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With the integration of Wireless Sensor Networks and the Internet of Things, the smart grid is being projected as a solution for the challenges regarding electricity supply in the future. However, security and privacy issues in the consumption and trading of electricity data pose serious challenges in the adoption of the smart grid. To address these challenges, blockchain technology is being researched for applicability in the smart grid. In this paper, important application areas of blockchain in the smart grid are discussed. One use case of each area is discussed in detail, suggesting a suitable blockchain architecture, a sample block structure and the potential blockchain technicalities employed in it. The blockchain can be used for peer-to-peer energy trading, where a credit-based payment scheme can enhance the energy trading process. Efficient data aggregation schemes based on the blockchain technology can be used to overcome the challenges related to privacy and security in the grid. Energy distribution systems can also use blockchain to remotely control energy flow to a particular area by monitoring the usage statistics of that area. Further, blockchain-based frameworks can also help in the diagnosis and maintenance of smart grid equipment. We also discuss several commercial implementations of blockchain in the smart grid. Finally, various challenges to be addressed for integrating these two technologies are discussed.
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Blockchain in Smart Grids: A Review on Different
Use Cases
Tejasvi Alladi 1, Vinay Chamola 1, Joel J. P. C. Rodrigues 2,3,4,and Sergei A. Kozlov 4
1Birla Institute of Technology and Science, Pilani 333031, India; (T.A.); (V.C.)
2Federal University of Piauí, Teresina-PI 64049-550, Brazil
3Instituto de Telecomunicações, 1049-001 Lisboa, Portugal
4International Institute of Photonics and Optoinformatics, ITMO University, St. Petersburg 197101, Russia;
Received: 30 September 2019; Accepted: 4 November 2019; Published: 8 November 2019
With the integration of Wireless Sensor Networks and the Internet of Things, the smart
grid is being projected as a solution for the challenges regarding electricity supply in the future.
However, security and privacy issues in the consumption and trading of electricity data pose serious
challenges in the adoption of the smart grid. To address these challenges, blockchain technology is
being researched for applicability in the smart grid. In this paper, important application areas of
blockchain in the smart grid are discussed. One use case of each area is discussed in detail, suggesting
a suitable blockchain architecture, a sample block structure and the potential blockchain technicalities
employed in it. The blockchain can be used for peer-to-peer energy trading, where a credit-based
payment scheme can enhance the energy trading process. Efficient data aggregation schemes based
on the blockchain technology can be used to overcome the challenges related to privacy and security
in the grid. Energy distribution systems can also use blockchain to remotely control energy flow to a
particular area by monitoring the usage statistics of that area. Further, blockchain-based frameworks
can also help in the diagnosis and maintenance of smart grid equipment. We also discuss several
commercial implementations of blockchain in the smart grid. Finally, various challenges to be
addressed for integrating these two technologies are discussed.
blockchain; smart grid; Internet of Things; security and privacy; Peer-to-Peer trading;
Wireless Sensor Networks
1. Introduction
Smart grids are currently advancing technologically at a very fast pace by leveraging the benefits
offered by Wireless Sensor Networks (WSNs) and the Internet of Things (IoT). They offer optimization
in energy production and consumption by the adoption of intelligent systems that can monitor and
communicate with each other [
]. Automation of the smart sensor-based metering system by using
Advanced Metering Devices (AMI) leads to a lesser requirement of manpower and more accuracy.
Thus, by making the grid more intelligent, efficient energy utilization is achieved [
]. Smart grids
also promise more efficient tapping of renewable sources of energy by offering technological support
for the transfer of energy between local energy producers and consumers. The consumers who
can harvest renewable sources of energy such as sunlight using rooftop solar panels can become
producers-cum-consumers (prosumers) by selling their surplus energy either to neighboring consumers
or to the grid. This promotes consumers to utilize renewable sources of energy [
]. Since the energy
demand is ever-growing and there are multiple sources of energy, the need for a decentralized
Sensors 2019,19, 4862; doi:10.3390/s19224862
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energy management system has arisen [
]. The system should be able to manage the individual
transactions between the users as well as between the user and the grid without any tampering
of data or loss of information. Integrating distributed renewable energy resources whose power
generation is highly fluctuating makes it very challenging for the utilities to estimate the state of
the system. Some
works [810]
have proposed novel Kalman filter-based approaches for accurate
microgrid state estimation and control for the smart grids. Their models encourage consumers to use
environment-friendly renewable energy sources which will lead to many benefits such as line-loss
reduction, reliability, energy efficiency, etc. The authors of [
] discussed energy demand reduction
of the utilities and consumers and smart energy management while considering the ever-growing
renewable energy integration. Another issue that hinders an efficient grid management system is the
requirement of third parties for the supply and distribution of energy. Third-party involvement always
increases the cost of operation drastically and paves the way for erroneous transactions, intentionally
or otherwise. This is where blockchain offers a promising solution to these existing issues of the smart
grid [12,13].
The adoption of blockchain technology allows the grid network to decentralize its operations.
That means the decision making and the transaction flows do not need to be channeled through
a centralized system that is inclusive of third parties, e.g., mediators, banks, etc. The record of
transactions is stored in all or selected nodes involved in the operation of the network depending on the
type of blockchain used [
]. The transactions of buying and selling of energy across users no longer
needs to go through the procedures of a bank but rather can be done through a computer program by
validating the required pre-determined clauses of the transaction [
]. Blockchain technology among
various other benefits helps in setting up real-time energy markets and identity preserving transactions
at much lower costs due to a simplified trading
framework [17,18]
. The computation and power
consumption of IoT devices are important challenges restricting the application of blockchain in IoT
and smart grid. The authors of [
] proposed a decentralized on-demand energy supply architecture
for miners in the IoT network, using microgrids to provide renewable energy for mining in the IoT
devices. This paper identifies some of the various scenarios in which blockchain can be incorporated
in the smart grid, and discusses the various technological aspects about each scenario.
The main contributions of this paper are:
We discuss major applications of blockchain in smart grids, giving details such as blockchain
architecture, sample block structure and blockchain-related technologies employed in each
application area.
A table summarizing these application areas with important technical details is also presented
after a discussion of the application areas.
We then discuss commercial implementations of blockchain in the smart grid.
We also discuss existing challenges for incorporating blockchain into the smart grid and present
some future research directions.
The rest of the paper is organized as follows. Section 2gives a brief overview of blockchain
technology. In Section 3, important application areas of blockchain in the smart grid are discussed.
Section 4summarizes several commercial implementations of blockchain in the energy sector.
In Section 5
, practical challenges in the incorporation of blockchain into the smart grid are discussed.
Section 6suggests some future research directions. Finally, the paper is concluded in Section 7.
2. Blockchain Overview
Blockchain is a decentralized ledger meant for keeping a record of the various transactions carried
out in the network right from the beginning of the chain. The ledger is shared among different
nodes (also referred to as peers) that participate in the network, with each peer having its copy of
the ledger. Each block in the chain is connected to the previous one using cryptographic techniques,
which makes the system secure and resistive to malicious attacks and malpractices, as illustrated in
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Figure 1. Each node can check for the validity of the transactions and reach a consensus before adding
the block to the blockchain, thus providing a high level of transparency and reliability.
Previous Block Hash
Target Diff.
Merkle Root Hash
Block Body
Block Header
Block 1
Previous Block Hash
Target Diff.
Merkle Root Hash
Block Body
Block Header
Block 2
Previous Block Hash
Target Diff.
Merkle Root Hash
Block Body
Block Header
Block 3
Previous Block Hash
Target Diff.
Merkle Root Hash
Block Body
Block Header
Block 4
Figure 1. Blockchain structure.
2.1. Composition of Blockchain
Each transaction in a blockchain is verified by the participating nodes using a consensus algorithm
and, if a consensus is reached upon its validity by the nodes, the transaction data are stored into
structures called blocks. Mining is the addition of the blocks into the blockchain while the Miners or
the Mining Nodes are the nodes involved in this process. A cryptographic hash function [
] links any
two adjacent blocks in the blockchain, with the hash of the previous block stored in the current block.
To carry out a successful attack, the attacker trying to modify a particular block in the blockchain has
to ensure that all the following blocks are also modified. Since the hash of the current block is stored
in the next block, modifying any field of the current block will also modify its hash. Thus, the older
the target block is, more challenging it is for an attacker to modify and update the block and all the
succeeding blocks until the newest block in the blockchain. Furthermore, the attacker also has to
ensure that no new block has been added into the blockchain by the time his changes are reflected in
the blockchain. This requires a much higher processing and hashing capability on the attacker’s end
compared to the combined capability of all the miners. Therefore, such an attack on the blockchain
network remains economically quite infeasible. In addition, since a copy of the complete blockchain is
available with each participating node of the network, any malpractice such as modification of a block
of the blockchain can be easily detected. These cryptographic security techniques thus provide data
immutability to the blockchain. Each block essentially comprises of a block header and a block body.
The block header contains various fields such as the previous hash, timestamp, etc. The timestamp
indicates the time of the creation of a block. Version denotes the type and format of data contained
in the block while the Merkle root hash is the combined hash of all the transactions that have been
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added into that block. Merkle trees are generated by iteratively hashing pairs of transactions until
there is only one hash value left. The single hash value is called the Merkle root. Merkle root is the
digital fingerprint of all the transactions stored in a particular block. Using a Merkle root, a user can
securely and efficiently verify the presence of a particular transaction in a block. A nonce is an arbitrary
number used by the mining nodes to change the block’s hash value to satisfy the consensus criterion
of a blockchain. The block body comprising of the transaction information related to the block can be
divided into two parts. The first part of the block stores information about the transactions (amount,
date, time, etc.), whereas the other part stores information about the participants of the transactions.
All blocks are connected to form a chain having information about the transaction history of the whole
network and are shared with the whole network [2124].
2.2. Classification of Blockchains
Blockchains are generally classified into three types, namely public, consortium and private
blockchain. A comparison of these three types based on different parameters is summarized in Table 1.
Table 1. Classification of blockchains [2531].
Parameter Public Blockchain Consortium
Blockchain Private Blockchain
Receptivity Fully open Open to some nodes
Open to a person/entity
Access to Write Anyone Specific nodes Internally controlled
Access to Read Anyone Anyone Open to the public
Obscurity More Less Less
Speed of Transaction Low High Extremely high
Decentralization Fully decentralized Less decentralized Less decentralized
3. Applications of Blockchain in Smart Grid
Figure 2lists important applications of blockchain in the smart grid scenario. Based on the
existing surveys and reviews on blockchain applicability in IoT [
], in this paper, we focus on
these five important application areas in smart grids where blockchain technology has been extensively
researched. Each of these application areas is discussed below giving details of the blockchain
architecture employed, the structure of a sample block and the different blockchain technologies used.
Use Cases of Blockchain
in Smart Grid
Energy Trading
Energy Trading
in Electric Vehicles
Security and Privacy
Preserving Techniques
Power Generation
and Distribution
Secure Equipment
   Maintenance for  
Smart Grids
Figure 2. Applications of blockchain in smart grid.
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3.1. Peer-To-Peer Trading Infrastructure
A major drawback in the existing grid networks is the lack of security regarding the transactions
caused by the involvement of mediators and other third parties. This hierarchical organizational
trading structure of the grid leads to heavy operating costs with low efficiency of operation [
On the other hand, a blockchain-based trading infrastructure offers a decentralized platform that
enables the Peer-to-Peer (P2P) trade of energy between consumers and prosumers in a secure manner.
The identity privacy and security of transactions is higher in the decentralized platform compared
to the traditional system. The P2P energy trade finds purpose in many applications including the
Industrial Internet of Things (IIoT) and enhances the possibility of developing micro-grids leading to
sustainable energy utilization [
]. The UK based Energy Networks Association has declared the
plan to invest 17 billion Euros in the local energy markets using the smart grid [
]. Various aspects of
P2P energy trade using blockchain are discussed below.
3.1.1. Blockchain Architecture
Based on the various state-of-the-art research works surveyed on P2P energy trading infrastructure
using blockchain, the blockchain architecture for a typical P2P energy trading system can be shown
as in Figure 3. This architecture is based on the reference model used in [
], in which the authors
used a consortium blockchain-based secure P2P energy trading system. A comparison of several such
research works is shown in Table 2. Depending on the market scenario, the required computational
power and the speed of transactions, the decision regarding the choice of blockchain type to be used
can vary.
Energy coins / Tokens
Energy buyers
Energy sellers
Energy blockchain
Figure 3. Architecture for P2P energy trading.
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Table 2. Comparison of state-of-the-art research papers on P2P energy trading using blockchain.
Ref. Cost and Energy
Secure against
Analysis Scalable Performance
3 3 7 7 7 7
3 3 7 7 3 7
7 7 3 7 3 3
3 3 7 7 3 3
3 3 3 3 3 3
A public blockchain gives a high level of transparency by providing a copy of the distributed
ledger to each node, and the ability to perform consensus and validation of data. However,
the disadvantage comes in the form of energy consumption and performance. A consortium blockchain,
on the other hand, allows only a set of pre-authorized nodes to handle the distributed ledger or
the transaction database. Only these authorized nodes are allotted high computational capabilities
required to solve the consensus algorithm thereby reducing the overall power consumption and
facilitating faster transactions. The authors of [
] proposed a consortium blockchain platform for
facilitating a secure P2P system for energy trade in IIoT, called energy blockchain. The different energy
nodes comprising of small scale consumers, industrial consumers, electric vehicles, etc. are given the
flexibility to choose their roles as buyers/sellers or idle nodes can initiate transactions according to
their requirement. A record of these transactions is stored and managed by a special authorized set of
entities called Energy Aggregators (EAGs).
3.1.2. Block Structure
In the case of P2P energy transfer, a typical block in the blockchain network, as shown in
Figure 4, consists of data structures that include information regarding the amount of energy used
and the timestamp indicating the usage of energy usually dealing with a particular transaction [
The number of structures and the data included depends on the architecture adopted.
Block ID
Lock Time
Block n TID
Block n+2
Block n+1
Block n
Block n-1
Block n-2
Figure 4. Block structure for P2P energy trading.
In a consortium blockchain with predefined processing and consensus nodes, the block structure
consists of the Block ID for unique identification; Header, which is hashed with a Secure Hash
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Algorithm (SHA); Lock Time, which indicates the time of addition of that particular block into the
network; and the transactions. Each transaction is generated when the buyer requests energy from the
transaction servers of the supervisory nodes. The transaction part of the block structure consists of data
specific to each transaction such as Transaction ID (TID), Meter ID (MID), Amount of Energy Requested
(AER), Amount of Energy Granted (AEG) for the requesting buyer by the supervisory nodes based on
the available energy from the sellers, Energy coins Transferred (ET) by the buyer for the transaction,
Digital Signature of the Seller (DSS) indicating a successful transaction, and Digital Signature of the
Processing node (DSP) indicating validation of the transaction. It also includes timestamps indicating
Time of Request (TR) and Time taken for Transaction (TT).
3.1.3. Technologies Used
Virtual currency: Using blockchain, a virtual currency can be created for representing each unit
of electricity. This system is highly useful in situations where renewable energy is generated
at the prosumer’s end. Surplus energy available to the prosumer can be sold by engaging in
transactions with other peers within the blockchain network and transferring this electrical energy
into the grid. The prosumer can earn virtual currency for the energy sale at a specified price while
the consumers with deficit can buy energy for their requirement with the virtual currency. The
true identity of both the buyer and the seller do not need to be disclosed in such transactions
using virtual coins [
]. Further, incentive schemes can be introduced for the promotion of
renewable energy. A set of peers who contribute the most to the trade of renewable energy can
be chosen by monitoring the transaction history from the blockchain ledgers and rewarded with
virtual currencies.
Credit-based transactions: Since there is some latency in the validation and addition of transactions
into the blockchain, which in turn delays the release of virtual currency for the respective user,
users might face a shortage of virtual currency temporarily. A credit-based transaction system
helps such users in purchasing the required energy without actual possession of virtual currencies
at that moment. Li et al.
utilized a credit-based payment scheme where each node is allotted
an identity, a set of public and private keys, a certificate for unique identification, and a set of
wallet addresses upon a legitimate registration onto the blockchain. Upon initialization, the
wallet integrity is checked and its credit data are downloaded from the memory pool of the
supervisory nodes (which store records on credit-based payments). The request from each node
for the release of credit-based tokens is validated by the credit bank managed by the supervisory
nodes and released if the requesting node meets the specified criteria. These tokens which are
then transferred to the wallet of the node can be used to buy the required energy from other
selling nodes [39,47].
Smart contracts: These are computer codes consisting of terms of agreements under which the
parties involved should interact with each other. They are finite state machines that implement
some predefined instructions upon meeting a particular set of conditions or certain specified
actions. Smart contracts associated with the smart meters in the grid are deployed in the
blockchain. They ensure secure transactions by allowing only authentic data transfers between the
smart meters and the supervisory nodes and report if any unauthorized and malicious tampering
of data has occurred [47,48].
3.2. Energy Trading in Electric Vehicles
Electric vehicles (EVs) play an important role in the smart grid infrastructure for distributed
renewable energy transportation [
]. There can be two sources to charge the EVs: using
vehicle-to-grid (V2G) and vehicle-to-vehicle (V2V) trading. In V2V trading, EVs can trade electricity in
the hotspots (charging stations or parking lots) in a P2P manner, where the discharging vehicles (with
surplus electricity) discharge their energy to fulfill the electricity demand of the charging vehicles
and thus balance the electricity supply–demand equilibrium. However, due to privacy concerns,
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discharging EVs tend to be reluctant to participate in the electricity trading market and consequently
the supply and demand equilibrium among EVs becomes unbalanced. These problems with the
traditional centralized electricity trading schemes which rely on intermediary parties are discussed
in [
]. Hence, there is a need to provide a secure electricity trading system that is decentralized and
preserves privacy for EVs during the electricity trade.
3.2.1. Blockchain Architecture
A blockchain-based solution to trade electricity brings with it the advantages of security,
decentralization, and trust. A system known as PETCON is designed by the authors of [
] to achieve
secure trading of electricity. Among the other existing works on energy trade in EVs, this architecture
is not only shown to be secure against cybersecurity attacks but also shown to be cost-optimized and
scalable for multiple nodes, as shown in Table 3. Further, it is based on the P2P architecture discussed
in the previous section on the P2P energy trade. Consortium blockchain technology is used here
because of the cost advantage compared to the existing blockchain methods employed in electricity
trading. Based on this model, a generic architecture for electricity trading among EVs is shown in
Figure 5.
Local Aggregator 1
Local Aggregator
Energy Buffer
Energy Buffer
Discharging PHEVs
Social Hotspot 2
Charging PHEVs
Social Hotspot 1
Energy Coin DataEnergy ASmart Meter Switch
Energy Coins
Social Hotspot 1 Social Hotspot 2
Energy Coins
Energy Blockchain
Figure 5. Architecture for energy trading in electric vehicles.
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Table 3.
Comparison of state-of-the-art research papers on energy trading in Electric vehicles (EVs)
using blockchain.
Ref. Cost and Energy
Secure against
Analysis Scalable Performance
7 7 3 7 3 3
3 3 7 7 7 7
3 3 3 3 3 7
3 3 3 3 3 3
The EVs in this system are divided into three categories as follows:
Discharging EVs, which sell surplus energy.
Charging EVs, which demand energy.
Idle EVs, which neither demand nor sell energy.
An EV joins the system after registering itself with the trusted authority and chooses its role
as a discharging/charging EV as per its current energy states and the future energy requirements.
The charging EV sends a request to the EAG, which broadcasts its demand to the discharging EVs.
Upon receiving their responses, the EAG performs bidding and transactions among the EVs. The
payment of energy coins is made by the charging EV to the discharging EV’s wallet address, which
verifies it using the last block in the memory pool of the EAG. The fastest EAG is considered as the
leader of the consensus process and sends data and timestamp of the block along with the PoW to other
EAGs for verification and auditing. Only when all the EAGs reach an agreement are the data stored as
a block in the blockchain. Since a consortium blockchain is being used here, the number of nodes in the
network is not expected to grow a lot unlike in a public blockchain. For networks with the exponential
growth of nodes, running PoW will require high energy consumption. Instead, other consensus
algorithms such as Proof-of-Stake (PoS) [
], Proof-of-Burn (PoB) [
] and Proof-of-Elapsed-Time
(PoET) [58] may be run.
The various entities used in the energy blockchain are discussed here. Borrowers are the energy
buyers borrowing energy coins from the credit banks. Transaction Servers (TS) are responsible for
collecting and counting the energy requests and matching the transaction pairs for energy trading.
Wallets are the entities that store the energy coins. Account pools (AP) are the entities that record the
wallets, the energy coin accounts, and the wallet addresses. The transaction records of the local EVs
are stored in the Memory Pools (MP). Credit banks are the entities through which borrowers borrow
energy coins based on their credit values.
3.2.2. Block Structure
Information about the traded electricity and the transaction records of the digital assets are stored
in a block of this blockchain. The transaction records are collected and managed by the local energy
aggregators (EAGs). These records are encrypted, signed with digital signatures and audited by
the rest of the EAGs using the consensus algorithm, PoW. The block structure is shown in Figure 6.
The first is PoW for EAGs, in which data auditing by authorized EAGs is done. Various EAGs compete
for the creation of blocks by finding PoW and the fastest one audits the transaction records and puts in
the block which is verified by other EAGs. Secondly, PoW for EVs is the amount of energy sold by that
EV, which is measured and recorded by the built-in smart meters.
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Block b-1
Block b+1
Block b
Block ID
Lock Time
Block b
Transaction ID
Energy transferred
Digital signature
of sellers
Digital signature
of LAGs
Figure 6. Block structure of energy trading in electric vehicles.
3.2.3. Technologies Used
Smart contracts: These are used for the commitment from the charging EVs before the local
aggregator (LAG) makes the contract with the discharging EVs. A deal is formed, which includes
the rates for the purchase of battery and discounts for charging and parking. Breaking the terms of
contracts will lead to penalties. Smart contracts are used for registering the EVs and for securing
the energy trade (e.g., detection of malpractices).
Digital currency: The NRGcoin is the digital currency used in energy trading between the EVs.
After the trading of electricity, there will be a transfer of NRGcoins from the wallet of charging EV
to the discharging EV’s wallet address.
Double auction mechanism: Double auction mechanism is used for energy negotiation, bidding,
and transactions between the EVs. This mechanism is used for price optimization and also
for optimizing the electricity units traded between EVs, thus maximizing social welfare along
with the privacy protection of EVs. LAG acts as an auctioneer and performs this mechanism
iteratively according to the selling prices of discharging EVs and buying prices of charging EVs.
The auctioneer will determine the final prices of the trading and the amount of electricity to be
traded, which will be useful to protect the EV information during the electricity trade [51].
3.3. Security and Privacy-Preserving Techniques
Smart meters in the smart grid are placed at every house to get information about electricity
consumption in real-time, which is used by the utilities for various purposes [
]. By analyzing
the electricity consumption profile of the users, malicious entities can track the electricity usage
pattern, thereby disclosing the users’ private information [
]. The authors of [
] proposed a
blockchain-based scheme for efficient data aggregation and privacy preservation. In their work, they
divided the users into many groups with each group using a blockchain for recording the users’ data.
Bloom filter is used by the scheme for fast authentication, to facilitate a quick check of the legality of
the user ID in the system. For the preservation of privacy within the group, pseudonyms are used by
the users. Although blockchain technology does not directly ensure privacy preservation, advanced
cryptographic mechanisms can be incorporated for enabling data privacy. Zero knowledge proof
(ZKP), Elliptic Curve Digital Signature Algorithm (ECDSA), and linkable ring signatures are some
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of the techniques which can protect the privacy of the devices involved. The privacy-preserving
blockchain architecture discussed here makes use of ZKP combined with pseudonyms for the users.
3.3.1. Blockchain Architecture
A typical blockchain-based architecture for the data aggregation scheme is described in Figure 7.
This is based on the reference model presented by Guan et al.
. We present a comparison of
blockchain-based state-of-the-art research works done on security and privacy-preserving techniques
in the smart grid in Table 4. Based on electricity consumption, users are divided into various
groups/neighborhood area networks (NANs). Multiple public and private key pairs are generated
by the key management center (KMC) for every user using RSA, a popular public-key cryptography
algorithm, with the pseudonym of the user being the public key. By collecting the pseudonyms, the
bloom filter is created by the KMC for every group and sent to all the users of the corresponding group.
The authenticity of the user pseudonym can be verified using zero-knowledge proof, a probabilistic
verification method in cryptography. At every time slot, a mining node is selected among the users of
the group based on the average consumption of the electricity data. The mining node aggregates the
electricity data consumed, records them in a private blockchain and sends it to the central unit with
the help of wide-area network (WAN). The central unit can extract the electricity consumption profile
in real-time for energy planning and dynamic pricing. The billing center on the arrival of the billing
date calculates the users’ electricity bill and records it in the blockchain.
ControlUnit BilingCentre Monitoring
Blockchain Blockchain Blockchain
Figure 7. Architecture for data aggregation and privacy preservation scheme.
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Table 4.
Comparison of state-of-the-art research papers on security and privacy-preserving techniques
in smart grid using blockchain.
Ref. Cost and Energy
Secure against
Analysis Scalable Performance
3 7 7 7 7 7
3 3 3 3 7 7
3 7 3 3 3 3
3 3 3 3 3 3
3.3.2. Block Structure
The block structure for this scheme is shown in Figure 8. The PoW consensus algorithm is adopted
for the selection of mining nodes among the different users [
]. The mining nodes record the electricity
consumption data in a Merkle tree. Block header records the hash value of the previous block, the root
hash value of the Merkle tree, timestamp, pseudonym and the average. Timestamp marks the time
at which each transaction occurs on the blockchain and indicates when and what happened in the
blockchain. A pseudonym is a public key for that user, generated by the KMC. Average provides the
value of the average consumption of electricity data.
Hash2 Hash3Hash1Hash0
Pk0,m0 Pk1,m1 Pk3,m3Pk2,m2
Root hash
Previous block hash
Block Header
Block n
Block n+2
Block n+1
Block n
Block n-1
Block n-2
Figure 8. Block structure for data aggregation and privacy preservation scheme.
3.3.3. Technologies Used
The technologies used in this scheme can be discussed in two aspects, namely the preservation of
user identity and preservation of user data. User identity can be preserved using a virtual ring,
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where the control center validates the user’s identity using the ring signature without actually
knowing its identity. In smart contracts, the system can be protected against any theft by using
multiple independent parties to sign the transactions before considering them as valid (multi-signature
transactions). User identity can also be preserved using pseudonyms or based on household battery.
Depending on the consumption profile of the household, the battery will discharge (if household
consumption goes high). Hence, using the household battery, the electricity consumption profile of
the user can be balanced and at the same time, the privacy of the user can be protected. The other
technique to preserve the user data is based on authentication in which the credentials generated by
the consumer are sent for his/her proof of identity to the control center, which signs the credentials.
User data can also be preserved based on data aggregation, which employs data obfuscation and
homomorphic encryption techniques. In data obfuscation, noise is added to the original data to make
data of the user’s electricity consumption unclear, while, in homomorphic encryption, the intermediary
agent is allowed to operate on encrypted data without any information of the plaintext.
3.4. Power Generation and Distribution
Numerous cyberattacks on smart grids have been undertaken in the past where the malicious
attackers have used various methods such as Denial of Service (DoS), Data Injection Attacks (DIA),
etc. to manipulate data and gain control in the grid [
]. This has resulted in complications such as
regional power outages and even complete blackouts [
]. Incorporating blockchain into the power
generation and distribution systems help in the prevention of data manipulation since one of the prime
characteristics offered by the blockchain system is its ability to ensure data immutability.
3.4.1. Blockchain Architecture
Figure 9shows how a blockchain system can be incorporated into a power generation station
with a Single Machine Infinite Bus (SMIB) system and its distribution networks. This framework is
created based on the architectures discussed in other works on power generation and distribution
using blockchain [66,71].
An SMIB is constituted by a synchronous generator G, which is connected to the infinite bus
through a reactance Z; a load, which is fed through a load switch SL; a Power System Stabilizer (PSS)
used for damping the generator’s electro-mechanical oscillations to protect the shaft line and to provide
grid stabilization; and a control switch SC for the PSS, which takes its input from the load switch.
A cyber attacker can use a suitable attacking scheme to modify the conditions of the switches resulting
in the removal of load from the generator and leading to sudden transition in the terminal voltages to
very high values. Since the control switch, SC to PSS, is tampered with, automatic voltage regulation is
rendered unresponsive and damping of the oscillations does not occur. This leads to shaft damage and
loss of synchronization in the target generator. This can be avoided by incorporating the blockchain
into the power generation system [
]. The time-stamped values of each switch state and the target
generator can be stored as data in the blocks. Specific nodes can be given the privilege to validate and
mine the data into the blocks. In the event of an attack, violation in the current state of each switch
should be reported to the blockchain. A smart contract in the metering device would then identify the
violation and maintain the previous terminal value of the target generator by enforcing PSS to damp
the oscillations.
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Supervisory nodes
Block n-2
Block n-1
Block n-2
Block n+1 Block n+2 Block n+3
Blockchain based decentralized platform
Power electronic
DApp DApp
Distribution network
Target generator
Figure 9. Architecture for power generation and distribution.
3.4.2. Block Structure
The block body, as shown in Figure 10, includes measurements, switch states, violations and
timestamp. The measurements part of the block includes the frequency, voltage, and current generated
by the system. Switch States store the states of the switches SL, SC, and PSS and the measured value
of the target generator G. The failed status of the switches as reported by the respective metering
devices is stored in the violations part of the block. The timestamp indicates the time instant of the
measurement. This data is further utilized by the smart contract to take the necessary action.
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Block n-2
Block n-1
Block n+1
Block n
Switch states
Block n
Figure 10. Block structure for power generation and distribution.
3.4.3. Technologies Used
Decentralized Applications (dApps) are the applications running on a network of peers. They
can be utilized in blockchain-based smart grid systems to connect every prosumer, consumer and
energy substation in the grid [
]. Smart contracts are used to intelligently make decisions and to
monitor data. In a DoS attack on any node of the distribution system, a massive amount of data is sent
from multiple sources rendering the node unresponsive. If it occurs on a Remote Terminal Unit (RTU),
which is responsible for monitoring and control of the SCADA devices in the grid, the whole balance
in the distribution system is disrupted. Since the RTU will not be able to communicate with the master
controller in such circumstances, there may be an excess supply of power leading to blowing up of
fuses or to variations in frequency. The dApps provide a means of remotely monitoring the power
consumption metrics, to monitor the change in values of voltage and frequency measures by their
direct links to the blocks in the blockchain network. Since the measured metrics such as the voltage,
current, and frequency are stored in the blocks with timestamps, these values can be compared against
the measurements in the grid to identify the attack and verify the real power consumption.
3.5. Secure Equipment Maintenance for Smart Grids
Equipment health monitoring, fault diagnosis, and maintenance are integral parts of the smart
grid system. Traditional methods of diagnosis involve the necessity for technicians to visit the field for
diagnosis and maintenance. It also involves an investment of manpower and other expenses at the
risk of the client being unsatisfied with the services. This leads to a need for developing systems that
can reduce the maintenance time and are unaffected by regional restrictions. Smart grids encompass
several types of equipment ranging from substations to smart meters installed in homes. Such a
complex smart system, in turn, requires smart equipment maintenance measures to ensure high
efficiency and reliability [73,74].
3.5.1. Blockchain Architecture
A blockchain integrated framework, as shown in Figure 11, can be utilized to create a platform
for interaction among the vendors, diagnosis depots and clients in a secure manner to decide upon the
required maintenance measures for a mutually agreeable price. This framework has been chosen from
Sensors 2019,19, 4862 16 of 25
the existing works in smart grid equipment maintenance and monitoring using blockchain technology,
as discussed in Table 5. Zhang and Fan
used a consortium blockchain with pre-determined
book-keeping nodes to implement this system.
Original Vendor
Failure node
Diagnosis node Consensus processing
Policy control
   center
Smart contract
  triggered
Consensus run
for block creation
Diagnosis requested
Figure 11. Architecture for secure equipment maintenance.
Table 5.
Comparison of state-of-the-art research papers on equipment maintenance and monitoring in
smart grids using blockchain.
Ref. Cost and Energy
Secure against
Analysis Scalable Performance
7 7 3 7 7 7
3 3 3 3 7 7
3 7 3 3 3 3
3 3 3 3 3 3
Whenever a piece of electrical equipment exhibits some fault or abnormality in its operation,
a request for diagnostic services is sent in the network. These equipment are then labeled as failure
nodes in the network. Smart contracts are modeled to respond to the failure nodes and to lead the
flow of operation as decided. The failure node needs to deposit virtual currency for the maintenance
services to the smart contract. If the equipment is within its warranty period, its vendor will perform
the required services and the deposited currency will be returned to the node. However, if the device is
out of its warranty period, the vendor and the other verified maintenance teams who are willing to tend
to the diagnosed fault will now bid to obtain the tender. These nodes will form the diagnosis nodes.
Only the entities that are validated and registered in the system can compete as diagnosis nodes. They
compete fairly in the auction process and the smart contract decides upon who gets the bid depending
on the auction algorithm. When the deal is finalized, the smart contract broadcasts the transaction with
the details fed in the block format to the network. The bookkeeping nodes carry out the respective
consensus algorithm to add the block to the network. This prevents double-spending and once a
consensus is reached regarding the bid, neither of the parties can withdraw without depositing penalty,
making it a reliable system.
3.5.2. Block Structure
As shown in Figure 12, the block body consists of Device Type; Transaction Value denoting the
cost of the maintenance; Diagnosis Node, which responds to the request for diagnosis; Service Files
with information related to the failure node, failure type, time, etc.; Maintenance Mode, indicating
whether it is a remote or on-site maintenance; and Credit, which acts as a means for one node to assess
if they require the services of another.
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block hash
Register 1
Register 2
Register n
Number of
Service files
Block Header
Block Body
Device type
Block b
Block b+2
Block b+1
Block b
Block b-1
Block b-2
Figure 12. Block structure for secure equipment maintenance.
3.5.3. Technologies Used
To provide satisfactory customer service, through a smartphone application that communicates
with the blockchain network via the smart contract, one can connect and log into the network. The app
can receive the progress of the transaction regularly and can be used as a tool to bring about any
adjustments in the policy of operation as required. Information about the node initiating the diagnosis,
the diagnosis method adopted, the payment information, etc. can be relayed periodically to the app,
which leads to an even more reliable and secure transaction.
The comparison between the different use cases discussed above is described in Table 6.
Table 6. Summary of blockchain applications in the smart grid.
Application Problem Addressed
Sample Block Content Technologies Used
P2P energy
Decentralized electricity
trade between prosumers
and consumers, promotion
of renewable energy
Transaction ID, consumer meter
ID, amount of energy requested
and energy granted, a digital
signature of the seller and the
processing node
Smart contracts, virtual
currency, credit-based
Energy trade
between EVs
Buying and selling of
surplus energy between
EVs, privacy-preserving of
Transaction ID, EV’s meter
ID, charged energy, a digital
signature of the charging station
and the processing node
Smart contracts, energy coins
and privacy-
To protect the application
usage pattern and the
privacy information of
Transaction ID, the energy
transferred, a digital signature of
the seller and the LAGs
Bloom Filter, data
aggregation, authentication
Protection from cyber
attacks, incorporation
of abnormality control
Time of measurement,
measurement of frequency,
voltage and current, switch
Smart contract, dApps,
remote control of distortion
using power electronics
Platform for interaction
between vendor and client
for equipment diagnosis
and privacy preservation
Device ID, mode of maintenance,
service files and credits,
transaction value
Smart contracts, user
interaction using smart
phone app
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4. Commercial Implementations of Blockchain in the Smart Grid
One of the foremost applications of blockchain in the smart grid is to incorporate virtual
currencies for payments. The first company to accept
for payment of energy bills was
BASNederl and
]. This inspired several other companies to come up with cryptocurrency-based
solutions for billing and metering, and several of them providing incentives for users making payments
using cryptocurrency instead of those using fiat currencies [
]. Meanwhile, some other companies
such as the South Africa based startup
are developing smart meters with integrated
payments using Bitcoin [
]. The Netherlands based companies
have developed
a blockchain-based token for energy sharing called
]. This token allows the P2P transaction
of electricity through spending the energy tokens from their e-wallets. Another company,
an Australia based startup, developed a blockchain-based platform for P2P renewable energy transfer
between residential prosumers and consumers [
]. The platform makes use of a smart contract-based
system called
to enable the transfer of tokens called
. The company has demonstrated
its ability in saving significant revenue for the users and supplying additional incentives for renewable
energy producers.
The most significant implementation of blockchain in P2P decentralized energy trading and
creation of a local marketplace is the
microgrid. It was launched by the US energy firm
along with
, a Blockchain company [
]. The first trial of the project, which
was carried out with five prosumers and five consumers, marked the first-ever recording of energy
transactions using blockchain. Ethereum-based smart contracts were used to architect the platform,
which facilitated the consumers to buy surplus renewable energy from the prosumers through a
token-based transaction system. The surplus energy tapped through the rooftop photovoltaic (PV)
panels by the prosumers is converted into tokens by the smart meters installed in their houses, which
can be directly used for trade in the energy market. This platform records the mode of transaction in
energy units or tokens as per the requirement of the user. The ledger stores, in chronological order,
details about each transaction, such as the parties involved, the amount of energy consumed/sold
and the related contract terms. The future developments in the
microgrid system include
assigning the users with the ability to choose from the prospective buyers/sellers the required energy,
among other privileges such as the ability to decide the percentage of energy share needed to buy
from prosumers and the main grid. A bidding system will be used in which renewable energy will be
sold to the highest bidder. A mobile application is also being developed to provide users with easy
means of interaction with the platform. Such projects will change the face of energy transactions in the
coming future [83].
Share and Charge
is a blockchain-based platform developed jointly by
Innogy Motionwerk
a subsidiary of German energy conglomerate RWE, and a blockchain firm
. This platform allows
P2P energy trading among EVs and the private charging stations [
]. The users can use their e-wallets
to know about the real-time prices and carry out transactions on this public Ethereum-based platform,
which automatically manages certificates and billing.
is yet another blockchain-based
platform deployed by a company called
in California for leasing out charging piles to EV
drivers for some time [85]. The platform maintains a record of the transactions and allows the owner
of the charging pod the required payment. Moreover,
provides a mobile application for the
owners of the EVs to locate a charging pile from among the enlisted charging piles in the neighborhood.
5. Challenges for Blockchain Incorporation into Smart Grid
5.1. Scalability Issues
Transactions in a blockchain increase on a day-to-day basis, which calls for heavy storage
capabilities to accommodate the ever-growing number of transactions. Currently, the storage for
has exceeded 200 GB while that for
has reached about 1 TB. Even though a
considerably high number of transactions are being carried out using
, the processing rate of
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data into blocks in a blockchain is estimated to be about seven per second. Meanwhile, the average
number of transactions in
is up to 15 per second. Such low rates of processing are attributed
mostly to the consensus mechanism, PoW, which is used in the
technology. High processing
power and time are required by the nodes to compute the PoW algorithm to add the block into the
blockchain network. According to the report in [
], to process 30 million transactions, 30 billion kWh
of electricity was spent, which accounted for about 0.13 percent of global electricity consumption.
In the energy sector, for large scale operations, the number of transactions per second is very high since
thousands of users are simultaneously involved in the process of buying and selling energy. This creates
a large overhead upon the nodes involved in the consensus and validation process. This problem
can be addressed by replacing the PoW consensus algorithm either with the Proof-of-Stake (PoS) or
the Proof-of-Authority (PoA) algorithm. These algorithms require much less computing capacity and
support much higher rates of transactions. A new blockchain platform named
is aimed specifically at the energy sector with transaction rates as high as a few thousand per second.
It uses the PoA consensus mechanism, which gives it such high processing rates. Further research and
innovations have to be carried out to find solutions to properly scale up the platform to accommodate
the requirements of the smart grid system without compromising on the security aspects [
]. Other
so-called “second-layer” solutions are intensely being researched by the community for addressing the
scalability issues [
]. Off-chain [
] and side-chain [
] techniques have been proposed for reducing
the number of transactions and for parallelizing the transaction validation, respectively. Research is
also leading to advancement in the enabling technologies such as Distributed Hash Table (DHT) [
InterPlanetary File System (IPFS) [
], and nonlinear block organizations such as Directed Acyclic
Graph-based chains (DAGchains) [
] to potentially address the scalability and
throughput challenges.
5.2. Chances of Centralization
Currently, blockchain application in the energy sector is still a budding technology and is prone
to attacks from the energy conglomerates who might exploit it for financial advantages. One of the
reasons for centralization is the clustering of mining nodes into mining pools for better computational
capacity. The only chance of changing the transactional data in a block is through the 51 % attack,
where the attacker controls 51 % of the computational capacity in the network. By clustering the mining
nodes into pools, there exists a risk of the mining pools acquiring enough resources to plot a malicious
attack. Another reason for centralization is the fact that much of the architecture in the energy sector is
based on consortium or private blockchains. The reason for their popularity is the problem of power
wastage and latency associated with public blockchain architectures. Since a predefined set of nodes
are responsible for validation and consensus in the public blockchains, chances of malpractice exist.
Therefore, strict supervision under governmental laws should be enforced especially in the beginning
stages to ensure security.
5.3. Development and Infrastructure Costs
Implementing blockchain in the smart grid requires high infrastructural costs for re-architecting
the current grid networks, upgrading smart meters to aid in transactions through smart contracts,
infrastructure for Information and Communication Technologies (ICT) specific for Blockchain
operations, other related Advanced Metering Interfaces (AMI) and software for development of
the whole platform. Such high infrastructure costs may dissuade grid operators from the incorporation
of blockchain into the grid structure. The current infrastructure of the grid has been adopted after
years of research and development and it yields optimal results with much less overall expenditure.
For example, the grid communication system currently employs technologies such as telemetry which
is more mature as well as much less expensive compared to blockchain.
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5.4. Legal and Regulatory Support
The regulatory bodies do support the active participation of users in the energy market, and
the formation of community energy structures. However, when it comes to radical changes in the
main power grid framework, the current grid legal system does not support the trading of energy
from prosumers to consumers and does not endorse the adoption of the distributed ledger into the
framework. New types of contracts have to be developed especially for the P2P trading system and
changes in the energy tariffs need to be brought about to support such services. Such matters are
heavily regulated in the current grid system. For these reasons, even though blockchain technology
has proven its worth in the formation of microgrids, without amended legal structures, it is very
challenging to adopt the technology into the main grid framework.
6. Future Research Directions
Using blockchain technology, a decentralized computing platform can be created in addition
to the trading infrastructure. All the peers who participate in the network give a share of their
computational capacity, thus increasing the total capacity within the system, which will enable
efficient operation and control of microgrids. It will also increase trust among the owners and the
scalability of the grid. Even if an extra consumer is added, there will be no increase in complexity.
Any new technology needs to prove that it can offer the scalability, speed, and security required
before it can be widely accepted. The blockchain technology has already passed the proof
of concept but it still needs to be scaled up and be cost-efficient. For grid communication,
there already exists established solutions such as telemetry, which are significantly cost-efficient.
Blockchain technology also has to compete on all the above-mentioned aspects for wider utility
and acceptance. There is a scope in cutting the cost for data storage by storing actual data in the
sidechains (as subsidiary blockchains) and operating the main blockchain as a control layer rather
than as a storage layer.
In current large-scale blockchain networks such as Ethereum or Bitcoin, any upgrade to the
software code that runs in the participating nodes must be approved (via consensus algorithms)
to be affected throughout the network. Any disagreements to do so can lead to forking and
fragmentation of the network, compromising its security and data integrity. The design of these
blockchain networks for smart grids must be protected against such effects.
Blockchain-based solutions for various aspects of decentralized grid management and control,
e.g., improving demand–supply balance, automated verification of grid assets, forecasting grid
requirements, self-adjusting power consumption based on price surges or drops, etc., need to
be explored.
7. Conclusions
The smart grid is a booming technology in the energy sector and it essentially needs a reliable
and secure framework for operations. This paper discusses several use cases in which blockchain can
be incorporated into the smart grid to open the doors to a wide range of possibilities. P2P energy trade
is the need of the hour for promoting sustainable use of energy and for tapping renewable energy
sources. With the advent of using the blockchain in the smart grid scenario, V2V and V2G energy
transfer have become simpler and more reliable than ever. Although the privacy requirement is not
directly ensured by blockchain technologies, advanced cryptographic techniques such as ZKP and
ECDSA can be incorporated to enable privacy preservation. Further, this paper discusses the data
immutability aspect of blockchain, which can be used to prevent cyber attacks, especially in the power
generation and distribution systems. A secure equipment maintenance system that ensures efficient
diagnosis using smart contracts is also discussed. Along with discussing various application areas of
blockchain, this paper illustrates potential blockchain architectures and block structures for each of
Sensors 2019,19, 4862 21 of 25
these areas. However, for the widescale adoption of blockchain in the smart grid, the industry and
research community will have to work together to address the significant challenges that lay ahead.
Author Contributions: T.A. investigated the related literature on the topic, wrote the first draft of the document
and identified some open research challenges. V.C. supervised all of the study and reviewed the structure and the
first draft. J.J.P.C.R. and S.A.K. reviewed all the content carefully and edited the paper. T.A., V.C., J.J.P.C.R. and
S.A.K. contributed equally to the scope definition, motivation, and focus of the paper.
This research/project was supported by DST-SERB, India funding ECR/2018/001479; by the National
Funding from the FCT—Fundação para a Ciência e a Tecnologia through the UID/EEA/50008/2019 Project; by
the Government of the Russian Federation, Grant 08-08; and by the Brazilian National Council for Scientific and
Technological Development (CNPq) via Grant No. 309335/2017-5.
Conflicts of Interest: The authors declare no conflict of interest.
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... Electric power grids are mission-critical systems; hence, any issues with grid equipment (such as substations and smart meters) must be quickly detected, diagnosed, and resolved. Traditionally, maintenance logistics are complex and labor-intensive and are often limited by regional restrictions [10]. Blockchains can be used to streamline the maintenance process. ...
... Al-Abri et al. [9] Allladi et al. [10] Appasani et al. [11] Baidya et al. [12] Gawusu et al. [13] Hasankhani et al. [14] Henninger et al. [15] Junaidi et al. [16] Khan et al. [17] Malla et al. [18] Miglani et al. [19] Musleh et al. [20] Nour et al. [21] O'Donovan et al. [22] Wang et al. [23] Yapa et al. [24] In [9], blockchain applications were divided based on the target components: (1) microgrids and smart grids, which include blockchain-based applications for the energy market, peer-to-peer trading, energy management, and carbon emission trading; (2) electric vehicles, which concerns how to integrate electric vehicles into the grid with energy trading; and (3) privacy protection of the users. ...
... In [10], the blockchain applications included peer-to-peer energy trading, energy trading in electric vehicles, secure equipment maintenance for smart grids, and security and privacy in power generation and distribution. ...
Full-text available
This article presents an umbrella review of blockchain-based smart grid applications. By umbrella review, we mean that our review is based on systematic reviews of this topic. We aim to synthesize the findings from these systematic reviews and gain deeper insights into this discipline. After studying the systematic reviews, we find it imperative to provide a concise and authoritative description of blockchain technology because many technical inaccuracies permeate many of these papers. This umbrella review is guided by five research questions. The first research question concerns the types of blockchain-based smart grid applications. Existing systematic reviews rarely used a systematic method to classify these applications. To address this issue, we propose a taxonomy of these applications, first by differentiating them based on whether the application is focusing on functional or non-functional aspects of smart grid operations, and then by the specific functions or perspectives that the application aims to implement or enhance. The second research question concerns the roles that blockchain technology plays in smart grid applications. We synthesize the findings by identifying the most prominent benefits that blockchain technology could bring to these applications. We also take the opportunity to point out several common technical mistakes that pervade the blockchain literature, such as equating all forms of blockchains to data immutability. The third research question concerns the guidelines for deciding whether a blockchain-based solution would be useful to address the needs of smart grids. We synthesize the findings by proposing benefit-based guidelines. The fourth research question concerns the maturity levels of blockchain-based smart grid applications. We differentiate between academic-led and industry-led projects. We propose a five-level scale to evaluate the maturity levels. The ranking of the industry-led projects is performed through our own investigation. Our investigation shows that more than half of the industry-led projects mentioned in the systematic reviews are no longer active. Furthermore, although there are numerous news reports and a large number of academic papers published on blockchain-based smart grid applications, very few have been successfully embraced by the industry. The fifth research question concerns the open research issues in the development of blockchain-based smart grid applications. We synthesize the findings and provide our own analysis.
... Además, cabe mencionar la tecnología blockchain (base de datos pública no modificable a la que pueden tener acceso multitud de usuarios de manera directa, es decir, sin intermediarios y "entre iguales"), ya que está adquiriendo cada vez más importancia debido a su aplicación en diferentes ámbitos [5] (Figura 3). ...
... De esta forma, cada nuevo bloque se conecta a todos los bloques anteriores en una cadena criptográfica de tal manera que es casi imposible de manipular. Además, todas las transacciones dentro de los bloques son validadas y acordadas por un mecanismo de consenso, asegurando así que cada transacción es verdadera y correcta [5]. ...
Este libro presenta un estudio acerca de las tecnologías digitales disruptivas (Internet of Things, Machine Learning, Blockchain y otras) que se han aplicado a la gestión de la pandemia ocasionada por la COVID-19. La investigación se ha llevado a cabo a través de un análisis cienciométrico -basado en minería de textos- de la producción científica publicada al respecto a lo largo de un período de año y medio (2020 y mitad de 2021) y, a este respecto, se ha considerado Scopus como fuente de datos principal y Web of Science como secundaria (a efectos comparativos). De esta manera, por medio de la utilización del potente software VOSviewer, se ofrecen multitud de resultados -ilustrados por los correspondientes mapas bibliométricos- como la evolución temporal del número de publicaciones, la producción y el número de coautorías por países, los temas (topics) y autores más prolíficos o un ranking de los artículos más referenciados. En definitiva, en este libro, se pretende ofrecer una visión lo más completa y actualizada posible de cómo la inteligencia artificial y ciertas tecnologías digitales emergentes han contribuido, de manera esencial, a cuestiones de predicción, seguimiento, diagnóstico, tratamiento y prevención de la COVID-19.
... Second application involves the interactions between the Transmission System Operator (TSO) and the Distribution System Operators (DSOs) to select prospective generation options and maintain supplydemand balance for stable grid frequency. This decision is made based on the energy storage capacity of each DSO [5], where DSOs with excess capacity will contribute towards better frequency regulation by facilitating a reliable supplydemand balance. ...
... Blockchain, a Distributed Ledger Technology (DLT) [6], creates a conducive environment for the realization of the applications of SG 2.0 [5], [7], [8] along with smart contracts, which are automated scripts of the process deployed onto the blockchain. Hence, the proposed reputation management system is integrated with the blockchain architecture and automated using smart contracts. ...
Conference Paper
Full-text available
The futuristic energy grids comprise of predominantly renewable generation, to align with the sustainable development goals. This would require integration of renewable energy sources at different levels of the power system out of which, consumers turning into power producers, often referred to as prosumers is an important aspect. Prosumers who generate excess power beyond self-consumption are keen on selling it to the neighbourhood in a peer-to-peer manner, expecting a profit. On the other hand, consumers expect concessions for using more of the green energy. Further, with the high intermittency of these generation, Distribution System Operators (DSO) face the challenge of securing a reliable power supply. In the envisaged grid context, deciding the price for energy trading between prosumers and consumers as well as estimating the reliability of each DSO is considered to be crucial. Hence, this study proposes utilizing an end-to-end reputation management system to maintain the past record related to the performance of each stakeholder, which can be integrated in the price determination and selection decisions. To further ensure decentralized and secure operations of such reputation management systems, a blockchain-based service architecture and smart contracts have been incorporated. The impact of this to the performance of the proposed energy trading system is analysed through cost and latency indices.
... Second application involves the interactions between the Transmission System Operator (TSO) and the Distribution System Operators (DSOs) to select prospective generation options and maintain supply-demand balance for stable grid frequency. This decision is made based on the energy storage capacity of each DSO [5], where DSOs with excess capacity will contribute towards better frequency regulation by facilitating a reliable supply-demand balance. ...
... A decentralized, transparent, and secure mechanism, which has the capabilities of automated execution of the P2P energy trading and facilitating DSO-TSO interactions, is seen as a timely requirement. Blockchain, a Distributed Ledger Technology (DLT) [6], creates a conducive environment for the realization of the applications of SG 2.0 [5], [7], [8] along with smart contracts, which are automated scripts of the process deployed onto the blockchain. Hence, the proposed reputation management system is integrated with the blockchain architecture and automated using smart contracts. ...
Conference Paper
Full-text available
The futuristic energy grids comprise of predominantly renewable generation, to align with the sustainable development goals. This would require integration of renewable energy sources at different levels of the power system out of which, consumers turning into power producers, often referred to as prosumers is an important aspect. Prosumers who generate excess power beyond self-consumption are keen on selling it to the neighbourhood in a peer-to-peer manner, expecting a profit. On the other hand, consumers expect concessions for using more of the green energy. Further, with the high intermittency of these generation, Distribution System Operators (DSO) face the challenge of securing a reliable power supply. In the envisaged grid context, deciding the price for energy trading between prosumers and consumers as well as estimating the reliability of each DSO is considered to be crucial. Hence, this study proposes utilizing an end-to-end reputation management system to maintain the past record related to the performance of each stakeholder, which can be integrated in the price determination and selection decisions. To further ensure decentralized and secure operations of such reputation management systems, a blockchain-based service architecture and smart contracts have been incorporated. The impact of this to the performance of the proposed energy trading system is analysed through cost and latency indices.
... A summary of application areas and technical details is included. Commercial implementations and challenges for integrating BC into smart grids are discussed, along with future research directions [16]. ...
... Energies 2023,16, 5963 ...
Full-text available
Energy demand is increasing rapidly due to rapid growth and industrialization. It is becoming more and more complex to manage generation and distribution due to the diversification of energy sources to minimize carbon emissions. Smart grids manage reliable power generation and distribution efficiently and cater to a large geographical area and population, but their centralized structure makes them vulnerable. Cybersecurity threats have become a significant concern with these systems’ increasing complexity and connectivity. Further transmission losses and its vulnerability to the single point of failure (SPOF) are also major concerns. Microgrids are becoming an alternative to large, centralized smart grids that can be managed locally with fewer user bases and are safe from SPOF. Microgrids cater to small geographical areas and populations that can be easily managed at the local level and utilized for different sources of energy, like renewable energy. A small group of consumers and producers are involved, but microgrids can also be connected with smart grids if required to exchange the excess energy. Still, these are also vulnerable to cybersecurity threats, as in the case of smart grids, and lack trust due to their decentralized nature without any trusted third party. Blockchain (BC) technology can address the trust and cybersecurity challenges in the energy sector. This article proposes a framework for implementing a BC-based microgrid system for managing all the aspects of a microgrid system, including peer-to-peer (P2P) energy trading, Renewable Energy Certificate (REC), and decentralized energy trading, that can be utilized in the case of Saudi Arabia. It can integrate cybersecurity standards and protocols, as well as the utilization of smart contracts, for more secure and reliable energy generation and distribution with transparency.
... Blockchain technologies have attained significant attention in recent years due to their ability to provide transparency and accountability using distributed ledger technologies [204,205]. Blockchain technologies are extensively used in financial services, smart grids, secure healthcare data storage, intellectual property management, secure voting services, and supply chain management [206][207][208]. Blockchain technology may be used for enabling certain 6G services, for example, decentralised authentication of users and distributed wireless resource sharing among users that might not trust each other [47]. ...
Full-text available
The quantum internet is a cutting‐edge paradigm that uses the unique characteristics of quantum technology to radically alter communication networks. This new network type is expected to collaborate with 6G networks, creating a synergy that will fundamentally alter how we communicate, engage, and trade information. The improved security, increased speed, and increased network capacity of the quantum internet will lead to the emergence of a broad variety of new applications and services. The current state of quantum technology and its integration with 6G networks are summarised in this study, with an emphasis on the key challenges and untapped possibilities. The main goal is to get knowledge about how the quantum internet might impact communication in the future and alter several economic and societal sectors.
... People can easily exchange energy with one another. Another benefit is that by monitoring a region's use data [123]. ...
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The quickening propensity of growth within the areas of information and communications technology and energy networks has triggered the emergence of a central idea termed as Internet of Energy (IoE). Such a concept relates the internet of things, which is the term used in describing the usage of sophisticated digital control devices with the capability of transmitting data via IT systems. The concept of an interconnected energy network is being formed in the upcoming days through upgrades in the field of intelligent energy systems to control real-time energy optimization and management. The energy industry has had a sustained expansion, reaching the IoE milestone and continuing to this cutting-edge power system, which is the next generation of IoE. A directional pathway from the traditional power system to the IoE has been conducted in this research work by addressing the importance of integrating the smart transmission and communication infrastructure, smart metering, pricing and energy management scheme. A detailed investigation of the IoE with respect to technical angles, such as communication architecture, IoE on the supply & demand side, and IoE protocol based on fundamental elements and essential technologies has been carried out to indicate the blueprint and jurisdiction complexity. The integration, security and energy management challenges may deviate the performance of the IoE technology that has been focused with proper control issues and solutions. Finally, a directional framework to establish the next-generation IoE system has been constructed with future scopes to insure higher resiliency, cyber-security and stability.
Peer-to-peer (P2P) energy trading using blockchain is presented as a great innovative potential to promote rural electrification. Opportunities and challenges assessment for the implementation of this technology in Sub-Saharan Africa shows that it is only at its embryonic stage in the region. The decreasing cost of stand-alone solar technology and the expansion of investment in mini-grid sector are among the opportunities. However, the considerable restriction of private participation in the mini-grid sector, the difficulty of the regulatory process and licensing requirements, the issues with tariff framework, and the uncertainty of the regulation about the future grid integration are among the main challenges. This chapter proposes a policy and regulation framework for the promotion of P2P energy trading using blockchain in Sub-Saharan Africa.
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As consumer Internet of Things (IoT) devices become increasingly pervasive in our society, there is a need to understand the underpinning security risks. Therefore, in this paper, we describe the common attacks faced by consumer IoT devices and suggest potential mitigation strategies. We hope that the findings presented in this paper will inform the future design of IoT devices.
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Drones or Unmanned Aerial Vehicles (UAVs) can be highly efficient in various applications like hidden area exploration, delivery, or surveillance and can enhance the quality of experience (QoE) for end-users. However, the number of drone-based applications are not very high due to the constrained flight time. The weights of the drones need to be kept less, and intuitively they cannot be loaded with big batteries. Frequent recharging and battery replacement processes limit the appropriate use of drones in most applications. A peer-to-peer distributed network of drones and charging stations is a highly promising solution to empower drones to be used in multiple applications by increasing their flight time. The charging stations are limited, and therefore, an adequate, fair, and cost-optimal scheduling algorithm is required to serve the most needed drone first. The proposed model allows the drones to enter into the network and request for a charging time slot from the station. The stations are also the part of the same network, this work proposes a scheduling algorithm for drones who compete for charging slots with constraints of optimizing criticality and task deadline. A game-theoretic approach is used to model the energy trading between the drones and charging station in a cost-optimal manner. Numerical results based on simulations show that the proposed model provides a better price for the drones to get charged and better revenue for the charging stations simultaneously.
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The protection of Smart Meters (SMs) from cyber attacks are of utmost importance because SMs in Advanced Metering Infrastructure (AMI) are physically unprotected and produce large amount of sensitive data. Due to scalability, SMs are small-sized and low cost devices having low computational capabilities. The algorithms designed to complete the security requirements of SMs should be light-weight. To address this issue, this paper proposes a light-weight security solution to address man-in-the-middle attack, data tempering and blockchain based data provenance. Received Signal Strength Indicator (RSSI) is used to generate link fingerprints, which are used along with pseudo-random nonce to secure AMI. The proposed algorithm detects the involvement of adversarial node or meter tempering by computing other values along with 0 and 1 as the average of consecutive RSSI and difference between the RSSI of connected static SMs. Pearson correlation coefficient (ρ) of 0.9102 is achieved when no adversarial node is present in between connected SMs having mobility in one or both SMs. Negative or approximately equal to zero values of ρ are computed when adversary is present in the AMI or any of the SM in the AMI is forged. For blockchain based data provenance, all the hash values of packet header are 100% matched with the hash functions present at the Data Concentrator Unit (DCU) which shows no adversary’s involvement in AMI. For cases when adversary is in the AMI, hash functions show no match with the hash values present at DCU.
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Internet of things (IoT) is the next era of communication. Using IoT, physical objects can be empowered to create, receive and exchange data in a seamless manner. Various IoT applications focus on automating different tasks and are trying to empower the inanimate physical objects to act without any human intervention. The existing and upcoming IoT applications are highly promising to increase the level of comfort, efficiency, and automation for the users. To be able to implement such a world in an ever growing fashion requires high security, privacy, authentication, and recovery from attacks. In this regard, it is imperative to make the required changes in the architecture of IoT applications for achieving end-to-end secure IoT environments. In this paper, a detailed review of the security-related challenges and sources of threat in IoT applications is presented. After discussing the security issues, various emerging and existing technologies focused on achieving a high degree of trust in IoT applications are discussed. Four different technologies: Blockchain, fog computing, edge computing, and machine learning to increase the level of security in IoT are discussed.
In the past decade, crypto-currencies such as Bitcoin and Litecoin have developed rapidly. Blockchain as the underlying technology of these digital crypto-currencies has attracted great attention from academia and industry. Blockchain has many good features, such as trust-free, transparency, anonymity, democracy, automation, decentralization and security. Despite these promising features, scalability is still a key barrier when the blockchain technology is widely used in real business environments. In this article, we focus on the scalability issue, and provide a brief survey of recent studies on scalable blockchain systems. We first discuss the scalability issue from the perspectives of throughput, storage and networking. Then, existing enabling technologies for scalable blockchain systems are presented. We also discuss some research challenges and future research directions for scalable blockchain systems.
The large amounts of data collected by smart meters (SM), such as electric energy, water gas consumption and power quality (PQ) metrics, can create a massive flow of data transmitted between consumers and utilities. In this context, an edge-fog-cloud architecture based on a low-cost SM is proposed. The employed SM acquires voltage and current signals to obtain their frequency and amplitude, allowing PQ to be monitored through methods of detection and classification of disturbances in order to send only information about the detected disturbances to the utility, thus reducing network traffic associated with PQ disturbances in Smart Grids. The proposed methodology was embedded at a low-cost SM to enable data exchange with the utility, offering an enormous potential for real scenarios.
Currently, blockchain technology has been widely used due to its support of transaction trust and security in next generation society. Using Internet of Things (IoT) to mine makes blockchain more ubiquitous and decentralized, which has become a main development trend of blockchain. However, the limited resources of existing IoT cannot satisfy the high requirements of on-demand energy consumption in the mining process through a decentralized way. To address this, we propose a decentralized on-demand energy supply approach based on microgrids to provide decentralized on-demand energy for mining in IoT devices. First, energy supply architecture is proposed to satisfy different energy demands of miners in response to different consensus protocols. Then, we formulate the energy allocation as a Stackelberg game and adapt backward induction to achieve an optimal profit strategy for both microgrids and miners in IoT. The simulation results show the fairness and incentive of the proposed approach.
In this paper, we propose a novel deep learning and blockchain-based energy framework for Smart Grids, entitled DeepCoin. The DeepCoin framework uses two schemes, a blockchain-based scheme and a deep learning-based scheme. The blockchain-based scheme consists of five phases; setup phase, agreement phase, creating a block phase and consensus-making phase, and view change phase. It incorporates a novel reliable peer-to-peer energy system that is based on the practical Byzantine fault tolerance algorithm and it achieves high throughput. In order to prevent smart grid attacks, the proposed framework makes the generation of blocks using short signatures and hash functions. The proposed deep learning-based scheme is an intrusion detection system (IDS), which employs recurrent neural networks (RNNs) for detecting network attacks and fraudulent transactions in the blockchain-based energy network. We study the performance of the proposed IDS on three different sources the CICIDS2017 dataset, a Power System dataset, and a Bot-IoT dataset.