Abstract China has abundant renewable energy resources.With the establishment of carbon peaking and carbon neutrality goals, renewable energy sources such as wind power and photovoltaics have undergone tremendous development.However, because of the randomness and volatility of wind and photovoltaic power, the large-scale development of renewable energy faces challenges with accommodation and transmission.At present,the bundling of wind-photovoltaic-thermal power with ultra-high voltage transmission projects is the main development approach for renewable energy bases in western and northern China.Nonetheless, solving the problems of high carbon dioxide emission, carbon dioxide capture, and the utilization of thermal power is still necessary.Based on power-to-hydrogen, powerto-methanol, and oxygen-enriched combustion power generation technologies, this article proposes a power-to-hydrogen-andmethanol model based on the collaborative optimization of energy flow and material flow, which is expected to simultaneously solve the problems of renewable energy accommodation and low-carbon transformation of thermal power.Models with different ways of linking power to hydrogen and methanol are established, and an 8760-hour-time-series operation simulation is incorporated into the planning model.A case study is then conducted on renewable energy bases in the deserts of western and northern China.The results show that the power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow can greatly reduce the demand for hydrogen storage and energy storage,reduce the cost of carbon capture,make full use of by-product oxygen and captured carbon dioxide, and produce high-value chemical raw materials, thus exhibiting significant economic advantages.

more

Abstract Integrating the photovoltaic/thermal(PV/T)system in green hydrogen production is an improvement in sustainable energy technologies.In PV/T systems, solar energy is converted into electricity and thermal energy simultaneously using hot water or air together with electricity.This dual use saves a significant amount of energy and officially fights greenhouse gases.Different cooling techniques have been proposed in the literature for improving the overall performance of the PV/T systems;employing different types of agents including nanofluids and phase change materials.Hydrogen is the lightest and most abundant element in the universe and has later turned into a flexible energy carrier for transportation and other industrial applications.Issues, including the processes of Hydrogen manufacturing,preservation as well as some risks act as barriers.This paper provides an analysis of several recent publications on the efficiency of using PV/T technology in the process of green hydrogen production and indicates the potential for its increased efficiency as compared to conventional systems that rely on fossil fuels.Due to the effective integration of solar energy,the PV/T system can play an important role in the reduction of the levelized cost of hydrogen (LCOH) and hence play an important part in reducing the economic calculations of the decarbonized energy system.

more

Abstract In this study,ten wind turbines and fourteen solar photovoltaic(SPV)modules were employed to compare the potential of hydrogen production from wind and solar energy resources in the six geopolitical zones of Nigeria.The amount of hydrogen produced was considered as a technical parameter,cost of hydrogen production was considered as an economic index, and the amount of carbon(IV)oxide saved from the use of diesel fuel was considered as an environmental index.The results reveal that ENERCON E-40 turbine yields the highest capacity factor in Lagos,Jos,Sokoto,Bauchi and Enugu sites while FUHRLAENDER,GMBH yields the highest capacity factor in Delta.The mean annual hydrogen production from wind ranged from 2.05 tons/annum at site S6(Delta)to 17.33 tons/annum at site S3(Sokoto),and the mean annual hydrogen production from SPV ranged from 64.33 tons/annum at sites S1(Lagos)to 140.28 tons/annum at site S6(Delta).The cost of hydrogen production from wind was 6.3679 and 25.9007$/kg for sites S3 and S6,respectively,and the cost of hydrogen production from SPV was 5.6659 and 6.1206$/kg for sites S3 and S1, respectively.The amount of CO2 saved annually from wind-based hydrogen generation was 137,267 kg/year in site S6 and 504,180 kg/year in site S3,and was used to produce electricity via fuel cells.The amount of CO2 saved using hydrogen produced from SPV was 615,400 kg/year and 1,341,899 kg/year in sites S1 and S6,respectively.The results also revealed that 75.55%,88.93%,80.28%,80.54%,85.65%,98.53%more hydrogen could be produced from SPV for sites S1-S6,respectively,compared to the wind resources.This study serves as a source of reliable technical information to relevant government agencies,policy makers and investors in making informed decisions on optimal investment in the hydrogen economy of Nigeria.

more

Abstract Optimizing photovoltaic (PV) power utilization in battery systems is challenging due to solar intermittency, battery efficiency, and lifespan management.This paper proposes a novel forecast-based battery charging management (BCM) strategy to enhance PV power utilization.A string of Li-ion battery cells with diverse capacities and states of charge (SOC) is contemplated in this constant current/-constant voltage(CC/CV)battery-charging scheme.Significant amounts of PV power are often wasted because the CC/CV mode cannot fully exploit the available power to maintain appropriate charging rates.To address this issue, the proposed BCM algorithm selects an optimal set of battery cells for charging at any given time based on forecasted PV power generation, ensuring maximum power is obtained from the PV system.Additionally,a support vector regression(SVR)-based forecasting model is developed to predict PV power generation precisely.The results indicate that the anticipated BCM strategy achieves an overall utilization rate of 87.47% of the PVgenerated power for battery charging under various weather conditions.

more

Abstract Submodule capacitor aging poses significant challenges to the safe operation of modular multilevel converter (MMC) systems.Traditional detection methods rely predominantly on offline tests, lacking real-time evaluation capabilities.Moreover, existing online approaches require additional sampling channels, thereby increasing system complexity and costs.To address these issues, this paper proposes an online evaluation method for submodule capacitor aging based on CapAgingNet.Initially, an MMC system simulation platform is developed to examine the effects of submodule capacitor aging on system operational characteristics and to create a dataset of submodule capacitor switching states.Subsequently, the CapAgingNet model is introduced, incorporating key technical modules to enhance performance: the Deep Stem module, which extracts larger receptive fields through multiple convolution layers and mitigates the impact of data sparsity in capacitor aging on feature extraction; the efficient channel attention (ECA) module, utilizing onedimensional convolution for dynamic weighting to adjust the importance of each channel, thereby enhancing the ability of the model to process high-dimensional features in capacitor aging data;and the multiscale feature fusion(MSF)module,which integrates capacitor aging information across different scales by combining fine-grained and coarse-grained features,thus improving the capacity of the model to capture high-frequency variation characteristics.The experimental results reveal that the CapAgingNet model achieves a TOP-1 accuracy of 95.32%and a macro-averaged F1 score of 95.49% on the test set,thereby providing effective technical support for online monitoring of submodule capacitor aging.

more

Abstract The frequency regulation reserve setting of wind-PV-storage power stations is crucial.However, the existing grid codes set up the station reserve in a static manner, where the synchronous generator characteristics and frequency-step disturbance scenario are considered.Thus, the advantages of flexible regulation of renewable generations are wasted, resulting in excessive curtailment of wind and solar resources.In this study, a method for optimizing the frequency regulation reserve of wind PV storage power stations was developed.Moreover, a station frequency regulation model was constructed, considering the field dynamic response and the coupling between the station and system frequency dynamics.Furthermore, a method for the online evaluation of the station frequency regulation was proposed based on the benchmark governor fitting.This method helps in overcoming the capacity-based reserve static setting.Finally,an optimization model was developed,along with the proposal of the linearized solving algorithm.The field data from the JH4#station in China’s MX power grid was considered for validation.The proposed method achieves a 24.77%increase in the station income while ensuring the system frequency stability when compared with the grid code-based method.

more

Abstract Flexible interconnection devices(FIDs)significantly enhance the regulation and management of complex power flows in distribution networks.Voltage source converter (VSC)-based FIDs, in particular, are pivotal for increasing system reliability and operational effi-ciency.These devices are crucial in supporting the extensive incorporation of electric vehicles(EVs)and renewable energy sources(RESs)into new, load-centric environments.This study evaluates four unique FID-based configurations for distribution network interconnections,revealing their distinctive features.We developed a comprehensive evaluation framework and tool by integrating the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE), which includes five key performance indicators to assess these configurations.The study identifies the optimal application scenarios for each configuration and discusses their roles in enabling the seamless integration of EVs and RESs.The findings provide essential insights and guidelines for the design and implementation of adaptable, interconnected distribution networks that are equipped to meet the growing demands of future urban environments.

more

Abstract With the advent of the digital economy, there has been a rapid proliferation of small-scale Internet data centers (SIDCs).By leveraging their spatiotemporal load regulation potential through data workload balancing, aggregated SIDCs have emerged as promising demand response (DR) resources for future power distribution systems.This paper presents an innovative framework for assessing capacity value(CV) by aggregating SIDCs participating in DR programs (SIDC-DR).Initially, we delineate the concept of CV tailored for aggregated SIDC scenarios and establish a metric for the assessment.Considering the effects of the data load dynamics, equipment constraints, and user behavior, we developed a sophisticated DR model for aggregated SIDCs using a data network aggregation method.Unlike existing studies,the proposed model captures the uncertainties associated with end tenant decisions to opt into an SIDC-DR program by utilizing a novel uncertainty modeling approach called Z-number formulation.This approach accounts for both the uncertainty in user participation intentions and the reliability of basic information during the DR process, enabling high-resolution profiling of the SIDC-DR potential in the CV evaluation.Simulation results from numerical studies conducted on a modified IEEE-33 node distribution system confirmed the effectiveness of the proposed approach and highlighted the potential benefits of SIDC-DR utilization in the efficient operation of future power systems.

more

Abstract Microgrids(MGs)and active distribution networks(ADNs)are important platforms for distributed energy resource(DER)consumption.The increasing penetration of DERs has motivated the development ADNs coupled with MGs.This paper proposes a distributed co-optimization method for peer-to-peer (P2P) energy trading and network operation for an ADN integrated with multiple microgrids(MMGs).A framework that optimizes P2P energy trading among MMGs and ADN operations was first established.Subsequently, an energy management model that aims to minimize the operation and energy trading costs was constructed for each MG.Accordingly,the MMGs’cooperative game model was established based on Nash bargaining theory to incentivize each stakeholder to participate in P2P energy trading,and a distributed solution method based on the alternating direction method of multipliers was developed.Moreover,an algorithm that adjusts the amount of energy trading between the ADN and MG is proposed to ensure safe operation of the distribution network.With the communication between the MG and ADN, the MMGs’ P2P trading and ADN operations are optimized in a coordinated manner.Finally, numerical simulations were conducted to verify the accuracy and effectiveness of the proposed method.

more

Abstract Accurate Electric Load Forecasting (ELF) is crucial for optimizing production capacity, improving operational efficiency, and managing energy resources effectively.Moreover, precise ELF contributes to a smaller environmental footprint by reducing the risks of disruption, downtime, and waste.However, with increasingly complex energy consumption patterns driven by renewable energy integration and changing consumer behaviors, no single approach has emerged as universally effective.In response, this research presents a hybrid modeling framework that combines the strengths of Random Forest (RF) and Autoregressive Integrated Moving Average (ARIMA) models,enhanced with advanced feature selection—Minimum Redundancy Maximum Relevancy and Maximum Synergy (MRMRMS) method—to produce a sparse model.Additionally, the residual patterns are analyzed to enhance forecast accuracy.High-resolution weather data from Weather Underground and historical energy consumption data from PJM for Duke Energy Ohio and Kentucky(DEO&K)are used in this application.This methodology,termed SP-RF-ARIMA,is evaluated against existing approaches;it demonstrates more than 40% reduction in mean absolute error and root mean square error compared to the second-best method.

more

Abstract This research aims to improve the power output of a horizontal axis wind turbine (HAWT) by using an auxiliary rotor in front of the main rotor, this configuration is called a dual-rotor wind turbine (DRWT).The three-bladed main rotor has a diameter of 0.9 m and both rotors with NREL S826 airfoil.ANSYS Fluent CFD simulation was used to optimize the DRWT performance where the numerical model was solved using the Realizable k-ε turbulence model.Four parameters are used, diameter ratio between the auxiliary front rotor and the main rear rotor (DR = 0.25, DR = 0.5, and DR = 0.75), axial free stream velocity according to the normal wind speed range in Egypt(Vo = 5 m/s, Vo = 7.5 m/s, and Vo =10 m/s),tip speed ratio which ranges from 2 to 8,and the number of blades of the front rotor(B=2,B = 3 and B = 4).The results show that increasing the number of blades positively impacts performance but at lower tip speed ratios.Smaller diameter ratios yield better performance,while increasing wind speed results in higher power.The best performance was achieved at freestream velocity Vo=10 m/s,diameter ratio DR=0.25,front rotor number of blades B=4,and tip speed ratio λ=5 in which the overall maximum power coefficient Cp max = 0.552 with an increase with 36.75 % compared to the single rotor case.

more

Abstract In this study, we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model, assuming an actual situation with several participants in energy trading.Firstly, the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly, the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally, a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds, the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%,respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59 %.

more