Energy Power Generation Technology Research Articles

Preface

The 2023 2nd International Conference on Renewable Energy and Electrical Technology (ICREET 2023) was held from December 22nd to 24th, 2023 in Tianjin, China via virtual form. With ICREET 2023, the conference series International Conference on Renewable Energy and Electrical Technology (ICREET) completed its second edition.ICREET 2023 attracted a number of papers related to renewable energy and electrical technology, including but not limited to: Renewable Energy Power Generation, Clean Production and Green Chemical Technology, Smart Grid Power Transmission and Distribution, Power System Modeling, Simulation and Analysis, Electric Traction Systems and Control, etc.All of the papers were exhaustively reviewed by the program committee members and peer-reviewers, who took into account the breadth and depth of the research topics that fall under the scope of ICREET. The most promising contributions were selected from all the submissions for presentation and inclusion in this paper volume, which presents innovative original ideas or results of general significance supported by clear and rigorous reasoning and compelling new evidence, as well as methods.The Conference agenda fell into mainly three parts, including keynote speeches, oral presentations, and academic investigation. Keynote speeches were performed by three distinguished professors: Prof. Abdul Hasib Chowdhury (Bangladesh University of Engineering and Technology, Bangladesh), whose research interests include power system planning, stability, reliability analysis, contingency and security analysis, power quality analysis etc., talked on Torsional Resonance in Turbine-Generator Shaft Due to the Operation of Multiple Electric Furnaces at Close Proximity, Assoc. Prof. Hidayat Bin Zainuddin (Universiti Teknikal Malaysia Melaka, Malaysia), who has authored and co-authored over 50 technical papers comprising journals and conference proceedings, and contributed in reviewing articles for many conferences and journals published by IEEE, Elsevier, etc., on Ester Oil as Greener Insulating Fluid for Oil-Filled Transformers, Assoc. Prof. Norzanah Rosmin (Universiti Teknologi Malaysia, Malaysia), who has 23 years’ experience in electrical engineering courses teaching and supervision of students’ projects and researches, and has published many papers in books, journals and conference proceedings and got numbers of awards for innovation projects based on her expertise, on Energy Efficiency and Energy Management System via Double Layer Approach for A Sustainable Future.We would like to acknowledge all the speakers, authors, Technical Program Committee members and anonymous reviewers for their efforts in making ICREET 2023 so successful. We’d also appreciate the support from the staff of Journal of Physics: Conference Series for making this volume published.The Committee of ICREET 2023List of Committee Member is available in this Pdf.

A Bi-level optimization dispatch for hybrid shipboard microgrid considering electricity-gas-heat coupling

With the increasingly severe problem of air pollution and energy crisis, new energy power generation technology in ship has quickly become the focus of attention. Compared with traditional ships, hybrid shipboard microgrid systems can achieve pollution-free, renewable and high use value. However, the integration of electricity-gas-heat in hybrid energy shipboard microgrid system also poses challenges to current optimization methods. Therefore, this paper develops a bi-level optimization dispatch model for hybrid shipboard microgrid system based on multi-objective particle swarm optimization algorithm. Taking the diesel generators, photovoltaic generation system, energy storage system (ESS) and thermal energy storage equipment into account, a hybrid shipboard microgrid system model considering electricity-gas-heat coupling is constructed. Based on this, a bi-level optimization dispatch model is established to reduce total cost, GHG (GHG) emissions and lifespan loss of ESS. The upper-level model achieves the optimization dispatch of power generation equipment and loads; a lower-level optimization model with the goal of reducing the lifespan loss of ESS is constructed. The improved multi-objective and single-objective particle swarm optimization algorithms are introduced to find the optimal dispatch solutions for bi-level optimization dispatch model. Finally, simulation results show that the proposed optimization method can not only reduce the cost and GHG emissions by 8.7% and 10.9%, but also improve the cycle life of ESS by 9.2%.

The Strategy of Continuous Commutation Failure Suppression by Combining Turn-off Angle Compensation and Dynamic Nonlinear VDCOL

In recent years, with the continuous growth in China’s economy, the continuous advancement of urbanization and industrialization, the contradiction between rapid economic development and the continuous reduction in traditional fossil energy reserves such as coal, oil, and natural gas, the continuous aggravation of environmental pollution has become increasingly prominent. In this era, clean energy power generation technologies such as hydropower, wind power, and solar power generation, which have the advantages of renewability, environmental protection, and economy, have developed rapidly. However, wind and photovoltaic power plants are often located in remote areas, which means significant losses in the transmission process. High-voltage direct current (HVDC) transmission technology becomes the best choice to solve this problem. The HVDC transmission system based on a grid commutator is widely used in China’s AC-DC hybrid power grid. When an AC fault occurs on the inverter side, the line-commutated converter high-voltage direct current (LCC-HVDC) system is more prone to continuous commutation failure, which brings serious harm to system operation. To better suppress the problem of continuous commutation failure on the contravariant side, this paper analyzes the mechanism of continuous commutation failure from multiple angles. The DC current command sensitivity of a voltage-dependent current order limiter (VDCOL) in the LCC-HVDC system is low, which will lead to different degrees of continuous commutation failure. In addition, the rapid rise in DC current and the drop in commutation voltage during the fault will cause the turn-off angle to drop, and the probability of continuous commutation failure of the system will increase significantly. Based on the above theoretical analysis, a new control strategy combining the dynamic compensation of the turn-off angle of a virtual inductor and the suppression of continuous commutation failure by dynamic nonlinear VDCOL is proposed. A dynamic nonlinear VDCOL control strategy is proposed for the low sensitivity of current command adjustment under conventional VDCOL control. Secondly, two concepts of virtual inductance and DC current change rate are introduced, and a control strategy based on virtual inductance is proposed to comprehensively ensure that the switching angle has sufficient commutation margin during fault recovery. Finally, based on the CIGRE standard test model in PSCAD/EMTDC, the accuracy of the correlation mechanism analysis and the effectiveness of the suppression method are verified.

Improving the Performance of Polydimethylsiloxane-Based Triboelectric Nanogenerators by Introducing CdS Particles into the Polydimethylsiloxane Layer.

Energy harvesting and power generation technologies hold significant potential for meeting future energy demands and improving environmental sustainability. A triboelectric nanogenerator (TENG), which harnesses energy from the surrounding environment, has garnered significant attention as a promising and sustainable power source applicable in various fields. In this study, we present a technique to improve the triboelectric performance of a PDMS-based TENG by incorporating nanostructured cadmium sulfide (N-CdS). This study investigates the utilization of CdS nanomaterials in TENG production, where mechanical energy is converted into electrical energy. We conducted a comparative analysis of TENGs utilizing N-CdS/PDMS, commercial CdS/PDMS (C-CdS/PDMS), and pure PDMS substrates. The N-CdS/PDMS substrates demonstrated superior triboelectric performance compared to TENG devices based on pure PDMS and C-CdS/PDMS. The triboelectric open-circuit voltage (Voc) and short-circuit current (Isc) of the N-CdS/PDMS-based TENG device were approximately 236 V and 17.4 µA, respectively, when operated at a 2 Hz frequency. These values were approximately 3 times and 2.5 times higher, respectively, compared to the pure PDMS-based TENGs. They were further studied in detail to understand the effect of different parameters such as contact-separation frequency and contact force on the TENGs' operation. The stability of the TENG devices was studied, and their potential to be integrated into self-powered smart textiles as power sources was demonstrated.

Life in biophotovoltaics systems.

As the most suitable potential clean energy power generation technology, biophotovoltaics (BPV) not only inherits the advantages of traditional photovoltaics, such as safety, reliability and no noise, but also solves the disadvantages of high pollution and high energy consumption in the manufacturing process, providing new functions of self-repair and natural degradation. The basic idea of BPV is to collect light energy and generate electric energy by using photosynthetic autotrophs or their parts, and the core is how these biological materials can quickly and low-loss transfer electrons to the anode through mediators after absorbing light energy and generating electrons. In this mini-review, we summarized the biological materials widely used in BPV at present, mainly cyanobacteria, green algae, biological combinations (using multiple microorganisms in the same BPV system) and isolated products (purified thylakoids, chloroplasts, photosystem I, photosystem II), introduced how researchers overcome the shortcomings of low photocurrent output of BPV, pointed out the limitations that affected the development of BPV' biological materials, and put forward reasonable assumptions accordingly.

Multicell nonisolated resonant modular multilevel dc‐dc converter with self‐voltage balancing and step‐up conversion

SummaryWith the rapid development of renewable energy power generation technologies in high‐voltage direct‐current (HVDC) system, the high step‐up ratio dc‐dc conversion plays an important role to connect dc grids with different voltage levels. This paper presents a multicell nonisolated resonant modular multilevel dc–dc converter (MMDC) for medium‐ and high‐voltage applications. The converter exhibits expandability without using transformer. Moreover, by adding additional switched‐inductor (SL) cells, switched‐capacitor (SC) cells, and the upper arm submodules (SMs), the proposed converter can obtain high gain with low voltage stresses on switches and diodes. The operating states of SMs is regulated by the carrier phase‐shifted pulse width modulation (CPS‐PWM) to guarantee the number of inserted SMs is constant to support the high‐side load at any moment. The converter is operated in resonant mode with resonance between SM capacitors and arm inductor. The step‐up ratio could be regulated by adjusting the number of SL cells, SC cells, and upper arm SMs; thus, more flexible voltage regulation can be realized. In addition, the proposed converter has the voltage self‐balancing capability of capacitors in SMs and SC‐cells without additional balancing control strategy. The topology configuration, parameter design guideline, operating principle, and comparison with other MMDCs are presented. Finally, the theoretical analysis is verified by the simulation and bench‐scaled experimental prototype results.

Application of Multimedia Quality Evaluation Relying on Intelligent Robot Numerical Control Technology in New Energy Power Generation System

New energy (NE) power generation technology has become an important means to solve the problems of global energy demand and environmental governance due to its sustainability and cleanliness. However, restricted by climate and other factors, the instability of its power generation capacity has a serious impact on the voltage multimedia quality evaluation of small microgrids, which even causes damage to important equipment. This paper proposed a multimedia quality evaluation method in the new energy power generation system relying on intelligent robot numerical control technology. According to the state characteristics of different units, the expanded representation models of conventional units, wind turbines, and photovoltaic units were established, respectively. Based on intelligent robot numerical control technology, a multimedia quality monitoring model of the new energy power generation system in random production simulation was established. The planned outage condition of the unit, which was ignored by the current stochastic simulation method, has been fully considered to ensure the rationality of the simulation of intelligent robot numerical control technology. The intelligent robot numerical control technology was used to explore the expected production power change of the unit and to improve the calculation speed and accuracy. In this paper, an appropriate wind and solar power generation model was constructed based on the output characteristics of wind and solar. Secondly, the influence of random faults between units on the subsequent loading rate was studied through probability calculation. The start-stop factors of conventional units were comprehensively analyzed. Then, the expected value of unit start-stop times was obtained. The average relative error of the expected value of the power shortage of the new energy electricity generation system (EGS) was 2.45%, and the error was lower than 2.98%. In the intelligent robot numerical control technology in this paper, the planned outage condition of the unit was considered, which showed the correctness and superiority of the multimedia quality evaluation of the proposed model.

Optimal Planning of Hybrid Electricity–Hydrogen Energy Storage System Considering Demand Response

In recent years, the stability of the distribution network has declined due to the large proportion of the uses of distributed generation (DG) with the continuous development of renewable energy power generation technology. Meanwhile, the traditional distribution network operation mode cannot keep the balance of the source and load. The operation mode of the active distribution network (ADN) can effectively reduce the decline in operation stability caused by the high proportion of DG. Therefore, this work proposes a bi-layer model for the planning of the electricity–hydrogen hybrid energy storage system (ESS) considering demand response (DR) for ADN. The upper layer takes the minimum load fluctuation, maximum user purchase cost satisfaction, and user comfort as the goals. Based on the electricity price elasticity matrix model, the optimal electricity price formulation strategy is obtained for the lower ESS planning. In the lower layer, the optimal ESS planning scheme is obtained with the minimum life cycle cost (LCC) of ESS, the voltage fluctuation of ADN, and the load fluctuation as the objectives. Finally, the MOPSO algorithm is used to test the model, and the correctness of the proposed method is verified by the extended IEEE-33 node test system. The simulation results show that the fluctuation in the voltage and load is reduced by 62.13% and 37.06%, respectively.

CFD analysis of gravity-fed drag-type in-pipe water turbine to determine the optimal deflector-to-turbine position

AbstractIn-pipe hydroelectric power generation is a relatively new clean energy power generation technology. This new clean energy technology has been identified to be feasible after successful commercial installation in different parts of the world. Several researchers worldwide have studied the optimal turbine type, the optimal number of blades in turbine, introduction of suitable deflector, etc. for this technology. However, the effect of the turbine's position relative to the upstream deflector on its performance has not been studied so far. This research encompasses a numerical study of the in-pipe hydroelectric power generation turbine to identify the optimal position of the turbine from the deflector. The study was performed for a 160-mm diameter pipeline and a 126-mm turbine height and aims to predict the behavior of larger diameter pipelines for commercial installation. The numerical study was performed for a hollow-type drag turbine at 6 different rotational speeds and 10 different turbine positions. The results suggest that the performance characteristics of drag-type turbine are erratic, thus leaving little space to draw a firm conclusion about the turbine's performance. However, there was an increase in pressure difference, head and available theoretical power with the increase in rotational speed for all the positions. It was also found that such turbines were generally more efficient at slightly higher rotational speeds, i.e. speed greater than 40 rad/s, and at about the distance of 0.65D (where D is the pipe diameter) between deflector's eye and turbine.Highlights: • Drag-type water turbines can significantly contribute to the production of clean energy. • We varied the turbine position and rotational speed to see how these parameters affects the turbine performance. • Computational fluid dynamics approach is used to study the behavior of turbine at different operating conditions.

Differentiated Configuration Options for Centralized and Distributed Energy Storage

With the rapid development of new energy power generation technology and the promotion and application of energy storage in smart grids, energy storage is more and more favored by people. Firstly, the energy storage technology is classified, and its role in the power grid is analyzed. Then, the economy of centralized and distributed energy storage is analyzed. Further, according to the technical and economic characteristics of centralized energy storage and distributed energy storage, the applications of these two types of energy storage are introduced. Finally, based on the characteristics of renewable energy in Jilin Province, recommendations are made for the placement of energy storage in Jilin Province in the context of “carbon neutrality and carbon peaking.”

An Optimized Algorithm for Renewable Energy Forecasting Based on Machine Learning

The large-scale application of renewable energy power generation technology brings new challenges to the operation of traditional power grids and energy management on the load side. Microgrid can effectively solve this problem by using its regulation and flexibility, and is considered to be an ideal platform. The traditional method of computing total transfer capability is difficult due to the central integration of wind farms. As a result, the differential evolution extreme learning machine is offered as a data mining approach for extracting operating rules for the total transfer capability of tie-lines in wind-integrated power systems. K-medoids clustering under the two-dimensional “wind power-load consumption” feature space is used to define representative operational scenarios initially. Then, using stochastic sampling and repetitive power flow, a knowledge base for total transfer capability operating rule mining is created. Then, a novel method is used to filter redundant characteristics and find features that are closely associated to the total transfer capability in order to decrease the ultra-high dimensionality of operational features. Finally, by feeding the training data into the proposed algorithm, the total transfer capability operation rules are derived from the knowledge base. It can be seen that, the proposed algorithm can optimize the system performance with good accuracy and generality, according to numerical data.

Advancement of Tidal Current Generation Technology in Recent Years: A Review

Renewable energy provides an effective solution to the problem existing between energy and environmental protection. Tidal energy has great potential as a form of renewable energy. Tidal current generation (TCG) technology is the earliest renewable energy power generation technology. The advancement of science and technology has led to TCG rapidly developing since its emergence in the last century. This paper investigates the development of TCG in recent years based on the key components of TCG systems, both in terms of tidal energy harvesting research and power generation unit research. A summary of tidal energy harvesting is presented, investigating the main tidal energy harvesting units currently available. In addition, research on generators and generator control is summarized. Lastly, a comparison between horizontal and vertical axis turbines is carried out, and predictions are made about the future trends in TCG development. The purpose of this review is to summarize the research status and research methods of key components in tidal energy power generation technology and to provide insight into the research of tidal energy-related technologies.

Analysis of the mechanism of renewable energy on energy-saving and environmental protection industry: Empirical evidence from four countries

The “Carbon Peaking and Carbon Neutrality” strategy of China has accelerated the process of industrial structure transformation of global energy-saving and environmental protection. With the international efforts to cope with climate change and the growing consensus on low-carbon energy, many countries have introduced policy measures to promote the development of the renewable energy industry. This paper constructs an empirical model to analyze the mechanism of four kinds of renewable energy power generation technologies on energy consumption in four countries, and further discusses the impact of main renewable energy power generation technologies on the development of the smart environmental protection industry of China under the “Carbon Peaking and Carbon Neutrality” goal. The results show that there is a huge gap in renewable energy technologies among different countries. There is technical heterogeneity in the effects of four kinds of renewable energy technologies on energy consumption, which can effectively reduce energy consumption on the whole. Renewable energy technologies have an impact on the development of the smart environmental protection industry in China from different aspects, which is generally conducive to promoting the development of energy-saving and environmental protection emerging industry. Finally, combined with the empirical conclusions, this paper puts forward suggestions on how to effectively optimize the construction of energy-saving and environmental protection emerging industry in the development of renewable energy technologies.

Study on electromagnetic transient numerical simulation of single-phase inverter circuit

With the continuous progress and development of new energy power generation technology, new energy grid and power electronic devices are widely used in power system, and the modeling requirements for electromagnetic transient simulation analysis of power system are higher and higher. Combined with the research status at home and abroad, this paper first analyzes the single-phase inverter circuit model, and establishes the mathematical model of single-phase inverter circuit in different switching states. Based on the stability, accuracy and efficiency of numerical integration algorithm, different numerical integration substitution methods are applied to the mathematical model established in each state of the circuit, and the electromagnetic transient analysis of single-phase inverter circuit is carried out the correctness and feasibility of the experimental results are verified by comparing with the results in Simulink.

Global renewable energy power generation efficiency evaluation and influencing factors analysis

The progress of renewable energy development varies around the world, and it's necessary to quantitatively measure the power generation efficiency (PGE) of each country. This study considers five types of renewable energy installed capacity as input indicators and renewable energy power generation as an output indicator. Based on panel data of 36 countries from 2009 to 2018, renewable energy PGE is calculated based on the super-efficiency data envelopment analysis model and is decomposed annually using the Malmquist index. Finally, a random forest regression model was used to evaluate the influencing factors of renewable energy PGE in each country. The results show that the global renewable energy development space pattern has formed. The differences in PGEs between countries are evident, and the correlation between the ranking of renewable energy installed capacity and the average ranking of PGE is weak. The reverse effect of technological progress hinders the growth of renewable energy PGE. Only 41.67 % of all countries are improving PGE, and renewable energy power generation technology is in urgent need of improvement. Among the eleven influencing factors, carbon emissions level and industrial structure have the greatest impact on PGE, followed by electricity structure, technology level, and economic level.

Analysis of grid-connected operation characteristics and limit access capacity of offshore wind farms

Wind power is a relatively ripe renewable energy power generation technology, which has the superiority of large-scale development and utilization. Large-scale deep-sea wind farms are a significant direction for wind power development. With the continuous growth of the capacity of a single offshore wind farm, it is necessary to study the impact of grid connection of large-capacity offshore wind farms on the normal operation of the power grid, which can guarantee the safety and stability of the power grid. Based on the smooth working of the power system, it is meaningful to determining the limit access capacity of offshore wind farms for guiding offshore wind power planning. In this paper, an evaluation index system for the operation characteristics of offshore wind farms integrated into regional power grids is constructed, and based on that, the influence of offshore wind farms on the safety, stability, economy and power quality of regional power system operation is studied, and the grid-connected power limit of offshore wind farms is further calculated.

Short‐term photovoltaic power prediction based on MDCM‐GA‐LSTM model

In recent years, photo-voltaic (PV) system has become one of the most potential renewable energy power generation technologies because of its many advantages. Considering the influence of the randomness of PV system on the operation and dispatching of power system, the necessity of a comprehensive forecasting model is increased rapidly. This paper proposes a short-term PV power forecasting method based on MDCM-GA-LSTM model to solve the problem of low accuracy of traditional and single forecasting model. First, the meteorological data are pre-processed based on wavelet denoising algorithm to improve the data quality. Second, a meteorological model is established based on genetic algorithm (GA) to optimize long short-term memory (LSTM) neural network. Finally, the network is trained with the modified data of the meteorological model as the input and the actual power as the output, and the power forecasting model is established. In this study, the forecasting accuracy is evaluated based on mean absolute error (MAE) and root mean square error (RMSE). The experimental results demonstrated that the MDCM-GA-LSTM model outperforms the conventional and single model by a difference of about 98.43% of the MAE and 98.97% of the RMSE error.

Transient Synchronizing Stability of Droop-Controlled Converter during Grid Fault Considering Current Saturation Limitation

Traditional power systems usually rely on synchronous generators to provide inertia and maintain grid stability. However, with the continuous development of new energy power generation technologies, more and more converter power supplies provide voltage and frequency support for the power grid. The synchronizing instability issue of a converter-dominated power system becomes increasingly relevant, which exists in both grid-following (GFL) and grid-forming (GFM) converters. In this paper, the transient synchronizing stability of grid-forming (GFM) converters with droop-control during a grid fault is studied, with the influence of current saturation limitation considered especially. The current saturation limitation applied to limit overcurrent during grid faults brings transient voltage-source/current-source switched mode of the converter, which significantly influences the transient behavior. Considering the influence, an equivalent motion model similar to the rotor motion of a synchronous generator is developed first to depict the transient synchronizing dynamics. It has been identified that the current saturation limitation reconstructs the power angle characteristics, which significantly influence the transient stability. Then based on the developed model, transient synchronizing stability during a grid fault is studied based on the accelerating–decelerating area method. With the influence of grid impedance and grid voltage sag considered, several kinds of transient synchronizing stability issues are revealed clearly. Finally, simulated results are presented to verify the theoretical analysis. The analysis of this article paves the way for the follow-up research on the synchronizing stability of multi-converters and the corresponding control methods to improve synchronizing stability.

Greenhouse gases emission reduction for electric power generation sector by efficient dispatching of thermal plants integrated with renewable systems

This research aims to contribute in developing a mathematical model for the composite probabilistic energy emissions dispatch (CPEED) with renewable energy systems, and it proposes a novel framework, based on an existing astute black widow optimization (ABWO) algorithm. Renewable energy power generation technology has contributed to pollution reduction and sustainable development. Therefore, this research aims to explore the CPEED problem in the context of renewable energy generation systems to enhance the energy and climate benefits of the power systems. Five benchmark test systems, combined with conventional thermal power plants and renewable energy sources such as wind and solar, are considered herein to obtain the optimum solution for cost and pollutant emission by using the ABWO approach. The ascendancy is not limited to environmental impacts, but it also provides the diversification of energy supply and reduction of reliance on imported fuels. As a result, the research findings contribute in lowering the cost of fuel and pollutant emissions, correlated with electricity generation systems, while increasing the renewable energy usage and penetration. Finally, the performance and efficacy of the designed scheme have been fully validated by comprehensive experimental results and statistical analyses.

An Electronic Double Auction of Prepaid Electricity Trading Using Blockchain Technology

Thailand’s current energy trading system is an Enhanced Single Buyer (ESB), a market monopoly by a single buyer. It will produce and distribute electricity to service providers in each area, enabling them to distribute services to consumers. In terms of the consumer aspect, it is necessary to purchase electricity from only one seller, and it is not possible to choose the manufacturer independently. Since the price mechanism is not competitive, the market price is mainly determined by a single buyer. Meanwhile, alternative energy power generation technology has progressed. Anyone can become a power producer using wind power or solar energy. People can easily produce electricity to use in their households. Besides, residual energy from use will be sold only to the ESB. However, there is a selling restriction because there is only one buyer. Importantly, Blockchain technology can be applied to enable independent electricity trading. In other words, called peer-to-peer (P2P) trading, the Thai government has policies to promote P2P trading. However, there are not many systems supporting P2P energy trading since P2P trading is still in the beginning stages of the Pilot Project. In this study, the researchers have presented a P2P Power Trading Model using Blockchain technology. This research presents a system with efficiency and simplicity. Also, there are other technology highlights such as IoT, Lora, and Electronic Double Auction. The researcher has designed, implemented, and tested it for actual electrical power trading. It can prove to be traded according to the designed test cases. Importantly, we are truly confident that this research will benefit those interested in developing real-world applications. This research can also be used as an alternative to the traditional power purchase and sale system.