consists of two layers: one layer is Multi-Agent System (MAS)
used for the sustenance of prosumer side information of generation of electricity.
MAS enabled users to negotiate the prices and form coalition. The second layer
showed the secure and trustworthy trading through transactions between MAS
and Social Coordination Agent (SCA). The trading is secure due to Blockchain
based settlement system in which the double-chain and high-frequency verifica-
tion mechanism worked parallelly, which helped to make trading transparent.
In every negotiation system, data is chained one by one and stored in the first
chain. The high-frequency mechanism are used to detect any malicious activity
occurred between contract and ledger.
In this paper [14], the authors proposed the concept of Federated Power
Plants (FPP) and Virtual Power Plants (VPP). VPP made P2P transactions
through self-organizing users. They also discussed the incentive mechanism dur-
ing trade between prosumers and consumers. Two different types of strategies
are proposed: Coordination between Distributed Energy Resources (DER) into
VPP and P2P energy trading platform.
Noor et al. [15] worked on the Demand Side Management (DSM) to improve
the reliability of the whole system. A game theoretic approach is used in sim-
ple DSM model, which does not only minimize the peak-to-average ratio in
SG. It also reduced the dips in a load profile of users. Blockchain technology
implemented a DSM system to make P2P trading system secure. In [16], the
maintenance and skillful usage of natural resources are essentially related and
beneficial for utilization of electricity. The use of the enormous powers, i.e., coal,
water, daylight, geothermal resources, wind and gravitational forces for elec-
tricity generation. In [17], the authors proposed a framework, which contains
seven components. These components are used to implement private Blockchain
in Brooklyn case study. In this paper, the authors introduced the merged con-
cept of MG and Blockchain to introduced MG energy market. Homes are acting
as prosumers and they generate electricity through PV. The physical layer is
showing the infrastructure of MG. Virtual layer displays the price and trad-
ing mechanism. Regulation layer tells about the government policies, taxes and
rules.
In [18], the authors addressed the issue of Demand Response (DR) with a
decentralized system and encouraged the consumers use less energy consumption
in on peak hours. The authors proposed the framework of Distributed Load
Balancing Trade Framework (LBTF) with two different schemes: Utility-Grid
contract and MG contract. Consortium Blockchain is used and POW consensus
algorithm is public key encryption, digital signatures and hash functions are
used to maintain security of users’ information.
Blockchain Based Balancing of Electricity Demand and Supply 189
Pop et al. [19] used a Blockchain based model for storing, managing and val-
idation of DR in low or medium voltages of SGs. Blockchain stored all that data
in P2P distributed ledger network which is collected from IOT smart metering
devices in a secure manner which is called as temper proof mannered. Authors
implemented a new smart contract named as a self-enforcing smart contract
which is used for checked out and tracked each Distributed Energy Prosumer
(DEP) profiles. All DEPs are enrolled in DR program. Their penalties or rewards
are calculated here and it also detects the unbalanced grid energy for DR events.
In [20], the authors described the P2P energy trading system using coalition
formation method. Surplus energy and depicted energy MGs are also able to com-
municate directly with each other. They know about each other state and if they
want to share electricity, they trade easily with each other. A Blockchain-based
system provides this facility to maintain their state record, whether they want
to sell or buy electricity to fulfill the demand of their consumers. Blockchain pro-
vided secure transactions and a consensus mechanism allows every valid trans-
action to add in a block.
The utilities realized their role in the power systems. When the consumers’
need a power supply to fulfill their electricity demands. They directly contact
utilities. The authors in [21] described the responsibilities of utilities. They
collect domestic communities information because there is a rapid increase in
the usage of electricity. These modern systems fully spread the power markets
and also increased the accessibility of decentralized renewable power production.
However, the utilities are able to modernize their business models and support
SG markets by proficient knowledge.
Wang et al. proposed the system of transactions between MGs through
Blockchain and they are using the continuous double auction mechanism for
trading [22]. The authors proposed the concept of Unspent Transaction Out
(UTXO) model. In this system, the authors used Continuous Double Auction
(CDA) with Blockchain technology parallelly to achieved low-cost transactions
and transparent data of MG. Satoshi is used as a digital currency which is the
sixteenth part of the bitcoin. It is also used as a token. The mechanism of trad-
ing of electricity and transfer of tokens are very helpful. MGs can sell/ buy
their energy with each other. MGs are able to fulfill the requirements of their
consumers. In this system, the unique data structure of Blockchain confirmed
the security of data. However, in this system, the authors ignored the power
fluctuation in the main SG.
In [23], the authors discussed the issues of management and control of sus-
tainable energy forms. To solved these problems, blockchain implemented with
energy through the internet and gives the new concept of energy internet. It con-
sists of renewable energy generation, Energy Storage Devices (ESD) and inter-
net is used for connectivity between them. The energy internet involved various
energy forms and different participants. The main contributions are to intro-
duce the compatibility of energy internet and blockchain technology. Blockchain
is implemented in many companies and is helpful to provide decentralized appli-
cations, however, the excessive power usage is considered. It is just suitable for
190 M. Zahid et al.
some small communities and the practical implementation on a huge commercial
level needs more resources. Smart Community (SC) is a necessary part of the
Internet of Energy (IoE) which connected all the RES, SG and EV. Permissioned
blockchain is used on the basis of smart contracts for secure and private com-
munication. The authors proposed reputation based Delegated Byzantine Fault
Tolerance (DBFT) consensus algorithm for energy trading. Users also take elec-
tricity from traditional SG or electricity generated through RES, it depends on
EV user. Furthermore, this system is designed for SGs, however, prosumers are
not considered to participate in it.
In [24], authors proposed the privacy preserving mechanism through private
blockchain. Authors in [25,26] proposed incentive mechanism and repudiation
Table 2. Summary of related work of blockchain
Proposed models Achievements Limitations
[10] Energy Internet with
blockchain
Reduced costs Reliability and excessive
power consumption
[11]LEM Short term electricity
trading, transparent
High Energy Consumption
[12] Grid Monitoring
System
Customer utility control Storage Capacity is small
[13] MAS system Efficient negotiation
System
Interruption of third party
[14] FPP platform Confidential coordination
between VPPs
Cost consumption is very
high
[15] Game theoretic model Reduce peak-to-average
ratio and reduced dips
Storage capacity is less
[16] Brooklyn MG Scalability and robustness Cost is high
[17]LBTF Privacy and integration of
stored data
Computation time
between nodes is very high
[18] Decentralized DR
system
DSM system Multi stakeholder market
[20] P2P using distributed
coalition formation
method
Trust and robustness Specific for only two MGs
[22]UTXO Low cost transactions and
transparency
Ignored the power
fluctuation in the main SG
[23]DBFT Energy trading Third party is involved
[36] Pure P2P and hybrid
P2P
Invalid transaction, energy
loss, cost efficient
Privacy and no access
control of users
[37]POC Saved the labor cost,
minimized the human
interaction
Fixedpricesforusers
Blockchain Based Balancing of Electricity Demand and Supply 191
system through blockchain for data storage of IoT devices on cloud edge network.
In [2729] authors used blockchain for data trading and store health records of
patients on IPFS. Authors in [3032] performed node recovery in wireless sensor
networks and provide secure communication in crowd sensor networks through
blockchain (Table 2).
2.1 Problem Statement
Home Energy Management Controller (HEMC) is a centralized system which
monitors and controls the home appliances. A consumer requests its electricity
demand through SM to SG which can reveal the consumption behavior in front
of third party [33]. In such a way, all the data of users can be easily hacked and
the malicious person can extract the behavior of users about the routine of the
SH dwellers or inhabitants. Authors in [34] proposed cloud based systems to save
the large amount of data. SG uses cloud to store vast amount of the information
of users. They send their requests of electricity demand and get early responses
of their requests. However, the communication between users and cloud is not
secured. The record maintained about users detail cannot be seen by users.
Users are not able to get access of their own profile history, i.e., demand history
of electricity. So, any malicious person can hack the cloud server and can change
the users data. In result, the users received huge amount of bills. SG is a single
entity to fulfill the electricity demand of consumers. In [36], the authors provide
the facility of P2P trading through DSO between users to divide the load of SG.
However, authorization of users is not considered. Anonymous users can also
become the part of the trading. Moreover, the users are not able to know about
the available amount of electricity from DSO. In [37], authors used Blockchain
for decentralized trading. However, the users purchase electricity on the defined
prices of utility which is considered as one sided market. Users pay taxes to third
party which acts as a communication link between prosumers and consumers.
The data of users is maintained by DSO. However, there is also an issue of
data integrity and confidentiality. In this paper, the Blockchain is implemented
for decentralized and P2P trading between different consumers and prosumers.
Authorized users can just participate through PDA [22] and do negotiation on
prices. They also get access their own previous history of electricity (selling and
buying). If an unauthorized user wants to change the data in Blockchain, or wants
to add any malicious block in the chain the hash of the block will be changed and
a new block is generated. Due to distributed ledger, P2P decentralized trading
and immutable nature, the existing block of data remains same.
3 Proposed System Model
This section describes the methodology adopted for the study. The description
of the system model represents in Fig. 1is given below. This proposed model is
designed by taking motivation from figs in [37].
192 M. Zahid et al.
Profile Login
Authentication
User Layer
Information Layer
Market Layer
PV System
User
Monitors
User Data
Maintain History
SmartGrid
Consumer
Prosumer
Registration
Smart Meter
Two Way
Communication
One Way
Communication
Access
History Smart Grid
Save
Data
Access
History
User User
Market
Mechanism
2.
1.
3.
Fig. 1. System model
Blockchain Based Balancing of Electricity Demand and Supply 193
3.1 User Layer
The user layer contains all the entities who purchase electricity from the market
for the beginning and running of processes that are necessary for routine works.
Prosumers and consumers can directly communicate with each other without
any central party.
They can share their information through blockchain either they want to
sell electricity or they need to buy energy from any prosumer. There is a small
community in which the registered users are able to do trading. All the infor-
mation about available electricity sell and buy can be seen by authorized users.
A home which has PV panel for electricity generation it acts as a prosumer.
When a home has surplus energy after its own usage, then it is able to sell
this surplus energy to those homes which are energy deficient. All those homes
which purchase electricity to fulfil their electricity demand called consumers.
This layer connects with information layer and users provide some information
to get registered themselves for become the part of the network.
3.2 Information Layer
It is a second layer of the system model. It comprises of two parts: registration
and authentication. When a user wants to be a part of this system then, he must
register himself through interface by providing some necessary information his
name, password and email address. In addition to this, the user gets its specific
unique ID and every user has its own profile. All the information of user is saved
on Blockchain and the data stored in the form of hash in block.
In this paper, users are firstly registered themselves and after the authenti-
cation they get access to see the history of their previous usage.
When user enters its unique ID and password, the hash will be calculated and
matched with the copy of the existing hash which is already saved in Blockchain.
If the user can enter wrong ID or password, then the hashes are different and
it does not matched with the already calculated hashes. The system shows a
message or give pop up notification, your ID or password is incorrect.
The users demand and generation of electricity measured from SM details
either this user have surplus amount of energy or energy deficient. On the basis of
this information, the deficient and surplus energy details saved in a blockchain
and it is a distributed ledger. Every user in the blockchain network have the
record of all the transactions happened.
The users demand and generation of electricity measured from SM details
either this user has excess amount of energy or needs energy to buy. On the
basis of this information, the deficient energy and surplus energy details saved
in a blockchain and it is a distributed ledger. Every user in the network have the
record of all the transactions done in the blockchain.
3.3 Market Layer
First of all, the consumer gets login from his unique ID and after that, the
consumers can place their order in an open market according to their requirement
194 M. Zahid et al.
and also their suggested prices for buying and selling. Prosumers give a response
to that consumer who submit its required demand of electricity to buy. The
PDA helds for price negotiation between consumer and prosumer. The price
auction occurs within a specific time slot for one bid. When bidding is done,
then trading occurs. A message is broadcasted in blockchain to SG provides
this amount of electricity to that consumer. Every user is known by its special
account address in blockchain. It provides the required quantity of electricity
to that specific consumer. The transaction cost is deducted for double auction
and for the transfer of electricity from the consumer account. All the data of
sell/purchase is maintained in blockchain through hashes. It is a distributed
ledger which maintains all the records of every transaction in a block. A block
creates when all the transactions are added in it for single bidding. A single
block can store more than one transaction and it depends upon the consensus
mechanism is using in the system. After the generation and validation of a block,
it becomes the part of the chain. The users can also be able to see the history of
their own usage of energy. The history contains all the information of user details
i.e., meter id, amount of electricity demand, electricity sell, electricity buy and
timestamp. SG maintains all the history record of every user. Consumer and
prosumer can access their own history of sell and purchase through profile. They
can also see that how much extra quantity purchased from prosumer, how much
electricity consumed. Blockchain provides transparency and immutability.
In this layer, blockchain used to make the system secure and users access their
own history. SG acts as a prosumer here. SG is connected physically with all the
consumers. So, when the bidding is going to be happen between prosumers and
consumers, for transfer of energy to that specific consumer, then Prosumer sends
message to SG to transfer electricity to a specific consumer. Every prosumer
provides its surplus energy to SG. After the authentication, then user can also
be able to do trading and also get access their own data: how much electricity
sells at which time and at which price. It checks all the buying and selling
transactions. When all the transactions are done then a block is generated and
after the validation of a block, it becomes the part of the chain. Hashes of
transactions are calculated. These hashes are used to verify about the ownership
of sender through its address. Every node in a network has its specific address
and all the nodes in the network are anonymous. So, no one can see the name
or other details of any user, the address of the account is just visible.
For energy trading within a small community, electricity is generated through
PV panels and the PDA mechanism is used. PDA used closed order book system
for trading. A particular clearing price is obtained for every single time slot t.
In this specific time slot, one bidder could be entertained. Consumer can send
their demand of particular amount of electricity and price into the market for
bidding. When prosumers received the order, then they reply their own prices and
quantity for bidding. After that, the prices are matched between both of them.
Then, prosumer sends encrypted message through its SM to SG, provide this
specific amount of electricity to this specific consumer. SG decrypts this message
through the public key of user. The price of per unit of sell/ purchase of electricity
is followed by the tariff price given by utility market. Prosumers cannot send their
Blockchain Based Balancing of Electricity Demand and Supply 195
surplus energy to consumers below the minimum price limit of tariff. Consumers
cannot purchase the electricity per unit more than the maximum price limit
already defined by the utility. Electricity cannot be sell or buy from SG in this
local market. SG is also acts as a prosumer here because it is physically connected
to every SM to provide electricity.
4 Simulations and Results
In this section, the implementation details is based upon an open source platform
of Ethereum blockchain, which inherits some technical features and block cre-
ation after validation. Market mechanism and authentication of users by RBACS
are implemented through smart contracts which are written in solidity language.
The specifications for implementation setup are: intel(R) core (TM) m3-7Y30
CPU@1.61 GHz, 8 GB RAM, 64 bit Operating system and X64-based proces-
sor. The programming language is solidity to write smart contract. Javascript
using for front user interactive form. The tools used to develop this system are
following:
Visual Studio Code: It is an open source editor designed by Microsoft for
different windows and operating systems. It is used for code compilation and
also supports java script for user interface. Ganache: It is a virtual emulator
which has ten addresses of Ethereum accounts and each account contains 100
ethers. It is used as a wallet to test the smart contracts, to run test and to execute
different commands. Meta mask: It is the extension which is added in a browser
to create connectivity between ganache and smart contract for transactions.
For simulations, python language is used and Spyder is used as a tool to
perform all of these results are showing here.
Different graphs are showing about the transaction cost and execution cost of
various smart contracts. Transaction cost is the total gas consumption of sending
data to the blockchain [6]. Transaction gas depends on four things: Base cost of
a transaction is 21000 gas. Base fee is the cost of an operation which retrieve
the sender address from the signature. The minimum deployment cost of the
contract is 32000 gas, zero byte data or cost for a code of transaction and the
cost of nonzero byte of data or the cost for a code of transaction. Execution cost
is also included in a transaction cost. Execution gas is the cost which depends on
the cost of computation operation of every line of code in a function. Basically,
the execution cost is the everything cost which is used as a runtime cost used
for the calling of single method or function.
Figure 2shows the execution and transaction costs of the contract to deploy
and calling of every function. The contract is used to do double auction at which
the global variables call. This graph represents the difference in transaction cost
and execution of every function. The total transaction and execution gas con-
sumed for the deployment of these contract is $0.8541 and $0.4310, respectively.
The different bars show the different amount for execution and transaction gas.
Transaction cost of every function is high because it contains execution cost of
that function and also it contains the deployment of every function in smart
contact (Fig. 3).
196 M. Zahid et al.
Fig. 2. Double sided auction
Fig. 3. Data access
5 Conclusion and Future Work
Blockchain is used to do decentralized trading. Through PDA mechanism, users
are able to purchase electricity according to their own suggested prices. In this
proposed work, authorized users are just able to do trading and also achieved
immutability, decentralization and data security. In this paper, users are also
able to see their own history (buy and sell electricity). Authentic users are just
able to do trading and access their history through interface. Smart contracts
are used to remove third party. PDA is used to do negotiation in prices and pur-
chase electricity according to demand. Gas consumption prices are also analyzed
through calculation of transaction cost and execution cost of smart contracts.
The challenge of this work is limited amount of storage. In future, decentralized
storage is used to store large amount of data on it.
Blockchain Based Balancing of Electricity Demand and Supply 197
References
1. Newbery, D., Strbac, G., Viehoff, I.: The benefits of integrating European electric-
ity markets. Energy Policy 94, 253–263 (2016)
2. Manshadi, S.D., Khodayar, M.E., Abdelghany, K., Uster, H.: Wireless charging
of electric vehicles in electricity and transportation networks. IEEE Trans. Smart
Grid, to be published. http://ieeexplore.ieee.org/document/7837718/
3. Andraeand, A.S.G., Edler, T.: On global electricity usage of communication tech-
nology: trends to 2030. Challenges 6(1), 117–157 (2015)
4. Kabalci, Y.: A survey on smart metering and smart grid communication. Renew.
Sustain. Energy Rev. 57, 302–318 (2016)
5. Salahuddin, M., Alam, K.: Information and communication technology, electricity
consumption and economic growth in OECD countries: a panel data analysis. Int.
J. Elect. Power Energy Syst. 76, 185–193 (2016)
6. Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system (2008)
7. The promise of the blockchain: the trust machine. http://mt.sohu.com/20161021/
n470943606.shtml. Accessed 10 May 2019
8. Yan, Y., Zhao, J.H., Wen, F.S., Chen, X.Y.: Blockchain in energy systems: concept,
application and prospect. Electr. Power Constr. 38(2), 12–20 (2017)
9. Szczerbowski, J.J.: Transaction costs of blockchain smart contracts. Law Forensic
Sci. 16, 2 (2018)
10. Wu, J., Tran, N.: Application of blockchain technology in sustainable energy sys-
tems: an overview. Sustainability 10(9), 3067 (2018)
11. Sikorski, J.J., Haughton, J., Kraft, M.: Blockchain technology in the chemi-
cal industry: machine-to-machine electricity market. Appl. Energy 195, 234–246
(2017)
12. Gao, J., Asamoah, K.O., Sifah, E.B., Smahi, A., Qi Xia, H., Xia, X.Z., Dong,
G.: Gridmonitoring: secured sovereign blockchain based monitoring on smart grid.
IEEE Access 6, 9917–9925 (2018)
13. Luo, F., Dong, Z.Y., Liang, G., Murata, J., Xu, Z.: A distributed electricity trad-
ing system in active distribution networks based on multi-agent coalition and
blockchain. IEEE Trans. Power Syst. 34, 4097–4108 (2018)
14. Morstyn, T., Farrell, N., Darby, S.J., McCulloch, M.D.: Using peer-to-peer energy-
trading platforms to incentivize prosumers to form federated power plants. Nature
Energy 3(2), 94 (2018)
15. Noor, S., Yang, W., Guo, M., van Dam, K.H., Wang, X.: Energy demand side
management within micro-grid networks enhanced by blockchain. Appl. Energy
228, 1385–1398 (2018)
16. Khaqqi, K.N., Sikorski, J.J., Hadinoto, K., Kraft, M.: Incorporating seller/buyer
reputation-based system in blockchain-enabled emission trading application. Appl.
Energy 209, 8–19 (2018)
17. Mengelkamp, E., G¨arttner, J., Rock, K., Kessler, S., Orsini, L., Weinhardt, C.:
Designing microgrid energy markets: a case study: the Brooklyn microgrid. Appl.
Energy 210, 870–880 (2018)
18. Inayat, K., Hwang, S.O.: Load balancing in decentralized smart grid trade system
using blockchain. J. Intell. Fuzzy Syst. 1-11
19. Pop, C., Cioara, T., Antal, M., Anghel, I., Salomie, I., Bertoncini, M.: Blockchain
based decentralized management of demand response programs in smart energy
grids. Sensors 18(1), 162 (2018)
198 M. Zahid et al.
20. Thakur, S., Breslin, J.G.: Peer to peer energy trade among microgrids using
blockchain based distributed coalition formation method. Technol. Econ. Smart
Grids Sustain. Energy 3(1), 5 (2018)
21. Green, J., Newman, P.: Citizen utilities: the emerging power paradigm. Energy
Policy 105, 283–293 (2017)
22. Wang, J., Wang, Q., Zhou, N., Chi, Y.: A novel electricity transaction mode of
microgrids based on blockchain and continuous double auction. Energies 10(12),
1971 (2017)
23. Di Silvestre, M.L., Gallo, P., Ippolito, M.G., Sanseverino, E.R., Zizzo, G.: A techni-
cal approach to the energy blockchain in microgrids. IEEE Trans. Ind. Inf. 14(11),
4792–4803 (2018)
24. Samuel, O., Javaid, N., Awais, M., Zeeshan, A., Imran, M., Guizani, M.: A
blockchain model for fair data sharing in deregulated smart grids. In: IEEE Global
Communications Conference (GLOBCOM 2019) (2019)
25. Rehman, M., Javaid, N., Awais, M., Imran, M., Naseer, N.: Cloud based secure
service providing for IoTs using blockchain. In: IEEE Global Communications Con-
ference (GLOBCOM 2019) (2019)
26. Ali, I., Javaid, N., Iqbal, S.: An incentive mechanism for secure service provision-
ing for lightweight clients based on blockchain, MS thesis, COMSATS University
Islamabad (CUI), Islamabad, Pakistan, July 2019
27. Javaid, A., Javaid, N., Imran, M.: Ensuring analyzing and monetization of data
using data science and blockchain in loT devices, MS thesis, COMSATS University
Islamabad (CUI), Islamabad, Pakistan, July 2019
28. Naz, M., Javaid, N., Iqbal, S.: Research based data rights management using
blockchain over ethereum network, MS thesis, COMSATS University Islamabad
(CUI), Islamabad, Pakistan, July 2019
29. Kazmi, H., Zainab, S., Javaid, N., Imran, M.: Towards energy efficiency and trust-
fulness in complex networks using data science techniques and blockchain, MS
thesis, COMSATS University Islamabad (CUI), Islamabad, Pakistan, July 2019
30. Khan, R.J.H., Javaid, N., Iqbal, S.: Blockchain based node recovery scheme for
wireless sensor networks, MS thesis, COMSATS University Islamabad (CUI),
Islamabad, Pakistan, July 2019
31. Mateen, A., Javaid, N., Iqbal, S.: Towards energy efficient routing in blockchain
based underwater WSNs via recovering the void holes, MS thesis, COMSATS Uni-
versity Islamabad (CUI), Islamabad, Pakistan, July 2019
32. Noshad, Z., Javaid, N., Imran, M.: Analyzing and securing data using data science
and blockchain in smart networks, MS thesis, COMSATS University Islamabad
(CUI), Islamabad, Pakistan, July 2019
33. Shakeri, M., Mohsen Shayestegan, S.M., Reza, S., Yahya, I., Badariah Bais, M.,
Akhtaruzzaman, K.S., Amin, N.: Implementation of a novel home energy manage-
ment system (HEMS) architecture with solar photovoltaic system as supplementary
source. Renew. Energy 125, 108–120 (2018)
34. Bukhsh, R., Javaid, N., Khan, Z.A., Ishmanov, F., Afzal, M., Wadud, Z.: Towards
fast response, reduced processing and balanced load in fog-based data-driven smart
grid. Energies 11(12), 3345 (2018)
35. Liu, Y., Wu, L., Li, J.: Peer-to-peer (P2P) electricity trading in distribution systems
of the future. Electr. J. 32, 2–6 (2019)
36. Park, L., Lee, S., Chang, H.: A sustainable home energy prosumer-chain method-
ology with energy tags over the blockchain. Sustainability 10(3), 658 (2018)
37. Mengelkamp, E., Notheisen, B., Beer, C., Dauer, D., Weinhardt, C.: A blockchain-
based smart grid: towards sustainable local energy markets. Comput. Sci.-Res.
Dev. 33(1–2), 207–214 (2018)
... A centralized system is highly prone to malicious attacks as customer usage, and billing information may be compromised. This can be solved with the help of blockchain, where information is stored on the computers of consumers [5]. ...
... Wang et al. suggested a multi-layered neural network for price forecasting [17]. However, with such a complex network, we gain a high computational time; moreover, the work proposed by M. Zahid et al. shows the loss of neurons is also very high [5]. ...
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Chapter
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Thesis
Full-text available
Decision fusion is used to fuse classification results and improve the classification accuracy in order to reduce the consumption of energy and bandwidth demand for data transmission. Decentralized classification fusion problem was the reason to use belief function based decision fusion approach in Wireless Sensor Networks (WSNs). With the consideration of improving the belief function fusion approach, we have proposed four classification techniques namely Enhanced K-Nearest Neighbor (EKNN), Enhanced Extreme Learning Machine (EELM), Enhanced Support Vector Machine (ESVM), and Enhanced Recurrent Extreme Learning Machine (ERELM). In addition, WSNs are fallible to errors and faults because of their different software, hardware failures, and their deployment in diverse fields. These challenges require efficient fault detection methods to be used to detect faults in WSNs in a timely manner. We induced four type of faults: offset fault, gain fault, stuck-at fault, and out of bounds fault and used enhanced classification methods to solve the sensor failure issues. Experimental results show that ERELM has given the first best result for the improvement of belief function fusion approach. The other three proposed techniques ESVM, EELM, and EKNN have provided the second, third, and fourth best results, respectively. Proposed enhanced classifiers are used for fault detection and are evaluated using three performance metrics ,i.e., Detection Accuracy (DA), True Positive Rate (TPR), and Error Rate (ER). In this thesis, the owner of the (Internet of Thing) IoT device can generate revenueby selling IoT device’s data to interested users. However, on the other hand, users do not trust the owner of IoT device for data trading and are not confident about the quality of data. Traditional data trading systems have many limitations, as they involve third party and lack: decentralization, security and reputation mechanisms. Therefore, in this thesis, we have leveraged the IoTs with blockchain technology to provide trustful data trading through automatic review system for monetizing IoT’s data. We have developed blockchain based review system for IoT data monetization using Ethereum smart contracts. Review system encourages the owner to provide authenticated data and solve the issues regarding data integrity, fake reviews and conflict between entities. Data quality is ensured to users through reviews and ratings about the data, stored in blockchain. To maintain the data integrity, we have used Advanced Encryption Standard (AES)-256 encryption technique to encrypt data. All transactions are secure and payments are automated without any human intervention. Arbitrator entity is responsible to resolve problems between data owner and users. Incentive is provided to users and arbitrator in order to maintain the user participation and honesty. Additionally, Ethereum blockchain system requires gas for every transaction. Simulations are performed for the validation of our system. We have examined our model using three parameters: gas consumption, mining time and encryption time. Simulations show that the proposed methods outperform the existing techniques and give better results for belief function and fault detection in datascience WSNs. Additionally, blockchain based data trading in IoT system requires gas for every transaction. We have examined our model using three parameters: gas consumption, mining time and encryption time.
Thesis
Full-text available
Wireless Sensor Networks (WSNs) are vulnerable to faults because of their deployment in unpredictable and hazardous environments. This makes WSN prone to failure such as software, hardware, and communication failures. Due to the sensor’s limited resources and diverse deployment fields, fault detection in WSNs has become a daunting task. To solve this problem, Support Vector Machine (SVM), Probabilistic Neural Network (PNN), Stochastic Gradient Descent (SGD), Multilayer Perceptron (MLP), Random Forest (RF), and Convolutional Neural Network (CNN) classifiers are used for classification of gain, offset, spike, data loss, out of bounds, and stuck-at faults at the sensor level. Out of six faults, two of them are induced in the datasets, i.e., spike and data loss faults. Likewise, sensors embedded mobile phones are used for the collection of data for some specific task which can effectively save cost and time in Crowd Sensing Network (CSN). The quality of collected data depends on the participation level from all entities of CSN, i.e., service provider, service consumers and data collectors. In comparison with the centralized traditional incentive and reputation mechanisms, we propose a blockchain based incentive and reputation mechanism for CSNs, which mainly consists of three smart contracts. The incentives are used to stimulate the involvement of data collectors and motivate the participants to join the network. Also, the issue of privacy leakage is tackled by using Advanced Encryption Standard (AES128) technique. In addition to that, a reputation system is implemented to tackle the issues like untrustworthiness, fake reviews, and conflicts among entities. Through registering reviews, the system encourages data utilization by providing correct, consistent and reliable data. Furthermore, the results of first scenario are compared on the basis of their Detection Accuracy (DA), True Positive Rate (TPR), Matthews Correlation Coefficients (MCC), and F1-score. In this thesis, a comparative analysis is performed among the classifiers mentioned previously on real-world datasets and simulations demonstrate that the RF algorithm secures a better rate of fault detection than the rest of the classifiers. Similarly, the second scenario is evaluated through analyzing the gas consumption of all the smart contracts, whereas, the encryption technique is validated through comparing the execution time with base paper technique. Lastly, the reputation system is inspected through analyzing the gas consumption and mining time of input string length.
Thesis
Full-text available
Underwater Wireless Sensor Networks (UWSNs) are promising and emerging frameworks having a wide range of applications. The underwater sensor deployment is beneficial; however, some factors limit the performance of the network, i.e., less reliability, high end to end delay and maximum energy dissipation. The provisioning of the aforementioned factors has become a challenging task for the research community. In UWSNs, battery consumption is inevitable and has a direct impact on the performance of the network. Most of the time energy dissipates due to the creation of void holes and imbalanced network deployment. In this work, two routing protocols are proposed to avoid the void hole and extra energy dissipation problems due to which lifespan of the network will increase. To show the efficacy of the proposed routing schemes, they are compared with the state of the art protocols. Simulation results show that the proposed schemes outperform their counterpart schemes. By keeping in mind the emerging security issues in sensor networks, we have proposed a blockchain based trust model for sensor networks to enrich the security of the network. Additionally, this model provides security along with data immutability. We have used a private blockchain because it has all the security features that are necessary for a private sensor network. Moreover, private blockchain cannot be accessed by using the Internet. In the proposed trust model, the Proof of Authority (PoA) consensus algorithm is used due to its low computational power requirement. In PoA consensus mechanism, a group of the validator is selected for adding and maintaining blocks. Moreover, smart contracts are used to validate and transfer cryptocurrency to service providers. In the end, transaction and execution costs are also calculated for each function to testify the network suitability.
Thesis
Full-text available
In a research community, data sharing is an essential step to gain maximum knowledge from the prior work. Existing data sharing platforms depend on trusted third party (TTP). Due to involvement of TTP, such systems lack trust, transparency, security and immutability. To over come these issues, this thesis proposed a blockchain based secure data sharing platform by leveraging the benefits of interplanetary file system (IPFS). A meta data is uploaded to IPFS server by owner and then divided into n secret shares. The proposed scheme achieves security and access control by executing the access roles written in smart contract by owner. Users are first authenticated through RSA signatures and then submit the requested amount as a price of digital content. After the successful delivery of data, a user is encouraged to register reviews about data by announcing customer incentives. In this way, maximum reviews are submitted against every file. In this scenario, decentralized storage, Ethereum blockchain, encryption and decryption schemes and incentive mechanism are combined. To implement the proposed scenario, smart contracts are written in solidity and deployed on local Ethereum test network. The proposed scheme achieves transparency, security, access control, authenticity of owner and quality of data. In simulation results, an analysis is performed on gas consumption and actual cost required in terms of USD, so that a good price estimate can be done while deploying the implemented scenario in real setup. Moreover, computational time for different encryption schemes are plotted to represent the performance of implemented scheme, which is shamir secret sharing (SSS). Results show that SSS shows least computational time as compared to advanced encryption standard (AES) 128 and 256.
Thesis
Full-text available
Decision fusion is used to fuse classification results and improve the classification accuracy in order to reduce the consumption of energy and bandwidth demand for data transmission. Decentralized classification fusion problem was the reason to use belief function based decision fusion approach in Wireless Sensor Networks (WSNs). With the consideration of improving the belief function fusion approach, we have proposed four classification techniques namely Enhanced K-Nearest Neighbor (EKNN), Enhanced Extreme Learning Machine (EELM), Enhanced Support Vector Machine (ESVM), and Enhanced Recurrent Extreme Learning Machine (ERELM). In addition, WSNs are fallible to errors and faults because of their different software, hardware failures, and their deployment in diverse fields. These challenges require efficient fault detection methods to be used to detect faults in WSNs in a timely manner. We induced four type of faults: offset fault, gain fault, stuck-at fault, and out of bounds fault and used enhanced classification methods to solve the sensor failure issues. Experimental results show that ERELM has given the first best result for the improvement of belief function fusion approach. The other three proposed techniques ESVM, EELM, and EKNN have provided the second, third, and fourth best results, respectively. Proposed enhanced classifiers are used for fault detection and are evaluated using three performance metrics ,i.e., Detection Accuracy (DA), True Positive Rate (TPR), and Error Rate (ER). In this thesis, the owner of the (Internet of Thing) IoT device can generate revenueby selling IoT device’s data to interested users. However, on the other hand, users do not trust the owner of IoT device for data trading and are not confident about the quality of data. Traditional data trading systems have many limitations, as they involve third party and lack: decentralization, security and reputation mechanisms. Therefore, in this thesis, we have leveraged the IoTs with blockchain technology to provide trustful data trading through automatic review system for monetizing IoT’s data. We have developed blockchain based review system for IoT data monetization using Ethereum smart contracts. Review system encourages the owner to provide authenticated data and solve the issues regarding data integrity, fake reviews and conflict between entities. Data quality is ensured to users through reviews and ratings about the data, stored in blockchain. To maintain the data integrity, we have used Advanced Encryption Standard (AES)-256 encryption technique to encrypt data. All transactions are secure and payments are automated without any human intervention. Arbitrator entity is responsible to resolve problems between data owner and users. Incentive is provided to users and arbitrator in order to maintain the user participation and honesty. Additionally, Ethereum blockchain system requires gas for every transaction. Simulations are performed for the validation of our system. We have examined our model using three parameters: gas consumption, mining time and encryption time. Simulations show that the proposed methods outperform the existing techniques and give better results for belief function and fault detection in datascience WSNs. Additionally, blockchain based data trading in IoT system requires gas for every transaction. We have examined our model using three parameters: gas consumption, mining time and encryption time.
Thesis
Full-text available
Wireless Sensor Networks (WSNs) are vulnerable to faults because of their deployment in unpredictable and hazardous environments. This makes WSN prone to failure such as software, hardware, and communication failures. Due to the sensor’s limited resources and diverse deployment fields, fault detection in WSNs has become a daunting task. To solve this problem, Support Vector Machine (SVM), Probabilistic Neural Network (PNN), Stochastic Gradient Descent (SGD), Multilayer Perceptron (MLP), Random Forest (RF), and Convolutional Neural Network (CNN) classifiers are used for classification of gain, offset, spike, data loss, out of bounds, and stuck-at faults at the sensor level. Out of six faults, two of them are induced in the datasets, i.e., spike and data loss faults. Likewise, sensors embedded mobile phones are used for the collection of data for some specific task which can effectively save cost and time in Crowd Sensing Network (CSN). The quality of collected data depends on the participation level from all entities of CSN, i.e., service provider, service consumers and data collectors. In comparison with the centralized traditional incentive and reputation mechanisms, we propose a blockchain based incentive and reputation mechanism for CSNs, which mainly consists of three smart contracts. The incentives are used to stimulate the involvement of data collectors and motivate the participants to join the network. Also, the issue of privacy leakage is tackled by using Advanced Encryption Standard (AES128) technique. In addition to that, a reputation system is implemented to tackle the issues like untrustworthiness, fake reviews, and conflicts among entities. Through registering reviews, the system encourages data utilization by providing correct, consistent and reliable data. Furthermore, the results of first scenario are compared on the basis of their Detection Accuracy (DA), True Positive Rate (TPR), Matthews Correlation Coefficients (MCC), and F1-score. In this thesis, a comparative analysis is performed among the classifiers mentioned previously on real-world datasets and simulations demonstrate that the RF algorithm secures a better rate of fault detection than the rest of the classifiers. Similarly, the second scenario is evaluated through analyzing the gas consumption of all the smart contracts, whereas, the encryption technique is validated through comparing the execution time with base paper technique. Lastly, the reputation system is inspected through analyzing the gas consumption and mining time of input string length.
Conference Paper
Full-text available
Wireless Sensor Network (WSN) is a network of nodes connected through a wireless channel. The sensor nodes in the network are resource-constrained in terms of energy, storage and computational power. Node failure is a common phenomenon , which occurs due to environmental factors, adversary attacks, draining of battery power, etc. After node failure, recovery is challenging that needs a strong mechanism. In this paper, Blockchain based Node Recovery (BNR) scheme for WSNs is proposed. In BNR scheme, recovery of failed nodes is on the basis of node degree. The working mechanism of the scheme is that, first the failed nodes are detected using state (active or inactive) of the Cluster Heads (CHs). In the second phase, the recovery process is initiated for inactive nodes. The main purpose at this step is to recover the failed CH, which will ultimately result in restoring the active states of its member nodes. NodeRecovery Smart Contract (SC) is written for the purpose. Furthermore, cost analysis for NodeRecovery is performed. Also, security analysis for the proposed scheme is performed to assure the security. Simulation results show the effectiveness of the proposed model. 1 Background Wireless Sensor Network (WSN) has attracted extensive attention of researchers in recent times. It consists of several sensor nodes, working collectively to monitor the environmental conditions: temperature, humidity, sound and pollution levels. This data is then stored at a central location, which is termed as the sink or the base station. Such nodes have a microcontroller, radio transceiver, wireless communicating devices and an energy source (battery). The nodes have limited energy,
Conference Paper
Full-text available
Internet of Things (IoTs) is widely growing domain of the modern era. With the advancement in technologies, the use of IoTs devices also increases. However, security risks regarding service provisioning and data sharing also increases. There are many existing security approaches, although these approaches are not suitable for IoT devices due to their limited storage and limited computation resources. These secure approaches also require a specific hardware. With the invention of blockchain technologies, many security risks are eliminated. With the help of blockchain, data sharing mechanism is also possible. In this paper, we proposed a novel secure service providing mechanism for IoTs by using blockchain. We introduced cloud nodes for maintaining the validity states of edge service providers. The rating and cryptocurrency is given to edge servers. Given rating and incentive is stored in cloud node and updated with respect to time. The smart contract is proposed to check the validity state of the edge server as well as compare and verify the service provided by edge servers. In our proposed system we perform service authentication at cloud layer as well as edge server layer. Moreover, by using Proof of Authority (PoA) consensus mechanism overall performance of our proposed system also enhanced.By experimental analysis it is shown, our proposed model is suitable for resource constrained devices.
Conference Paper
Full-text available
The emergence of smart homes appliances has generated a high volume of data on smart meters belonging to different customers which, however, can not share their data in deregulated smart grids due to privacy concern. Although, these data are important for the service provider in order to provide an efficient service. To encourage customers participation, this paper proposes an access control mechanism by fairly compensating customers for their participation in data sharing via blockchain and the concept of differential privacy. We addressed the computational issues of existing ethereum blockchain by proposing a proof of authority consensus protocol through the Pagerank mechanism in order to derive the reputation scores. Experimental results show the efficiency of the proposed model to minimize privacy risk, maximize aggregator profit. In addition, gas consumption, as well as the cost of the computational resources, is reduced. Index Terms-Blockchain, consensus mechanism, proof of authority, privacy preserving and smart grid. I. INTRODUCTION Presently, because of the rapid growth of the world population and the technological innovations, a lot of energy is needed in a short period of time and during peak hours, and its effect increases the cost of production. Customers can, therefore, optimize their utilization based on the current energy demand and supply. As a result, demand response and dynamic pricing proposal are subject to privacy issues. In a smart grid, customers will share their hourly information load profile with a service provider only to allow a certain level of privacy to be maintained, which is a major barrier for customer participation. In order to efficiently aggregate customer data, while preserving their privacy, Liu et al. [1] propose a privacy-preserving mechanism for data aggregation. The proposed solution minimizes the cost of communication and computational overhead. However, a trusted environment is not considered. To achieve a trusted environment, several studies in [2]-[8] used blockchain as privacy-preserving mechanism for data aggregation; privacy protection and energy storage; secure classification of multiple data; incentive announcement network for smart vehicle; crowdsensing applications; dynamic tariff decision and payment mechanism for vehicle-to-grid. A survey concerning privacy protection using blockchain is discussed in [9]. The survey highlights all the existing