scholarly journals When Energy Trading Meets Blockchain in Electrical Power System: The State of the Art

2019 ◽  
Vol 9 (8) ◽  
pp. 1561 ◽  
Author(s):  
Naiyu Wang ◽  
Xiao Zhou ◽  
Xin Lu ◽  
Zhitao Guan ◽  
Longfei Wu ◽  
...  
Keyword(s):  
Power System ◽  
Electrical Power ◽  
System Optimization ◽  
Assessment Model ◽  
Security And Privacy ◽  
Renewable Energy Resources ◽  
Electrical Power System ◽  
Trading System ◽  
Energy Trading ◽  
Low Efficiency

With the rapid growth of renewable energy resources, energy trading has been shifting from the centralized manner to distributed manner. Blockchain, as a distributed public ledger technology, has been widely adopted in the design of new energy trading schemes. However, there are many challenging issues in blockchain-based energy trading, e.g., low efficiency, high transaction cost, and security and privacy issues. To tackle these challenges, many solutions have been proposed. In this survey, the blockchain-based energy trading in the electrical power system is thoroughly investigated. Firstly, the challenges in blockchain-based energy trading are identified and summarized. Then, the existing energy trading schemes are studied and classified into three categories based on their main focuses: energy transaction, consensus mechanism, and system optimization. Blockchain-based energy trading has been a popular research topic, new blockchain architectures, models and products are continually emerging to overcome the limitations of existing solutions, forming a virtuous circle. The internal combination of different blockchain types and the combination of blockchain with other technologies improve the blockchain-based energy trading system to better satisfy the practical requirements of modern power systems. However, there are still some problems to be solved, for example, the lack of regulatory system, environmental challenges and so on. In the future, we will strive for a better optimized structure and establish a comprehensive security assessment model for blockchain-based energy trading system.

scholarly journals SPETS: Secure and Privacy-Preserving Energy Trading System in Microgrid

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8121
Author(s):  
Ahmed Samy ◽  
Haining Yu ◽  
Hongli Zhang ◽  
Guangyao Zhang
Keyword(s):  
Smart Grids ◽  
Energy Allocation ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Smart Devices ◽  
Energy Market ◽  
Sensitive Information ◽  
Renewable Energy Resources ◽  
Trading System ◽  
Energy Trading

Recently, the development of distributed renewable energy resources, smart devices, and smart grids empowers the emergence of peer-to-peer energy trading via local energy markets. However, due to security and privacy concerns in energy trading, sensitive information of energy traders could be leaked to an adversary. In addition, malicious users could perform attacks against the energy market, such as collusion, double spending, and repudiation attacks. Moreover, network attacks could be executed by external attackers against energy networks, such as eavesdropping, data spoofing, and tampering attacks. To tackle the abovementioned attacks, we propose a secure and privacy-preserving energy trading system (SPETS). First, a permissioned energy blockchain is presented to perform secure energy transactions between energy sellers and buyers. Second, a discrete-time double auction is proposed for energy allocation and pricing. Third, the concept of reputation scores is adopted to guarantee market reliability and trust. The proposed energy system is implemented using Hyperledger Fabric (HF) where the chaincode is utilized to control the energy market. Theoretical analysis proves that SPETS is resilient to several security attacks. Simulation results demonstrate the increase in sellers’ and buyers’ welfare by approximately 76.5% and 26%, respectively. The proposed system ensures trustfulness and guarantees efficient energy allocation. The benchmark analysis proves that SPETS consumes few resources in terms of memory and disk usage, CPU, and network utilization.

scholarly journals A streamlined 17-level cascaded H-bridge multilevel converter with solar PV integration

2021 ◽  
Vol 10 (2) ◽  
pp. 598-608
Author(s):  
Muhammad Hamza Shahbaz ◽  
Kashif Amjad ◽  
Naqash Ahmad ◽  
Arslan Ahmed Amin ◽  
Sajid Iqbal ◽  
...  
Keyword(s):  
Power System ◽  
Electrical Power ◽  
Cost Comparison ◽  
Power Electronic ◽  
Solar Pv ◽  
Renewable Energy Resources ◽  
Multilevel Converter ◽  
Power Electronic Converters ◽  
Electrical Power System ◽  
Proposed Model

The quest for a green electrical power system has increased the use of renewable energy resources and power electronic converters in the existing power system. These power electronic converters, however, are a major cause of harmonics and result in the degradation of power quality. In the last two decades, researchers have proposed various designs of multilevel converters to minimize these harmonic distortions, however, a comprehensive solution for stand-alone solar photovoltaic (PV) systems with low total harmonic distortion (THD) is still missing in the present body of knowledge. This paper proposes a single-phase 17-level cascaded H-bridge multilevel converter (CHMC) model for a stand-alone system using solar PV arrays. The proposed model employs eight different flexible PV arrays that can be replaced with DC voltage sources when required to meet the load demand. The proposed model does not include any capacitor and filter thus saving a lot of cost in the overall system. The model has been implemented in the Simulink environment using a model-based design approach. The simulation results show that the proposed model has reduced the THD to almost 7% as compared to the existing models. The cost comparison of the proposed converter also proved its economic benefit over other types.

scholarly journals A Review of Considered Factors to Penetrate Renewable Energy Resources in Electrical Power System

KnE Energy ◽  
2015 ◽  
Vol 1 (1) ◽  
pp. 52
Author(s):  
Dhanis Woro Fittrin Selo Nur Giyatno
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Distributed Generation ◽  
Electrical Power ◽  
Energy Resources ◽  
Maintenance Cost ◽  
Renewable Energy Resources ◽  
Electrical Power System ◽  
Greenhouse Gasses

<p>As an increasing of load demand, scarcity of fossil fuel and penetration of greenhouse gasses (GHG) effect, utilization of renewable energy resources (RER) such as wind, solar, biomass and tidal are rising drastically. Distributed generation (DG) is a technology giving opportunity to integrate RER into power system network. These integrations are needed optimal long term planning. Those planning, hopefully, can increase reliability of electrical power system network while saving environment from GHG with minimum infestation, operation and maintenance cost. The aim of this paper is reviewing factors should be consider when preparing, operating and evaluating electrical power system with integration of RER. By this planning, it is expected that its integration is effective and efficient in a lifetime of project. Finally, this review can help government, researcher, engineer and private sector to make policies to preparing hybrid power system-DGs.  </p><p><strong>Keywords</strong>: <em>Penetration of renewable energy resources, electrical power system, long term planning, distributed generation, policies  </em></p>

Gradient Ascent Optimization for Fault Detection in Electrical Power System Based on Wavelet Transformation

2019 ◽  
Vol 14 ◽  
Author(s):  
Iyappan Murugesan ◽  
Karpagam Sathish
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Power System ◽  
Electrical Power ◽  
Daubechies Wavelet ◽  
Electrical Power System ◽  
Gradient Ascent ◽  
Neural Learning ◽  
Weight Value ◽  
Transmission And Distribution

: This paper presents electrical power system comprises many complex and interrelating elements that are susceptible to the disturbance or electrical fault. The faults in electrical power system transmission line (TL) are detected and classified. But, the existing techniques like artificial neural network (ANN) failed to improve the Fault Detection (FD) performance during transmission and distribution. In order to reduce the power loss rate (PLR), Daubechies Wavelet Transform based Gradient Ascent Deep Neural Learning (DWT-GADNL) Technique is introduced for FDin electrical power sub-station. DWT-GADNL Technique comprises three step, normalization, feature extraction and FD through optimization. Initially sample power TL signal is taken. After that in first step, min-max normalization process is carried out to estimate the various rated values of transmission lines. Then in second step, Daubechies Wavelet Transform (DWT) is employed for decomposition of normalized TLsignal to different components for feature extraction with higher accuracy. Finally in third step, Gradient Ascent Deep Neural Learning is an optimization process for detecting the local maximum (i.e., fault) from the extracted values with help of error function and weight value. When maximum error with low weight value is identified, the fault is detected with lesser time consumption. DWT-GADNL Technique is measured with PLR, feature extraction accuracy (FEA), and fault detection time (FDT). The simulation result shows that DWT-GADNL Technique is able to improve the performance of FEA and reduces FDT and PLR during the transmission and distribution when compared to state-of-the-art works.

scholarly journals Optical Voltage Transformer Based on FBG-PZT for Power Quality Measurement

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2699
Author(s):  
Marceli N. Gonçalves ◽  
Marcelo M. Werneck
Keyword(s):  
Power System ◽  
Power Quality ◽  
Distribution System ◽  
Electrical Power ◽  
Quality Measurement ◽  
Pockels Effect ◽  
Electrical Power System ◽  
Voltage Transformer ◽  
Technical Literature ◽  
Distribution Lines

Optical Current Transformers (OCTs) and Optical Voltage Transformers (OVTs) are an alternative to the conventional transformers for protection and metering purposes with a much smaller footprint and weight. Their advantages were widely discussed in scientific and technical literature and commercial applications based on the well-known Faraday and Pockels effect. However, the literature is still scarce in studies evaluating the use of optical transformers for power quality purposes, an important issue of power system designed to analyze the various phenomena that cause power quality disturbances. In this paper, we constructed a temperature-independent prototype of an optical voltage transformer based on fiber Bragg grating (FBG) and piezoelectric ceramics (PZT), adequate to be used in field surveys at 13.8 kV distribution lines. The OVT was tested under several disturbances defined in IEEE standards that can occur in the electrical power system, especially short-duration voltage variations such as SAG, SWELL, and INTERRUPTION. The results demonstrated that the proposed OVT presents a dynamic response capable of satisfactorily measuring such disturbances and that it can be used as a power quality monitor for a 13.8 kV distribution system. Test on the proposed system concluded that it was capable to reproduce up to the 41st harmonic without significative distortion and impulsive surges up to 2.5 kHz. As an advantage, when compared with conventional systems to monitor power quality, the prototype can be remote-monitored, and therefore, be installed at strategic locations on distribution lines to be monitored kilometers away, without the need to be electrically powered.

Analysis between graph-based and Power Transfer Distribution Factors (PTDF)-based model reduction methods in Electric Power Systems

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Diego A. Monroy-Ortiz ◽  
Sergio A. Dorado-Rojas ◽  
Eduardo Mojica-Nava ◽  
Sergio Rivera
Keyword(s):  
Power Systems ◽  
Power System ◽  
Model Reduction ◽  
Electrical Power ◽  
Schur Complement ◽  
Power Transfer ◽  
Electrical Power System ◽  
Admittance Matrix ◽  
Test Beds ◽  
Power Transfer Distribution Factors

Abstract This article presents a comparison between two different methods to perform model reduction of an Electrical Power System (EPS). The first is the well-known Kron Reduction Method (KRM) that is used to remove the interior nodes (also known as internal, passive, or load nodes) of an EPS. This method computes the Schur complement of the primitive admittance matrix of an EPS to obtain a reduced model that preserves the information of the system as seen from to the generation nodes. Since the primitive admittance matrix is equivalent to the Laplacian of a graph that represents the interconnections between the nodes of an EPS, this procedure is also significant from the perspective of graph theory. On the other hand, the second procedure based on Power Transfer Distribution Factors (PTDF) uses approximations of DC power flows to define regions to be reduced within the system. In this study, both techniques were applied to obtain reduced-order models of two test beds: a 14-node IEEE system and the Colombian power system (1116 buses), in order to test scalability. In analyzing the reduction of the test beds, the characteristics of each method were classified and compiled in order to know its advantages depending on the type of application. Finally, it was found that the PTDF technique is more robust in terms of the definition of power transfer in congestion zones, while the KRM method may be more accurate.

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