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\begin{document}

\title{Research of trusted real-time electrical data transmission mechanism
based on parallel proof of work algorithm}



\author[1]{Chen Yiming}%
\author[1]{Gao Doliang}%
\author[1]{Yang Yuxuan}%
\author[1]{Luo Jintang}%
\author[1]{Yi Li}%
\affil[1]{State Grid Sichuan Electric Power Company Economic Research Institute}%


\vspace{-1em}



  
  \date{May 23, 2024}


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\selectlanguage{english}
\begin{abstract}
Secure and reliable electricity supply is a prerequisite for the
development of smart cities, and the trustworthy and efficient
transmission of electrical data is the foundation for the safe and
stable operation of the power grid. This paper introduces a real-time
data transmission blockchain technique based on parallel proof of work
algorithm. The new block generation progress of proposed blockchain is
divided into five subroutines: hash pointer computation, real-time data
pudding, signature value iteration, interruption, block header assembly.
The real-time data pudding and signature value iteration are parallel
processed, which brings the effect of decreasing energy loss of
blockchain system, and upgrades the speed of new block generation and
the bandwidth of data storing on blockchain. Computer simulation shows
the proposed strategy can be effectively applied in real-time electrical
data transmission application, raising the data transmission reliability
with no harm to real-time data transfer function. This strategy provides
a solution to guarantee data transmission safety in the digital
conversion of power grid.%
\end{abstract}%



\sloppy


Type of the Paper (Review)

Research of trusted real-time electrical data transmission mechanism
based on parallel proof of work algorithm

Chen Yiming, Gao Dongliang, Yang Yuxuan, Luo Jintang, Yi Li

State Grid Sichuan Economic Research Institute, Chengdu, 610041

\textbf{*} Correspondence: chen90sky@163.com

\textbf{Abstract:} Secure and reliable electricity supply is a
prerequisite for the development of smart cities, and the trustworthy
and efficient transmission of electrical data is the foundation for the
safe and stable operation of the power grid. This paper introduces a
real-time data transmission blockchain technique based on parallel proof
of work algorithm. The new block generation progress of proposed
blockchain is divided into five subroutines: hash pointer computation,
real-time data pudding, signature value iteration, interruption, block
header assembly. The real-time data pudding and signature value
iteration are parallel processed, which brings the effect of decreasing
energy loss of blockchain system, and upgrades the speed of new block
generation and the bandwidth of data storing on blockchain. Computer
simulation shows the proposed strategy can be effectively applied in
real-time electrical data transmission application, raising the data
transmission reliability with no harm to real-time data transfer
function. This strategy provides a solution to guarantee data
transmission safety in the digital conversion of power grid.

\textbf{Keywords:} blockchain; electric power data; consensus algorithm;
proof of work

1. Introduction

Since 2008, when Satoshi Nakamoto invented Bitcoin, initiating the study
of blockchain, blockchain technology has been leading a new global wave
of technological and industrial transformation, becoming the ''prime
mover'' of innovative social development. Blockchain technology with
open and fault-tolerant characteristics, is highly compatible with
shared economic model based on distributed systems. Meantime, blockchain
techniques can also solve the essential requirements of electric power
and energy industry. In the construction of electric power and energy
industry, blockchain as the infrastructure of digital economy combined
with industry applications, can form an immutable distributed ledger,
potentially solving management, financing, regulation, and privacy
issues caused by numerous transaction entities and opaque data
information. Extensive research and attempts have been made by
industrial experts and scholars on the application of blockchain
technology in electric power field, including distributed energy
trading{[}1{]}, electric vehicle charging pile sharing{[}2{]},
enterprise energy consumption monitoring{[}3{]}, carbon emission
trading{[}4{]}, emerging energy business applications{[}5{]}, etc. Such
researches mainly based upon Bitcoin blockchain system, establishing a
trustworthy energy trading platform through blockchain technology,
thereby reducing trust cost in traditional power trading. On the other
hand, blockchain can also be seen as a decentralized, tamper-resistant,
and open autonomous distributed database, suitable for the trustworthy
storage and transmission of enterprise data.

However, in the context of electric power production, various sampling
data need to be transmitted to dispatch control center in a timely
manner, and the real-time data transmission requirements in such
applications have limited the direct application of blockchain
technology. This paper proposes a parallel proof-of-work algorithm for
blockchain, effectively applying blockchain technology to real-time
electric power data transmission scenarios, thereby significantly
enhancing the reliability and anti-tampering ability of electric power
data transmission.

2. Blockchain Consensus Mechanism Principles

Nowadays, blockchain is commonly used for distributed storage of
transaction data. According to transactions chronological order,
different transaction data are stored in different blocks, and adjacent
blocks are linked through hash pointers. Figure 1 illustrates the
schematic diagram of blockchain data structure.

\textbf{Hosted file}

\verb`image1.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 1.} Data structure diagram of blockchain

As can be seen from Figure 1, each block is divided into a block header
and a block data section. The block data section is primarily used to
store data information, such as transaction records in Bitcoin
system{[}6{]}, smart contracts in Ethereum system{[}7{]}, etc. The block
header records summary information of current block, including the
Merkle tree root hash value of block data, and stores the block header
hash value of previous block. Due to the one-way irreversibility of hash
function, any tampering on block data requires simultaneous forgery of
data's Merkle tree root hash value and of the block header hash value of
previous block, which increases data tampering difficulty. Blockchain
applies a consensus algorithm mechanism, which would be briefly
explained in this section, making tampering with block data almost
impossible.

2.1. Brief Description of the Proof of Work Principle

In blockchain system, to maintain data consistency across all network
nodes, it is necessary to synchronize storage data of all nodes
according to certain rules after a new block is generated. This rule is
known as consensus mechanism. Various implementation schemes for
consensus mechanisms based on different principles have been
proposed{[}8{]}, and Proof of Work (PoW) is one of the most
representative, having been applied to Bitcoin system and undergone
extensive practical testing{[}9{]}. The research approach of this paper
is also based on PoW algorithm, and its principle is briefly introduced
below.

Figure 2 shows a simplified flowchart of PoW algorithm. From the
flowchart, it can be seen that PoW algorithm is mainly divided into
three steps:

(1) Generate Merkle root hash value;

(2) Assemble block header;

(3) Iteratively calculate current block header hash value.

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\textbf{Figure 2.} Flowchart of Proof of Work algorithm

To generate a new block, data must first be placed within block, a
process achieved by calculating Merkle root hash value. Block data is
usually organized through a Merkle tree, the structural schematic is
shown in Figure 3. In Merkle tree, the hash values of the block data are
arranged in a binary tree structure, with the value of each parent node
equal to the hash value of the sum of its two child nodes. Merkle tree
root node is located at the top of entire binary tree, and its value is
equivalent to the hash attestation of all data in current block. By
storing Merkle root hash value in block header, a close association
between block header information and block data is established,
eliminating the possibility of an attacker tampering with the block data
only.

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\textbf{Figure 3.} Merkle tree structure in blockchain

After determining Merkle root hash value, PoW algorithm proceeds to
assemble block header, filling in corresponding fields with the hash
value of previous block header, current timestamp, target value for
generating new block, etc. The target value for generating new block is
defined by blockchain network protocol and is updated at specified
intervals. The value of random number (\emph{nonce} ) in block header is
determined through iterative calculation process of PoW algorithm.

During iterative calculation process, except for the random number
(\emph{nonce} ) field shown in Figure 1, all information of new block
has been determined. At this point, PoW algorithm fills in a random
value in\emph{nonce} field and calculates current block header hash
value. If this hash value is less than target value, the new block is
considered as a ''valid'' block and will be broadcast to blockchain
network. If the hash value does not meet target value requirement, PoW
algorithm will regenerate a new random value to fill in \emph{nonce}
field and perform hash value verification.

During the execution of PoW algorithm, if a host receives a ''valid''
block generated by other nodes from blockchain network, it adds such
block as the latest block to blockchain and executes PoW algorithm again
on the updated blockchain{[}6{]}.

2.2. Challenges of Proof of Work Algorithm

Blockchain system has solved the problem of constructing a trustworthy
distributed database in a network environment where communication
conditions are unreliable, and member information remains anonymous.
Based on blockchain technology, decentralized digital currencies, smart
contracts, distributed data storage, and other applications have been
realized, with consensus algorithms playing a vital role.

As one of the most successful consensus mechanisms to date, PoW
algorithm has been proven in practice to maintain long-term secure and
stable operation of blockchain system. Its core concept is to select
nodes to generate new blocks in proportion to the computing resources
possessed by each node. Due to the adjustable difficulty and easily
verifiable results of hash operation used by PoW algorithm, blockchain
network can dynamically adjust the target value parameter in PoW
algorithm according to the overall computing power of blockchain
network, and quickly propagate a ''valid'' new block to every node once
it is generated by a particular node.

However, while PoW algorithm effectively achieves decentralized data
storage, traceable data operations, and immutable on-chain information,
it also faces challenges such as high electric power consumption, long
time of new block generation, and low bandwidth of data upload.

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\verb`image4.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 4.} Transmission progress of new block

Figure 4 illustrates the schematic diagram of the propagation process of
a new block in blockchain network. After running PoW consensus algorithm
for some time, Server A first finds a ''valid'' new block and attempts
to propagate new block information to all nodes through blockchain
network. Server A first needs to send the new block information to
adjacent node B, and then Server B sends such information to other
adjacent nodes. Such process would be repeated until all nodes in
blockchain network receive the new block information. By analyzing this
process, it can be seen that the generation and propagation of new block
have following characteristics:

(1) Low Efficiency in Generating New Blocks. During block generation
process, all computing resources in blockchain network are used to find
a ''valid'' new block. As of June 2023, the total computational power of
Bitcoin network has exceeded 370EH/s. It is evident that to achieve
decentralization, PoW algorithm has sacrificed computing efficiency to
some extent{[}10{]}.

(2) Long Time to Generate New Blocks. During block generation process,
if no node in blockchain network finds a ''valid'' new block, all nodes
must continue running PoW algorithm. The average time to generate a new
block is regulated by block generation target value, and to ensure
system stability, this time cannot be set too small. For Bitcoin system,
the average time to generate a new block is about 10 minutes{[}11{]}.
Block generation speed limitation restricts the promotion and
application of blockchain in some fields.

(3) Size Limitation for Individual Blocks. To ensure efficient
propagation of the new block in blockchain network, the size of an
individual block cannot be too large; otherwise, it would significantly
prolong the time for entire network to reach consensus. In Bitcoin
system, each block must not exceed 1MB{[}11{]}. Thus, the upload
bandwidth of blockchain data is also limited.

In response to above problems, many new consensus algorithms have been
proposed in recent years, such as Proof of Stake (PoS){[}12{]},
Delegated Proof-of-Stake (DPoS){[}13{]}, Proof of Space {[}14{]}, Proof
of Elapsed Time {[}15{]}, etc. These algorithms replace the computing
power competition in PoW with different competition methods to address
resource consumption and security issues. However, these algorithms have
not yet been experienced large-scale, long-term practical testing and
have reduced the decentralization capability and usability of
blockchain.

3. Characteristics of electric power data transmission

Power grid, as a vast electromechanical hybrid system, suffers from the
risk of failure spreading throughout network, threatening the stability
of entire system. To ensure the safe and stable operation of power grid,
the timely transmission of grid status information to dispatch control
center through electric power data network is of great significance.
However, with the trend of power grid digitization development, electric
power data transmission faces risks such as network attacks and
malicious tampering. How to enhance the reliability of electric power
data transmission and verify data credibility has become a key focus of
academia and industry{[}16-19{]}. Blockchain as a cutting-edge
technology can effectively build a trustworthy data transmission
environment, becoming one of the alternative solutions to above
problems.

Currently, electric power data is mainly carried in dedicated data
networks. Unlike traditional Internet, the architecture of electric
power data network is clear and fixed, and its business characteristics
are explicit, allowing further optimization and enhancement of data
transmission by applying blockchain techniques.

3.1. Power Dispatch Network Architecture and Transmission Services

Electric power dispatch data network is a dedicated data network for
electric power dispatching and production services. Figure 5 shows the
schematic diagram of electric power dispatch data network architecture.
As can be seen from the figure, the architecture of electric power data
network is a tree structure. Substations and power plants, as the
terminal nodes in network, transmit operating data to dispatch and
control center through dispatch data network via plant and station
network equipment. To ensure the reliability of data transmission, each
plant and station equipment is configured in a dualized manner,
separately connected to two different levels of access networks{[}20{]}.
Compared to traditional Internet, the main characteristics of electric
power dispatch data network architecture are focused on two aspects:
first, dispatch data network only carries electric power dispatching
services, and its business nature and performance requirements are
relatively fixed; second, once dispatch data network is established,
there are very few large-scale changes in grid topology structure, and
data transmission paths would rarely change.

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\textbf{Figure 5.} Framework of power dispatching data network

Figure 6 illustrates the classification and data flow direction of
electric power dispatching services. Among them, the services carried on
dispatch data network are mainly divided into control area services and
non-control area services. Typical control area services include
electric power monitoring system and management of safety device,
five-protection device, relay protection device, phasor measurement unit
(PMU), etc. The data transmission time delay requirement for such
control area services is at millisecond or second level, using real-time
subnets or dedicated channels of data transmission. Typical non-control
area services include online status monitoring, auxiliary monitoring
system, the management of electricity metering terminal and fault
waveform recorder, etc. The time delay requirement of such services is
at minute or hour level, using non-real-time subnets of data
transmission.

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\verb`image6.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 6.} Business category and data flow of power dispatching

In addition to control area and non-control area services, there is
management information zone for organization and management of
production and personnel. More services such as administrative telephone
network management, electric power enterprise data transmission are also
involved in such zone. These services of management information zone are
carried on enterprise data network.

3.2. Challenges of Electric Power Data Transmission

During the operation of power grid, the operating information of power
plant/station such as voltage, current, active power, reactive power,
circuit breaker opening/closing status is collected through various
sensors installed on primary equipment like lines, buses, circuit
breakers, transformers, generators, etc. Such information is used for
emergency control by local control devices such as relay protection and
safety automatic devices, and is also sent to dispatch master station
through dispatch data network channel.

The transmission of electric power data from a plant/station to dispatch
master station occurs in three ways: (1)some measurement data are
regularly sent to master station in real-time; (2) alarm information and
fault analysis results are sent directly after generation; (3)when the
master station summons monitoring signals and/or graphical model
information, the plant/station send data immediately. These data
transmission methods can be summarized as follows: when there is no
special data demand, data from plant/station are send to dispatch master
station periodically; when any plant/station or dispatch master station
triggers a data transmission event, such as the emergence of alarm
information in plant/station or data summon request from dispatch master
station, the plant/station would immediately send corresponding data to
the master station.

These data transmission methods are adopted because power grid has high
requirements on data transmission time delay performance. As a bridge
connecting power plants and load demands, any change in load side may
cause fluctuations in entire power grid's operating status. Various
protection devices and automatic control equipment are used to enhance
the local stability of power grid. And in order to maintain the safe and
stable operation of power network, real-time monitoring of whole network
status by dispatch control center is necessary. Currently, power grid
lacks technical methods to judge the credibility of electric power data
and mainly relies on traditional hardware such as firewalls and
encryption isolation devices to guard against malicious attacks and data
tampering. As energy infrastructure, power grid security defense level
urgently needs to be further improved.

Applying blockchain technology to the field of electric power data
transmission will bring three advantages: first, it effectively enhances
the credibility of electric power data, laying foundation for the future
intelligent and digital development of power grid; second, it can
establish a reliable data traceability mechanism, providing a basis for
the analysis and judgment of various events; third, it would optimize
current power data organization, supporting data governance and
management for power enterprises.

4. Electric Power Data Transmission Based on Parallel Proof of Work
Algorithm

Although blockchain technology can effectively enhance data credibility
and traceability, the drawbacks of current consensus algorithms restrict
their applications in electric power data transmission.

This paper proposes a Parallel Proof of Work algorithm (P-PoW) based on
early blockchain consensus mechanism, for the sake of enhancing the
credibility and traceability of electric power data transmission.

4.1. Principle of Parallel Proof of Work Algorithm

The core idea of Parallel Proof of Work algorithm is to separate Proof
of Work calculation process from new block generation process. Figure 7
shows the schematic diagram of Parallel Proof of Work algorithm
principle. The blockchain structure shown is similar to Figure 1, where
each block is divided into a block header and block data area. For P-PoW
algorithm, block header contains \emph{P} , which is a hash pointer to
previous block header. \emph{M} stands for the Merkle root hash of
current block data. \emph{TS} represents the timestamp at which moment
current block is generated. And \emph{S} is the signature of P-PoW
algorithm. The subscript indices in Fig. 7 representing current block
order. In block data area, \emph{D} is the electric power data written
into block, with two subscripts representing the position of data item
in block data area and the current block order, respectively.

Unlike PoW algorithm, P-PoW algorithm no longer iteratively calculates
block header to find a suitable random number \emph{nonce} to generate a
new block. Instead, P-PoW algorithm extracts the hash pointer
\emph{P}from block header and generates a signature \emph{S} by
iteratively executing P-PoW algorithm. At the same time, to achieve
real-time transmission of electric power data, P-PoW algorithm has
eliminated the block generation target field in block header.

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\textbf{Figure 7.} Diagram of Parallel PoW algorithm

Figure 8 is the flowchart of P-PoW algorithm. The process consists of
five steps: hash pointer computing, real-time data filling, iterative
calculation of current block signature, interruption triggering, and
block header assembly. Such steps in the flowchart are executed from top
to bottom, and the real-time data filling and block signature iterative
calculation steps are carried out simultaneously.

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\verb`image8.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 8.} Flow diagram of P-PoW algorithm

By analyzing above flowchart, it can be seen that P-PoW algorithm
proposed in this paper only needs to know the hash value \emph{P} of
previous block to start running, and this hash value is also referred to
as hash pointer. To generate a new block signature, P-PoW algorithm
combines hash pointer with a random number, and calculates the hash
value of combination string. During new block generation process, the
random number that minimizes the aforementioned hash value would be used
as the signature of that block. The above process can be represented by
following formula:

(1)

Where \emph{S} \textsubscript{n} is the signature of \emph{n} -th
block,\emph{P} \textsubscript{n} is the block header hash value of
(\emph{n-1} )-th block, \emph{H} (\selectlanguage{ngerman}·) is hash function, and\emph{r}
\textsubscript{d} is the random number generated in the\emph{d} -th
round computation in block generation process. In the generation process
of \emph{n} -th block, this random number\emph{r} \textsubscript{d}
minimizes the result of hash function\emph{H} (·) in equation (1).

During the iterative calculation of block signature, block data area is
simultaneously being filled with real-time data. Unlike Bitcoin
blockchain, the application scenario discussed uses blockchain to store
electric power data, where each data item \emph{D} can include fields
such as sampling time, data type, sampling value, station name,
equipment identity, etc. A possible implementation method will be
discussed in Chapter 4 of this paper.

In new block generation process, signature iterative calculation and
real-time data filling proceed parallelly, and these two processes
continue to run until timer reaches a predetermined moment or other
interrupting events occur. Subsequently, when interruption events
happen, hash pointer, Merkle root hash value, timestamp, block signature
of new block are determined. And the new block is added to blockchain.

4.2. Trusted Transmission Scheme for Electric Power Real-Time Data

Applying P-PoW algorithm to the transmission of electric power real-time
data requires further consideration of dispatch data network structure.
Figure 9 shows the structure of electric power dispatch data network,
where the core layer consists of provincial dispatch, backup dispatch,
and two important 500kV substations, forming a partial mesh network
between nodes; the backbone layer consists of 8 local dispatches and 14
hub substations, and the nodes in backbone layer connected each other in
a mesh or ring manner, forming a ring with the core layer nodes; the
access layer includes remaining 220kV and 110kV substations and 15 power
plants, with substation nodes connected to the backbone layer nodes in a
ring structure. It can be seen that electric power dispatch data network
presents a tree organization structure: from access layer to core layer,
the number of network nodes decreases, while the importance of nodes
increases. Consequently, the communication bandwidth and hardware
configuration of higher-level nodes are much higher than those of
lower-level nodes.

Considering electric power dispatch data network characteristics, P-PoW
algorithm can be applied to data transmission application scenario
between substations, power plants, and dispatch control centers. Figure
10 shows real-time electric power data transmission method based on
P-PoW algorithm, where Substation A, Substation B, and the power plant
are all equipped with local computing and storage devices. And each node
maintains a blockchain to store electric power real-time data locally.
In substations and power plants, the dedicated servers collect real-time
data generated by various data acquisition devices, encapsulating
real-time data in block structures through P-PoW algorithm, and store
such data in local blockchain. Meanwhile, the substations and power
plants send new blocks to local dispatch nodes incessantly.

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\textbf{Figure 9.} Structure of power dispatching data network

In above application scenarios, there are two strategies for uploading
new block information: one is that the plant/substation regularly upload
new block information to dispatch center, and this strategy can be
realized by utilizing the automated timing devices installed in
plants/substations. When the counter of timing device reaches a
specified value, it triggers an interruption to upload block
information. Another strategy is that local dispatch sends data summon
request to plants/substations, and the corresponding plants/substations
upload new block information immediately after receiving such summoning
message. Under either strategy, once the event to upload new block
information is triggered, P-PoW algorithm would instantly stop the
real-time data filling and signature iterative calculation progress, and
assembles the block header. Then, new block information is sent to local
dispatch center as soon as possible.

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\textbf{Figure 10.} Real-time transmission of electric power data based
on P-PoW algorithm

After receiving new block information from plants/substations, regional
dispatch center can verify the signature validation in new block. New
block can be considered trustworthy if its signature satisfies the
following inequality:

\selectlanguage{english}(2\selectlanguage{english})

In inequality (2), \emph{P} represents new block hash pointer
value,and\emph{Sig} is the block signature, \emph{Addr} is the address
space of hash function outcome \emph{Hash} (*), \emph{CP} is
computational power (TH/s) configured in the corresponding
plant/substation, \selectlanguage{greek}Δ\selectlanguage{english}\emph{T} \textsubscript{b} is the time duration from
receiving moment of previous block to the receiving moment of current
block, and \selectlanguage{greek}Δ\selectlanguage{english}\emph{T} \textsubscript{t} is the time consumption in
communication transmission process. Considering many factors such as
computing power fluctuation, environment influence and uncertainty of
transmission time can affect the computational result of left side of
inequality (2), a coefficient \emph{K} is added to the right side of the
equality to relax the verification condition. The specific value of
\emph{K} can be determined based on the actual experimental test.

If new block signature does not satisfy (2), the dispatch center would
reject the block. At this point, dispatch center may request
corresponding plant/station to resend the latest block or send alarm
message to dedicated personnel. For any attacker who wishes to tamper
with electric power data via the communication channel, there are two
challenges:  In order to make dispatch center accept tampered data, the
attacker must own sufficient computing power to produce a ``good
enough'' signature satisfying inequality (2);  The attacker must
possess the historical information of the blockchain to make the header
hash pointer \emph{P} conform to the rules of blockchain generation. By
using a dedicated hash algorithm and deploying specialized hardware,
while dispatching data network is used as communicational infrastructure
to transmit data, the data tampering cost would become tremendous high
that seldom individuals or organizations can afford. Therefore, the
trustworthy transmission of real-time electric power data is guaranteed.

5. Simulation Verification

To validate the feasibility of P-PoW algorithm, this paper implements a
simplified blockchain system for real-time electric power data
transmission using C++ programming language and Qt library. Simulation
experiment verifies the effectiveness of P-PoW algorithm for real-time
data transmission application.

5.1. Blockchain Program Architecture Based on P-PoW Consensus Algorithm

The main application scenario of P-PoW algorithm in this paper is
point-to-point data transmission. Considering the convenience of program
implementation and debugging, a multi-thread architecture is used to
build experimental program. Figure 11 shows the architecture of the
experimental program, which is divided into four threads: real-time data
generation thread, block data maintenance thread, P-PoW computation
thread, and human-machine UI interaction thread.

\textbf{Hosted file}

\verb`image13.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 11.} Structure diagram of experiment progress

As shown in the figure, Thread 1 simulates data collection function of
plant/station, implementing real-time data generation through the
program. Thread 2 creates a blockchain data structure
called\emph{BlockChain} , and fills real-time data generated by Thread 1
into the structure. Thread 3 implements P-PoW algorithm, and Thread 2
calls Thread 3 to realize proof of work of \emph{BlockChain} . Thread 4
is responsible for implementing human-machine UI interaction, and it
also communicates with Thread 2 to achieve timely reading and real-time
summoning of block data. Thread 1 to 3 together realize the data
collection, local blockchain generation, and storage functions of
plant/station, while Thread 4 plays the role of local dispatch center in
Figure 9.

\textbf{Hosted file}

\verb`image14.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 12.} User interface of experiment progress

By implementing multi-thread program architecture, P-PoW algorithm runs
in a individual thread, and the consensus algorithm of Thread 3 is
independent of blockchain data filling process which is implanted in
Thread 2. Therefore, the simulation program runs in exactly the same
manner as P-PoW algorithm should practically do. Furthermore, through
the communication interaction between Thread 4 and Thread 2, users can
choose Thread 2 to generate new blocks periodically and display related
information on UI interface, or to trigger an interruption event to
achieve real-time data summoning.

Figure 12 shows the user interface of the experimental program, where
the display area is mainly divided into two regions:  block header
information display region block data information display region. It
also allows for the adjustment of new block generation speed, searching
block information by index, real-time data summon, and other functions.
The fields in the block header and block data regions are explained in
Table 1.

Tab.1 Names and explanations of experiment program fields\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\textbf{Block Header Field} & \textbf{Explanations} &
\textbf{Unit}\tabularnewline
\midrule
\endhead
Index & Height of Block & ---\tabularnewline
PreHash & Previous Block hash & ---\tabularnewline
Timestamp & Block Timestamp & second\tabularnewline
MerkleRoot & Merkle Root hash & ---\tabularnewline
Sig & Block Signature & ---\tabularnewline
Hash(PreHash+Sig) & Hash value of (PrHash+Sig) & ---\tabularnewline
\textbf{Block Data Field} & \textbf{Explanation} &
\textbf{Unit}\tabularnewline
Station & Sation Name & ---\tabularnewline
Rating & Station Ranking & kV\tabularnewline
Device & Measurement Device & ---\tabularnewline
Value & Measurement Value & kV\begin{CJK}{UTF8}{gbsn}、\end{CJK}\selectlanguage{english}A\tabularnewline
Angle & Phasor Angle & degree\tabularnewline
Moment & Measurement Moment & second\tabularnewline
\bottomrule
\end{longtable}

5.2. Simulation Experiment Results

To further validate P-PoW algorithm, this paper uses a boosting station
of a photovoltaic power plant as assumed data collection object for
program verification. Figure 13 provides the main connection schematic
diagram of boosting station. Typically, the boosting station of
photovoltaic power plant adopts line-transformer group connection, with
the high-voltage side connected to the upper-level substation and the
low-voltage side lines leading to the photovoltaic plant. To monitor the
operation of photovoltaic power plant in real time, dispatch control
center needs to collect real-time data on the voltage and current of
boosting station. In this case, the main consideration is the data
collection of high-voltage side PT and high-voltage side No.1 interval
outgoing line CT of the main transformer, represented in the figure
as\emph{U} \textsubscript{TH} and \emph{I} \textsubscript{LH},
respectively. By default, voltage and current sampling data are saved
locally, and incremental sample data are sent to the local control
terminal for synchronization every 15 minutes.

\textbf{Hosted file}

\verb`image15.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 13.} Electrical connection diagram of boosting station
for photovoltaic power plant

Figure 14 shows screenshots of the simulation program in operation. In
Fig. 14(a), the detailed information of current block index, previous
block hash, Merkle root hash, signature value is presented in block
header information region. The signature is essentially a big random
integer in the program implementation, and P-PoW algorithm would select
the specific signature value to minimize the expression value
of\emph{Hash} (\emph{PreHash} +\emph{Sig} ). For the convenience of
validating P-PoW algorithm, the validation result\emph{Hash}
(\emph{PreHash} +\emph{Sig} )of current block is calculated and shown
below the region. However, it should be mentioned that the validation
result is not an entry existing in block header, it is only a program
calculation result to prove P-PoW algorithm works right in such
simulation.

In Fig. 14(b), the voltage and current sampling data are presented in
chronological order. In the simulation program, every entry of sampling
data includes information of station name, station ranking, measurement
device, measurement value, measurement time. In blockchain data
structure, all such information is organized by the form of byte
strings, so users can design their own data entry in the simulation
program as well.

The simulation screenshots in Fig. 14 show that the way the program
works is the same as in previous theoretical analysis, which proves the
validity of proposed P-PoW algorithm. The simulation program produces a
voltage sampling value and a current one every second, and such sampling
data are filled in block data region immediately. While data filling
process is autonomously executed, simulation program iteratively
searches the specific signature value which minimizes\emph{Hash}
(\emph{PreHash} +\emph{Sig} ) value simultaneously. The longer the
program execution time is, the more optimized signature would be found.

\textbf{Hosted file}

\verb`image16.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

(a) Screenshot of Block Header Information Region

\textbf{Hosted file}

\verb`image17.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

(b) Screenshot of Block Data Information Region\textbf{Figure 14.}
Screenshots of execution results of simulation program

By analyzing simulation results, Fig. 15 shows the generation time of
different block in simulation program. It can be noted that most blocks
take exactly 15 minutes for generation process. This is because many
sampling data in station/plant are required to transmitted to dispatch
center for every 15 minutes according to electricity industry
regulations. For the program implementation, a timer is used to trigger
an interruption for generating new block. However, if users need to
acquire data immediately, they can summon data through simulation
program interface. Such occasions, which are called data summon events,
happen on block 7, block 15, block 25 and block 35, and it can be seen
the generation time of those blocks is less than 15 minutes. Moreover,
due to the existence of program timer, the subsequent block after any of
these blocks also possesses generation time less than 15 minutes.

\textbf{Hosted file}

\verb`image18.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 15.} Generation time of blocks for simulation program

A data visualization of further study on the number of data entries is
illustrated in Fig. 16, and for the explicit, the data in first 300
minutes are only presented. Since the simulation program produces a
current measurement data entry and a voltage one, the number of data
entries stored in boosting station increases linearly. Meanwhile, when a
new block is generated, the data produced in such new block generation
process are stored in blockchain at once, hence a data synchronization
between boosting station and blockchain happens. And that is the reason
why the number of data entries in blockchain grows in a stepwise way.
Furthermore, when a data summon event happens, the synchronization time
would be advanced, so some ``narrower'' steps can be seen in the diagram
of Fig. 16.

\textbf{Hosted file}

\verb`image19.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 16.} Number of data entries in simulation program

In blockchain, each block generation process consumes a certain amount
of hash computing power, therefore it can be regarded as every block has
its own hash computing power inherently. Furthermore, since new blocks
are generated based on former blocks, the hash computing power in one
block would be accumulated. Any attacker trying to tamper with the data
in one block should owns higher hash computing power than the one
possessed by that block. Fig. 17 shows the hash computing power of block
1-7. From the diagram, it can be seen a former block always has higher
hash computing power than that of newer ones. And as time goes by, the
hash computing power of all blocks would increase. Such phenomenon can
be treated as an evidence for proving the safety of blockchain with
proposed P-PoW algorithm: the longer time the system runs, the harder an
attack could be made.

\textbf{Hosted file}

\verb`image20.emf`  available at \url{https://authorea.com/users/658276/articles/662695-research-of-trusted-real-time-electrical-data-transmission-mechanism-based-on-parallel-proof-of-work-algorithm}

\textbf{Figure 17.} Blocks hash computing power in simulation program

Tab.2 Comaprison of P-PoW and PoW algorithms\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
& \textbf{PoW} & \textbf{P-PoW}\tabularnewline
\midrule
\endhead
\textbf{Credibility} & high & Medium\tabularnewline
\textbf{Energy Consumption} & high & low\tabularnewline
\textbf{Data Transmission Bandwidth} & low & high\tabularnewline
\textbf{Minimum Hash Computation} & Global Computation & Local
Computation\tabularnewline
\textbf{Verification Method} & Difficulty-Based & Short-Term Hash
Rate-Based\tabularnewline
\bottomrule
\end{longtable}

Table 2 lists the characteristics comparison between the proposed P-PoW
algorithm and the traditional PoW algorithm. In the PoW algorithm, the
trust level of block data is based on the total computational power
across all network nodes as it searches for the minimal hash value,
making its credibility strictly higher than that of the P-PoW algorithm.
On the other hand, the PoW algorithm leads to high energy consumption,
slow new block generation, and low data upload bandwidth due to
utilizing the total network computational power. The P-PoW algorithm,
conducting the minimal hash value search through local computational
power, has lower energy consumption, larger data upload bandwidth, and
the data receiver can verify the sender's computational power through
the hash value, increasing the difficulty for data tampering.
Furthermore, P-PoW parallelizes the proof of work with new block data
filling, enabling real-time new block generation, suitable for real-time
electric power data transmission and other applications.

6. Conclusion

Based on the principles of the blockchain proof of work algorithm, this
paper proposes a parallel proof of work method. By parallelizing the
proof of work process with the new block data filling, the blockchain
system can real-time generate and transmit new blocks, overcoming issues
such as high energy consumption, slow new block creation, and low data
upload bandwidth.

The results of computer program simulation demonstrate that the proposed
parallel proof of work algorithm can be effectively applied to real-time
data transmission scenarios like electric power data transmission. While
enhancing data transmission trustworthiness, it retains functions such
as timed data uploading and real-time data retrieval. This offers a
feasible solution to the data security transmission problem in the
digitization and intelligent development of the power grid.

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