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In order to solve the problem of the large-scale integration of new energy into power grid output fluctuations, this paper proposes a new energy microgrid optimization scheduling algorithm based on a two-stage robust optimization and improved grey correlation theory. This article simulates the fluctuation of the outputs of wind turbines and distributed photovoltaic power plants by changing their robustness indicators, generates economic operating cost data for microgrids in multiple scenarios, and uses an improved grey correlation theory algorithm to analyze the correlation between new energy and various scheduling costs. Subsequently, a weighted analysis is performed on each correlation degree to obtain the correlation degree between new energy and total scheduling operating costs. The experimental results show that the improved grey correlation theory optimization scheduling algorithm for new energy microgrids proposed obtains weighted correlation degrees of 0.730 and 0.798 for photovoltaic power stations and wind turbines, respectively, which are 3.1% and 4.6% higher than traditional grey correlation theory. In addition, the equipment maintenance costs of this method are 0.413 and 0.527, respectively, which are 25.1% and 5.4% lower compared to the traditional method, respectively, indicating that the method effectively improves the accuracy of quantitative analysis. [ABSTRACT FROM AUTHOR]

Dynamic harmonic estimation is important for the monitoring and control of power-electronic grids. But the high-precision dynamic harmonic estimation algorithms usually have a heavy computational burden and occupy a large memory space, making them difficult to implement in the embedded platform. Thus, the motivation of this paper lies in providing an estimator with low computational complexity and less storage space consumption. A purely real-valued fast dynamic harmonics estimator is proposed. Firstly, a purely real-valued estimation model is established based on the Taylor series expansion on the time-varying amplitude and phase angle. Secondly, the estimation filter bank is computed in the least-squares sense, and the corresponding estimation error is theoretically analyzed. Finally, the purely real-valued fast dynamic harmonics estimator is designed. The advantage includes significantly reducing the computational complexity and memory space consumption while maintaining high-precision estimation. The testing results show that the proposed estimator can achieve the highest harmonics estimation precision under dynamic conditions. The frequency error, magnitude error, and phase angle error are less than 5 × 10−2 Hz, 7 × 10−1%, and 8 × 10−2 degrees, respectively, which verifies the advantage of high-precision estimation. The proposed estimator achieves a computational speed-up of approximately 430, 396, and 330 times compared to the Prony method, ESPRIT method, and iterative Taylor Fourier transform method, respectively. The computational load rate for executing the proposed estimator on the embedded prototype using C6748 DSP for estimating 50 harmonics is approximately only 2.05%, which verifies the advantage of a low computational load rate. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the midst of the push for dual-carbon goals, urban centers are faced with the imperative of reducing emissions and conserving energy, while rural regions are harnessing their abundant new energy resources to promote balanced urban–rural development. Photovoltaic (PV) power generation, known for its cleanliness, safety, and emission-free nature, is playing a crucial role in the evolution of Henan Province's power supply industry. This paper delves into the current state of Henan's power supply infrastructure, the trajectory of its low-carbon development, and the policies that shape the PV sector. It also examines the establishment of an urban–rural mutual aid model through the lens of alternative energy technologies. By utilizing a combination of case studies and systematic theoretical research, this paper uncovers the economic potential that remains untapped of new energy sources in rural areas and presents strategies for synergistic development in alignment with dual-carbon goals within the power supply industry. The research underscores the significance of an urban–rural mutual assistance model in achieving carbon neutrality, addressing urban–rural development gaps, fostering shared prosperity, and contributing Chinese insights to global climate governance frameworks. [ABSTRACT FROM AUTHOR]

With the increasing proportion of new energy in power systems, the instability issues of novel power systems become more prominent. This paper addresses the transient overvoltage problem in wind power DC transmission systems by proposing a method for transient overvoltage suppression based on doubly-fed wind turbines, high-voltage DC transmission systems, and SVC control parameter optimization. The electromagnetic transient model of the wind power DC transmission system is combined with intelligent optimization algorithms through joint invocation to achieve coordinated optimization of control parameters. Case studies validate the effectiveness of the proposed model and method. The results indicate that the improved genetic algorithm, SEGA, proposed in this paper, effectively suppresses overvoltage at the grid connection point of wind turbines. Furthermore, by simultaneously applying coordinated control strategies based on DFIG and SVC and optimizing parameters of HVDC, DFIG, and SVC, transient overvoltage phenomena can be effectively eliminated. [ABSTRACT FROM AUTHOR]

This paper delves into the critical issues of relay protection setting calculation in high-voltage power grids with large-scale integration of renewable energy sources, such as wind and solar power. By analyzing the topological structure of renewable energy systems, models of permanent magnet direct-drive wind turbines and photovoltaic power sources are established, with a particular focus on the short-circuit current characteristics of these renewable energy sources. Subsequently, a fault iterative method for short-circuit current calculation is proposed. This method effectively improves the accuracy of short-circuit current calculation by iteratively analyzing the fault region and considering the voltage-controlled current source characteristics of renewable energy sources. The paper also conducts in-depth research on various aspects of relay protection settings after the integration of renewable energy devices, including main transformer neutral grounding strategies, tie-line protection and reclosing principles, islanding prevention, and boundary backup protection management. By applying this method to a practical engineering case in G Province, China, the short-circuit current is calculated, and partial setting values are determined, demonstrating the ability of this method to enhance system safety and stability. This research provides valuable insights for operators of modern power systems. [ABSTRACT FROM AUTHOR]

Under the construction of the country's modern energy system structure, the generating capacity of wind and photovoltaic is growing rapidly across the country. Wind, light, and other renewable energy generation methods are characterized by randomness and volatility, and when a large number of them are connected to the power grid, it poses a huge challenge to the stable operation of the power system as well as grid power smoothing. Accurate prediction of new energy power generation can not only improve the grid's ability to reduce the grid's scheduling burden, but also reduce the economic costs to a certain extent. Therefore, the research of new energy generation forecasting technology is particularly important. A review was conducted of the classification of several prediction methods that had been established in recent years, alongside the newly proposed methods for new energy generation prediction. The analysis delved into the differences in the application principles of the models and the limitations encountered in their practical applications. Furthermore, the review summarized the advantages and disadvantages of the various methods, identifying areas where improvements could be made. Lastly, the current challenges faced by renewable energy generation forecasting were analyzed, and potential directions for future solutions were proposed, offering valuable reference and guidance to researchers in renewable energy generation forecasting technologies. [ABSTRACT FROM AUTHOR]

Green agriculture needs energy saving and emission reduction agricultural machinery, and it is feasible to replace fossil energy with new energy based on electricity to become the power source of agricultural machinery. Agricultural machinery is a kind of non-road mobile machinery working in farmland, which is a complex and changeable unstructured scene, including paddy field, hilly farmland and facility farmland. Agricultural machinery for the operation of the object that is the crop is also a lot, the operation of the link also contains a plowing and planting management and harvesting and other operational aspects, which makes the agricultural machinery operation load changes, to the design of electric agricultural machinery has brought many technical difficulties, coupled with the rural areas of the maintenance capacity of the poor, small farmers poor affordability and other socio-economic factors, resulting in the popularization of the application of electric agricultural machinery there are many problems that need to be solved. The characteristics of new energy agricultural machinery using pure electric, hybrid, solar auxiliary power and fuel cell power were reviewed. Domestic and foreign largescale agricultural machinery manufacturers have begun to actively layout the field of new energy agricultural equipment, but mainly concentrated in the concept machine stage. Endurance is a key factor restricting the development of electric agricultural equipment. The battery life of pure electric agricultural machinery products mainly relies on the increase of battery energy density, and hybrid agricultural machinery products increase the battery life through fuel, solar energy or clean fuel. Electric agricultural equipment products are currently mainly concentrated in the concept machine stage, the real mass production of products is less, in addition to consumer product cognition issues, economy is the main determining factor. Compared with foreign countries, China's electric vehicles and new energy industry chain is complete, the rapid development of electric construction machinery, to provide favorable conditions for the electrification of agricultural equipment, should make full use of advantages, accelerate the development and promotion of electric agricultural equipment. This paper starts with the operation characteristics of agricultural machinery, analyzes the key technical requirements of electric agricultural machinery on battery components, electric drive components, electric drive control, energy management and collaborative control, discusses the technical methods to increase the battery life of electric agricultural machinery, adapt to low speed and high torque and multipower output conditions, and summarizes the relevant technical research progress. It is suggested that the battery life of agricultural machinery can be increased by increasing the battery energy density, increasing the battery charging efficiency and increasing the auxiliary power supply. In terms of electric drive, agricultural machinery operations require low-speed motors with large torque, and the different speed requirements of transfer fields and operations require electric drive systems with large speed ranges. In terms of control, the whole machine energy algorithm and coordinated control of agricultural machinery is the focus of research, compared with electric vehicles, electric agricultural machinery in addition to providing power to the driving parts, but also need to achieve the power output of each working part, so the multi-power output power dynamic regulation algorithm is one of the focuses of research. The application of electric agricultural machinery in facility planting, hilly and mountainous areas and leisure agriculture was forecast. In view of the existing problems, it is pointed out that in the future, research should be carried out in the aspects of high-pass special chassis, high-adaptation three-power system, electrification transformation of operating parts, intelligent electrification technology integration, etc., to improve the comprehensive performance of electric agricultural machinery, reduce the cost of electric agricultural machinery through agricultural machinery subsidies, agricultural machinery multi-functional, “battery bank” construction and other methods, and improve the promotion speed of electric agricultural machinery. [ABSTRACT FROM AUTHOR]

Copyright of Urban Geology is the property of Urban Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ObjectivesMagnetic confinement fusion is regarded as a critical solution to future global energy challenges. As the central component of magnetic confinement fusion devices, magnets play a crucial role in generating and sustaining plasma stability. A review of the magnetic system structures and specifications in representative magnetic confinement fusion devices worldwide was provided.MethodsThe technological evolution of fusion magnets was reviewed, from copper-based to low-temperature superconducting, and finally to high-temperature superconducting magnets. The structure and performance parameters of magnetic systems in various typical fusion devices were summarized systematically. Additionally, the technical challenges in magnet development were explored and an outlook on future development trend was offered.ConclusionsAdvances in magnet technology are vital for enhancing the performance of fusion devices and accelerating the commercialization of fusion energy. With the increasing application of high-temperature superconducting materials and continuous optimization of magnet designs, the practical realization of fusion energy is becoming increasingly feasible.

In the context of sustainable energy development to reduce carbon emissions, the application of new energy sources and smart grid technologies in power systems is becoming more widespread. However, current research results on power system technology strategies for carbon emission reduction are not satisfactory. To address this problem, a model for optimal power system operation and scheduling based on the prediction error mechanism and synthetic fuel technology is proposed. The model used the carbon trading mechanism to further reduce carbon emissions and the carnivorous plant algorithm to optimize the scheduling strategy. The results indicate that the model demonstrates significant advantages in terms of carbon emission, total operating cost, prediction accuracy, and energy utilization efficiency, respectively, at 60.8 kg, 2517.5 yuan, 96.5%, and 90.2%, indicating that it utilizes energy more fully and helps to enhance the overall energy efficiency of the system. The calculation time of the optimized power system was only 12.5 s, the stability was as high as 98.7%, and the satisfaction rate was 95.6% in terms of user satisfaction. Compared to other contemporary designs, the proposed model can successfully reduce the system's carbon emissions while increasing energy efficiency. The model has positive implications for smart grid and sustainable development.

Abstract Aiming at the problem of high volatility and intermittency of new energy-containing power systems, which affects the prediction accuracy of carbon emissions, we study the adaptive prediction method of carbon emissions of a new energy-containing power system based on a least-squares support vector machine. The carbon emission coefficients of the nodes of the new energy-containing power system are determined based on the trend analysis method. Historical carbon emissions and carbon emission coefficients of the power system are collected, and the rough set method is used to simplify the carbon emission attributes and obtain a simplified attribute set for carbon emission prediction. The least-squares support vector mechanism is used to construct the carbon emission prediction model, and the simplified attribute set is used as the input of the carbon emission prediction model. The whale optimization algorithm was selected to determine the optimal parameters of the least-squares support vector machine through the process of encircling prey, hunting behavior, searching for predation, and adaptively optimizing the least-squares support vector machine to output carbon emission prediction results. The experimental results show that the method can accurately predict the carbon emissions of the power system, and the mean square error of the carbon emissions prediction is lower than 7.

ObjectivesTraditional electric energy storage has limitations in scale, duration, and environmental impact.Moreover, the renewable energy absorption capacity in the microgrid is low, and low-carbon and economy cannot be taken into account in planning. In order to solve the above problems, based on the basic working principle of hydrogen energy storage, hydrogen energy storage was incorporated into the microgrid instead of traditional electric energy storage, and a low-carbon and economic synergy bi-level optimization configuration model of microgrid with hydrogen energy storage was established.MethodsThe upper-level planning model aimed at minimizing the comprehensive equivalent annual value of the microgrid, based on the joint operation of electricity and hydrogen. The carbon trading mechanism was introduced to plan the capacity of various power generation equipments in the microgrid, which can enhance the low-carbon of the system. The lower-level operation model aimed to minimize the sum of the absolute values of the difference between the new energy output and the load demand. The model also encouraged users to adopt diversified demand-side response behaviors with the goal of accurately tracking the new energy output curve, and feeded back the user’s energy consumption behavior to the upper-level model to optimize the load curve. On the basis of improving the absorption capacity of new energy, the system economy is further improved, deeply exploring the synergy between the low-carbon and economic characteristics of microgrids.ResultsThe simulation results of microgrid in a certain industrial park show that the proposed method yields a planning scheme with excellent low-carbon and economy. Compared with the traditional planning method, the low-carbon and economy are improved by 53.6% and 37.1%, respectively.ConclusionsThe model presented in this paper not only enhances the capacity for new energy absorption but also further improves the system economic performance. It achieves a synergistic enhancement of the microgrid low-carbon and economy.

Rural energy plays an important role in realizing the goals of “carbon peak” and “carbon neutrality” in China. In this paper, the countryside was regarded as the research object, and the rural energy internet was constructed to study the impact of rural energy development on rural carbon emissions. The most advanced energy and informative technologies in the development of rural energy were introduced from three perspectives, including rural living, rural planting and rural breeding. The benefits of rural energy internet in practical application, including energy and carbon benefits, were presented through three application cases. In general, a low-carbon, digital and intelligent rural energy will be developed, and the goals of “carbon peak” and “carbon neutrality” will be achieved by constructing and applying of rural energy internet in China.

Introduction: With the rapid development of human society and economy, the power generation technology of various new energy vehicles has begun to receive widespread attention. Methods: Due to the lack of inertia and frequency stability in the new energy vehicle power generation system, this paper proposes a power generation control method that combines linear active disturbance rejection control technology and virtual synchronous generator technology. This method first introduces the control strategy and inertial response of the virtual synchronous generator. Then, it uses linear active disturbance rejection control technology to improve the virtual synchronous generator technology to deal with the uncertainty and external interference in the system. Results: The results showed that when the virtual inertia coefficient was 0, and the new energy vehicles would hardly intervene in the regulation of the grid voltage. When the virtual inertia coefficient was 5, the decline rate of the DC bus voltage of new energy vehicles had slowed down. When the virtual inertia coefficient increased, the power output of new energy vehicles can be increased to the grid. When the load suddenly increased, and the corresponding DC bus voltage decreased more slowly. In the VSG output power comparison, under the research method, the frequency fluctuation only increased by 0.09 Hz and returned to the rated frequency of 50 Hz. Additionally, the dynamic process of the system output power was the shortest, lasting only 0.05 s. Discussion: The above results show that the research method has significant superiority and effectiveness in improving the inertial response and overall stability of the new energy vehicle power system. [ABSTRACT FROM AUTHOR]

In the context of sustainable energy development to reduce carbon emissions, the application of new energy sources and smart grid technologies in power systems is becoming more widespread. However, current research results on power system technology strategies for carbon emission reduction are not satisfactory. To address this problem, a model for optimal power system operation and scheduling based on the prediction error mechanism and synthetic fuel technology is proposed. The model used the carbon trading mechanism to further reduce carbon emissions and the carnivorous plant algorithm to optimize the scheduling strategy. The results indicate that the model demonstrates significant advantages in terms of carbon emission, total operating cost, prediction accuracy, and energy utilization efficiency, respectively, at 60.8 kg, 2517.5 yuan, 96.5%, and 90.2%, indicating that it utilizes energy more fully and helps to enhance the overall energy efficiency of the system. The calculation time of the optimized power system was only 12.5 s, the stability was as high as 98.7%, and the satisfaction rate was 95.6% in terms of user satisfaction. Compared to other contemporary designs, the proposed model can successfully reduce the system's carbon emissions while increasing energy efficiency. The model has positive implications for smart grid and sustainable development. [ABSTRACT FROM AUTHOR]

Copyright of Precious Metals / Guijinshu is the property of Precious Metals Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Smart Rail Transit is the property of Smart Rail Transit Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem of high volatility and intermittency of new energy-containing power systems, which affects the prediction accuracy of carbon emissions, we study the adaptive prediction method of carbon emissions of a new energy-containing power system based on a least-squares support vector machine. The carbon emission coefficients of the nodes of the new energy-containing power system are determined based on the trend analysis method. Historical carbon emissions and carbon emission coefficients of the power system are collected, and the rough set method is used to simplify the carbon emission attributes and obtain a simplified attribute set for carbon emission prediction. The least-squares support vector mechanism is used to construct the carbon emission prediction model, and the simplified attribute set is used as the input of the carbon emission prediction model. The whale optimization algorithm was selected to determine the optimal parameters of the least-squares support vector machine through the process of encircling prey, hunting behavior, searching for predation, and adaptively optimizing the least-squares support vector machine to output carbon emission prediction results. The experimental results show that the method can accurately predict the carbon emissions of the power system, and the mean square error of the carbon emissions prediction is lower than 7. [ABSTRACT FROM AUTHOR]

Coastal cities have the natural resource endowment and location advantages to develop new energy. However, heterogeneity in the economic development of China's coastal cities has led to differences in the outcomes of environmental regulatory policies and related programs. To elucidate the difference, this paper obtained 5074 clean development mechanism (CDM) projects, which serves as a key instrument of the Kyoto Protocol designed to assist developing countries in achieving sustainable development through project-based emissions reductions and conducted a causal identification through quasi-experiment. And DID as well as DDD models are applied to identify the CDM effects on cities' economic development. Main findings are: (1) Through the DID regression, this paper finds that the development of CDM projects have promoted the development of the city's economy and lead to the upgrading of cities' industries. (2) The promoting effects in economic development and employment are more prominent in coastal cities with high levels of economic development. (3) CDM can better facilitate economic development and employment in less developed coastal areas when implemented in conjunction with economic promoting policies. By applying quasi-experimental methods, including DID and DDD models, the research introduces a novel approach to assess the causal effects of CDM projects on city economies, offering fresh insights into sustainable development policies. [ABSTRACT FROM AUTHOR]

To determine the ES allocation based on a specific number of EVs connected to a combined WPESS, this paper develops an ESS allocation model that considers the impact of EV charging behavior on LSD, ES allocation cost, new energy utilization rate, and self-power rate. First, several scenarios are generated using Monte Carlo sampling (MCS), and a typical day is selected through Backward Reduction (BR). Next, the Monte Carlo method is employed to generate conventional EV charging curves and optimize EV charging behavior by considering LSD and user charging costs. Subsequently, an ES capacity allocation model is developed, considering system costs, new energy utilization rate, and self-power rate. Finally, an improved triangulation topology aggregation optimizer (TTAO) is proposed, incorporating the logistic map, Golden Sine Algorithm (Gold-SA) strategy, and lens inverse imaging learning strategy. These enhancements improve the algorithm's ability to identify global optimal solutions and facilitate its escape from local optima, significantly enhancing the optimization effectiveness of TTAO. The analysis of the calculation example indicates that after optimizing the charging behavior of EVs, the average daily cost is reduced by 204.94, the self-power rate increases by 2.25%, and the utilization rate of new energy sources rises by 2.50%, all while maintaining the same ES capacity. [ABSTRACT FROM AUTHOR]

As an important production factor, energy's spatial layout is bound to have an impact on regional carbon emissions. In the context of China's goals of reaching peak carbon emissions and carbon neutrality, the contradiction between the reverse distribution of energy production centers and consumption centers in China has become increasingly prominent. Therefore, it is necessary to explore the impact of spatial agglomeration of energy production capacity on regional carbon emissions. Based on provincial panel data from China from 2000 to 2022, this study used fixed effects and mediation effects models to explore the impact and pathways of energy production capacity spatial agglomeration on regional carbon emissions. A series of robustness tests were conducted, and the moderating effects of environmental regulation and new energy development level on the carbon emissions of energy production capacity spatial agglomeration were tested using an interaction effect model. The results showed that: ① The spatial agglomeration of energy production capacity was not conducive to carbon emission reduction in both the national and subregional studies, with the low agglomeration area having the largest effect, followed by the agglomeration conversion area, and the high agglomeration area having the least effect. ② Energy efficiency, industrial structure, and energy structure were the three pathways ways that the spatial agglomeration of energy production capacity affected regional carbon emissions. ③ Environmental regulation had a significant regional heterogeneity in regulating the carbon enhancement of energy production capacity spatial agglomeration, with an inhibitory effect on the carbon enhancement of energy production capacity spatial agglomeration in the whole country and in the high agglomeration area, while it had a promoting effect in the agglomeration conversion area and the low agglomeration area. ④ At the national and regional levels, increasing the level of development of new energy helped to reduce or even eliminate the carbon enhancement of the spatial agglomeration of energy production capacity. According to the above research conclusions, to ensure the high-quality development of the energy industry and promote the 'dual carbon' goals, it is recommended that: first, an energy Internet with 'electricity as the core' should be built, and the spatial layout of fossil energy optimized. Second, the endowment structure should be relied on, and the energy structure and industrial structure reasonably optimized. Third, regional heterogeneity should be fully considered, and environmental regulation enhanced in a reasonable and orderly manner. Fourth, research and development of new energy technologies should be accelerated, and the regional installed scale of new energy increased. [ABSTRACT FROM AUTHOR]

In a new energy power system, there is a lack of sufficient inertia support when facing sudden frequency disturbances, which threatens frequency stability. To address the problem of how to control the frequency of a high-proportion new energy power system under low inertia, this paper proposes an emergency frequency control method based on the idea of control and cutting coordination to reduce the frequency deviation of the power system. With the minimization of the power system frequency offset and the minimization of the control cost as the objective function and the minimum inertia and power balance of the power system as the constraint conditions, an emergency frequency optimization control model of a high-proportion new energy power system under low inertia is established. Solving the model obtains the minimum frequency offset and the minimum control cost, and the optimal cutting and load reduction strategy is effectively determined to achieve stable control of the power system frequency. Results show that under different power shortage conditions, this method can effectively determine the inertia of the power system, thereby completing the control of the emergency frequency of the power system. Through the control of this method, the maximum frequency deviation of the power system is maintained at about 0.6 Hz, and the maximum total control cost is 16,600 CNY. Compared with the situation before the application of this method, the frequency deviation and control cost of the power system are significantly reduced, that is, the emergency frequency control effect of this method is better. The research conclusions are of great technical help in maintaining the safe and stable operation of the power system. [ABSTRACT FROM AUTHOR]

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A large-scale integration of photovoltaic (PV) systems can degrade the stability of the power grid. Therefore, it is important to accurately predict the short-term output power generated from PV systems to achieve better grid power distribution and allocation. For this reason, a short-term PV power prediction model that uses the data collected from temperature sensors, irradiance sensors, and other relevant sensors was proposed, in which an improved dragonfly algorithm (IDA) was applied to optimize the support vector machine (SVM). First, the output power curves of PV systems under sunny, cloudy, and rainy conditions were analyzed to determine the input variables of the prediction model, which included temperature, relative humidity, and solar radiation intensity. Second, the original dragonfly algorithm in the optimization process was improved, and then, this IDA was utilized to optimize the parameters of SVM, enhancing the predictive capability of the model. Finally, the IDA-optimized SVM (IDA-SVM) model was applied to predict the PV output power. Test performance results demonstrated that the average absolute percentage errors of IDA-SVM were 2.42, 5.96, and 7.44% for sunny, cloudy, and rainy days, respectively, outperforming other comparative models. The performance results showed that the proposed model can not only improve the stability of PV integration, but also effectively increase the penetration rate of PV energy and enhance the reliability of power system operation. [ABSTRACT FROM AUTHOR]

PetroChina Southwest Oil & Gasfield Company is making every effort to promote the construction of national natural gas (shale gas) production base with a capacity of billions of cubic meters, facing the dual challenges of green and low-carbon transformation and achieving dual carbon goals, it urgently needs to promote the deep integration of natural gas and new energy development. To this end, the resource foundation of integrated development is analyzed, the ideas and exploration process of past integrated development are summarized, and the three challenges currently faced are clarified: poor internal resource endowment and difficulty in obtaining external resources; new technologies and equipment are not mature enough, and there is a deviation in economic benefits; lack of systematic understanding and insufficient utilization of new business resources. On this basis, a path idea for the deep integration of natural gas and new energy is proposed: to develop wind, solar and geothermal businesses in an orderly manner within the region and focus on outside the region; vigorously develop characteristic businesses such as residual pressure power generation, associated resources, CCUS, hydrogen energy; explore the development of new track businesses such as underground space utilization and biogas. Finally, four suggestions are proposed: based on the current situation, focusing on the future, take into account overall economic considerations; considering the growth potential of the business and the need for technological iteration, orderly promote the industrial scale from small to large; cultivate market competitiveness awareness, deepen cooperation and communication, and jointly promote industrial development; innovate mechanisms and explore various mechanisms and models to support industrial development. [ABSTRACT FROM AUTHOR]

During China's industrial transformation, studying risk spillover effects and clarifying risk contagion pathways within the new energy industry chain is critical for promoting high-quality development in the new energy. The risk transmission mechanism of the new energy industry chain is explored by constructing a time–frequency index using a time-varying parameter vector autoregressive model in this paper. Additionally, we also further analyze the portfolio and hedging effectiveness of the new energy market. The findings reveal that, first, the downstream market serves as the primary risk source, propagating risk through the industry chain to the midstream and upstream sectors within the new energy industry chain contagion system. Second, the risk spillover effect of the new energy market has significant heterogeneity and time-varying due to the impact of short-term frequency domain drivers and extreme events. Third, the portfolio significantly reduces the investment risk of a single asset. With the extension of the investment horizon, investors' portfolio weights in the upstream, midstream and downstream industries gradually tend to be even. [ABSTRACT FROM AUTHOR]

Copyright of Natural Gas & Oil is the property of Editorial Department of Natural Gas & Oil and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper analyzes the economic, social and political three-dimensional driving effects of new energy substitution for fossil energy under the joint action of market, government and international competition from three perspectives: profit motive, mutual benefit and responsibility motive, combined with the relevant data of 78 countries from 1965 to 2021. The results show that fossil energy prices and energy security positively influence the process of new energy substitution, and environmental pollution negatively affects the process of new energy substitution, and the pushback effect of energy security on new energy substitution is more significant in the study interval, indicating that at the beginning of the new energy revolution, global environmental governance and willingness to reduce emissions drive the development of new energy industry, but the "carbon emission reduction" of each country has increased the complexity of new energy substitution, especially in some developed countries in taking responsibility for global environmental governance divergent views. Further heterogeneity analysis reveals that each country's energy strategy affects the degree of substitution of "quality" and "quantity" of new energy, and the speed, areas and corrective ability of new energy development vary among countries under different strategic choices. [ABSTRACT FROM AUTHOR]

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With the increasing proportion of new energy in power systems, the instability issues of novel power systems become more prominent. This paper addresses the transient overvoltage problem in wind power DC transmission systems by proposing a method for transient overvoltage suppression based on doubly-fed wind turbines, high-voltage DC transmission systems, and SVC control parameter optimization. The electromagnetic transient model of the wind power DC transmission system is combined with intelligent optimization algorithms through joint invocation to achieve coordinated optimization of control parameters. Case studies validate the effectiveness of the proposed model and method. The results indicate that the improved genetic algorithm, SEGA, proposed in this paper, effectively suppresses overvoltage at the grid connection point of wind turbines. Furthermore, by simultaneously applying coordinated control strategies based on DFIG and SVC and optimizing parameters of HVDC, DFIG, and SVC, transient overvoltage phenomena can be effectively eliminated.

Promoting the application of new energy technologies in marine ports is an important way to realize the carbon peaking and carbon neutrality goals and achieve the sustainable development of ports in China. This study summarizes the current situation and trends of energy consumption in marine ports of China and analyzes the basic attributes of the application of new energy technologies in marine ports from three dimensions: economical efficiency, demand, and maturity; it involves ffshore wind power, photovoltaic power generation, hydrogen energy, tidal energy, and biomass energy. Factors that constrain the application of new energy technologies in China’s marine ports are further discussed from three aspects: technology, economical efficiency, and technological policy. Our research indicates that the mismatch between the development level and application needs of new energy technologies, lack of centralized technology-developmentplatforms, inadequate profit models, and imperfect standards and policies collectively constrain the application of new energy sources in marine ports of China. Therefore, we propose the following suggestions: (1) establishing a collaborative research and development system for key core technologies to overcome technical difficulties and reduce application costs, (2) issuing guidance on multi-energy integration networks for ports to establish a multi-energy-complementary energy supply system, (3) optimizing the incentive mechanism for the application of new energy technologies in ports to enhance the enthusiasm of ports to apply new energy sources, and (3) improving the standards and norms for renewable energy application in ports to build a novel energy-storage supporting mechanism.

The integrated development of coal and new energy sources is crucial for the smooth transition of China’s energy system and the security and stable supply of energy. Considering China’s resource endowment and its demand for energy supply security and transformation, this study elaborates on the significance and fundamental conditions regarding the integrated development of coal and new energy sources. Moreover, it summarizes the major forms, technical characteristics, and application status of the integrated development from the aspects of four scenarios: integration of coal mining, coal-fired power generation, coal chemical industry, and carbon capture, utilization and storage (CCUS) with new energy sources. Emphasis is placed on five types of technologies: integration of coal development with new energy sources; combined dispatching of wind, solar, thermal, and storage; integration of solar thermal and coal-fired power generation; integration of solar thermal power generation with CCUS; and integration of green hydrogen with the coal chemical industry. Furthermore, this study explores the key technological challenges and breakthrough directions, and proposes the following suggestions: (1) incorporating the integrated development of coal and new energy sources into national strategies; (2) formulating action goals and roadmaps to systematically support the integrated development; (3) strengthening the research and development of technologies regarding coal and new energy sources; and (4) improving fiscal, financial, and talent support policies related to the integrated development.