International Transactions on Electrical Energy Systems
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Acceptance rate26%
Submission to final decision72 days
Acceptance to publication36 days
CiteScore4.000
Journal Citation Indicator0.640
Impact Factor2.639

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International Transactions on Electrical Energy Systems publishes original research results on key advances in the generation, transmission, distribution, and conversion of electrical energy systems. 

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International Transactions on Electrical Energy Systems maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

 

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Research Article

Block-Based Multicut Benders Decomposition Algorithm for Transmission and Energy Storage Co-Planning

This study proposes a block-based multicut Benders decomposition algorithm to solve the co-planning of transmission expansion and energy storage problem in a bi-level approach. The proposal breaks the chronological representative period into multiple subperiods blocks. This division makes it possible to use parallel computation methods to solve each block simultaneously, reducing the simulation time, which allows the use of a more extensive time window to model the variability of random variables of the system, such as wind and load. In the proposed algorithm, the master problem defines the State of Charge (SoC) of the energy storage devices between the blocks and the investment in transmission and energy storage devices. To demonstrate the effectiveness of the proposed method, different sizes of representative periods are evaluated in three test systems: Garver 6-bus, IEEE-RTS 24-bus, and IEEE-118 188-bus. The tests compare the performance of the proposed block-based multicut Benders decomposition algorithm with the usual approach applied in the literature considering Benders decomposition and the complete problem formulated as a Mixed-Integer Linear Programming (MILP) problem.

Research Article

Prophetic Energy Assessment with Smart Implements in Hydroelectricity Entities Using Artificial Intelligence Algorithm

An encouraging development is the quick expansion of renewable energy extraction. Harnessing renewable energy is economically feasible at the current rate of technological advancement. Traditional energy sources, such as coal, petroleum, and hydrocarbons, which have negative effects on the environment, are coming under more social and financial pressure. Companies need more solar and wind power because this calls for a well-balanced mix of renewable resources and a higher proportion of alternative energy sources. Sustainable energy can be captured using a variety of techniques. Massive scale and small-sized are the two most prevalent techniques. No renewable energy source possesses an inherent property that restricts how it may be managed or how it can be planned to produce electricity. A number of factors have contributed to a growth in the use of alternative sources, one of which is to mitigate the effects of rising temperatures. To improve the ability to estimate renewable energy, various modeling approaches have been created. This region might use an HRES to give many sources with the inclusion of different energy sources. The inventiveness of solar and wind power and the brilliant ability of neural networks to handle complex time-series data signals have both aided in the prediction of sustainable energy. Therefore, this research will examine the numerous information models in order to determine which proposed models can provide accurate projections of renewable energy output, such as sunlight, wind, or pumped storage. In the fields of sustainable energy predictions, a number of machine learning methods, such as multilayer perceptions MLP, RNN CNN, and LSTM designs, are frequently utilized. This form of modeling uses historical data to predict potential values and can predict short-term patterns in solar and wind generation.

Research Article

Analysis of Dynamic Relationship between Energy Consumption and Economic Growth Based on PVAR Model

In order to analyze the relationship between energy consumption and economic growth dynamics, the author proposes a dynamic analysis technology of energy consumption and economic growth based on the PVAR model. This technology uses the PVAR method to compare and quantitatively describe the relationship between economic growth and energy consumption in developed and developing countries from 1990 to 2009, using impulse response functions and variance decomposition analysis methods; study the similarities and differences between total energy consumption and various fossil energy consumption and the dynamic impact of economic development, and finally establish a PVAR model for analysis. Experimental results show that: in the forecast of variance analysis, the impact explanatory power of the total energy consumption of developing countries on the fluctuation of economic growth reaches 8.85070. However, the contribution of total energy consumption in developed countries to economic growth is insufficient. The explanatory power of economic growth in developed countries to total energy consumption is 15.58070, while that in developing country is 29.28070, both of which are greater than the explanatory power of their respective total energy consumption on economic growth. Conclusion. The technology based on the PVAR model can effectively meet the needs of analyzing the dynamic relationship between energy consumption and economic growth.

Research Article

Two-Layer Coordinated Energy Management Method in the Smart Distribution Network including Multi-Microgrid Based on the Hybrid Flexible and Securable Operation Strategy

With the advent of smart grid theory, distribution networks can include different microgrids (MGs). Therefore, to achieve the desired technical and economic objectives in these networks, there is a need for bilateral coordination between their operators. In the following, by defining an energy management problem for them, it is predicted that the mentioned goals can be achieved. Therefore, this paper presents the hybrid flexible-securable operation (HFSO) of a smart distribution network (SDN) with grid-connected multi-microgrids using a two-layer coordinated energy management strategy. In the first layer, the microgrid (MG) operator is coordinated with sources, storages, and demand response operators. This layer models the HFSO method in the grid-connected MGs, which is based on minimizing the difference between the sum of operating cost of nonrenewable distributed generations and cost of energy received from the SDN, and the sum of flexibility and security benefits. It is constrained to AC optimal power flow, flexibility and voltage security constraints, operation model of sources and storages, and demand response. The second layer concerns coordination between the MG operators and the SDN operator. Its formulation is the same as that of the first layer, except that the HFSO model is used in the SDN according to MGs power daily data obtained from the first layer problem. The strategy converts the mixed-integer nonlinear programming to linear one to obtain the optimal solution with low calculation time and error. Moreover, stochastic programming models the uncertainties of load, energy price, and renewable power. Eventually, numerical results confirm the capability of the scheme to improve technical and economic indices simultaneously. As a result, by expecting the optimal operation for sources, storage, and responsive loads, it succeeded to enhance energy loss, voltage profile, and voltage security of the mentioned networks by up to 30%, 22%, and 5%, respectively, compared to power flow studies. In addition, there was enhancement in economic and flexibility status of the SDN and MGs.

Research Article

Teaching Practice of Engineering Management Course for Engineering Education Certification under Background of Artificial Intelligence

With the advancement of China’s industrial construction, the field of engineering management has also attracted more attention. However, China’s engineering management major is currently in a growing stage due to the issue of the opening years, and the teaching and practice setting of each course is also in an immature stage, which makes China’s engineering management majors present more and more problems. The truancy rate has been increasing year by year, the students’ dominant position in the class has become objectified, and their trust in teachers has decreased. Students’ learning shows the characteristics of individualization and diversity. Higher requirements are put forward for teachers’ teaching quality, and schools lack an effective supervision mechanism. In order to solve these problems better, it is imperative to reform and innovate the course teaching of engineering management majors. The core of engineering education accreditation is to confirm that engineering graduates meet established quality standards recognized by the industry. It is a unique method to test whether the course teaching of engineering management majors is qualified and attracts many scholars to discuss it. Engineering education accreditation has attracted many scholars to discuss it because it is a unique means to test the qualifications of engineering management students’ course teaching. This study was based on an in-depth exploration of the teaching practice of engineering management courses and combines artificial intelligence with an engineering education certification. Through the research and analysis of colleges and universities, the research finally showed that the engineering management professional course teaching of engineering education certification under the background of artificial intelligence can promote the attendance of students in school by about 20%. The achievement of course teaching objectives has increased by about 13% and the comprehensive ability level of graduates has increased by about 8%. It improved the overall level of students and the teaching quality and efficiency of engineering management courses and also promoted the development of college education so that today’s engineering management graduates can better meet the needs of today’s society.

Research Article

Ecological Effects of Local Materials in Landscape Design based on Machine Learning

The local characteristic landscape is a way of adapting to nature, land, and land space pattern chosen by local people due to their living needs. With the in-depth development of the concept of ecological protection in China, great progress has been made in the cause of ecological environmental protection within the current urban area. This study mainly discusses the ecological effects of local materials in landscape design. It integrates geography, historical literature, landscape ecology, architectural aesthetics, and many other related disciplines. The basic knowledge of rural landscape elements is analyzed and summarized from all levels and angles. However, due to factors such as the contradiction between the urban and rural dual system, the large base of the rural population and construction land, the expansion of cities and the great changes in rural production and lifestyle, the rural living environment is faced with more ecological contradictions, which has become the bottleneck of the country’s overall ecological civilization construction. It comprehensively discusses and analyzes related concepts and theories, and optimizes the concept of rural landscape elements and the relationship between rural landscape elements and modern rural landscape design. It clarifies its classification and exemplifies the application methods of rural landscape elements. The second is to integrate and analyze the application of rural landscape elements through the investigation and analysis of excellent cases. It also compares the rural locality and studies the application of rural landscape elements and their shortcomings. Finally, the construction methods and application strategies of rural landscape elements in modern villages are proposed. Through the reasonable planning and configuration of the traditional village landscape, it creates a living landscape that can meet the actual needs of local people and an ornamental and experiential landscape that can meet the multilevel emotional needs of foreign tourists. This pushes traditional villages toward a benign path of sustainable development. The evaluation index of conformity between vernacular architecture and the environment reached 94%. On the basis of sorting out the problems of ecological planning and construction of rural human settlements, the article constructs the ecological adaptability theory of rural human settlement planning at the theoretical level. This study fully combines the advantages of local materials to build a beautiful village with regional cultural characteristics and ecological type, in order to open up new ideas for future rural planning and design.

International Transactions on Electrical Energy Systems
Publishing Collaboration
More info
Wiley Hindawi logo
 Journal metrics
See full report
Acceptance rate26%
Submission to final decision72 days
Acceptance to publication36 days
CiteScore4.000
Journal Citation Indicator0.640
Impact Factor2.639
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.