Achieving Synergistic Improvement in Dielectric and Energy Storage Properties of All-Organic Poly(Methyl Methacrylate)-Based Copolymers Via Establishing Charge Traps

How to achieve synergistic improvement of permittivity(ε_(r))and breakdown strength(E_(b))is a huge challenge for polymer dielectrics.Here,for the first time,theπ-conjugated comonomer(MHT)can simultaneously promote theε_(r)and E_(b)of linear poly(methyl methacrylate)(PMMA)copolymers.The PMMA-based random copolymer films(P(MMA-co-MHT)),block copolymer films(PMMA-b-PMHT),and PMMA-based blend films were prepared to investigate the effects of sequential structure,phase separation structure,and modification method on dielectric and energy storage properties of PMMA-based dielectric films.As a result,the random copolymer P(MMA-coMHT)can achieve a maximumε_(r)of 5.8 at 1 kHz owing to the enhanced orientation polarization and electron polarization.Because electron injection and charge transfer are limited by the strong electrostatic attraction ofπ-conjugated benzophenanthrene group analyzed by the density functional theory(DFT),the discharge energy density value of P(MMA-co-PMHT)containing 1 mol%MHT units with the efficiency of 80%reaches15.00 J cm^(-3)at 872 MV m^(-1),which is 165%higher than that of pure PMMA.This study provides a simple and effective way to fabricate the high performance of polymer dielectrics via copolymerization with the monomer of P-type semi-conductive polymer.

Inter-stage performance and energy characteristics analysis of electric submersible pump based on entropy production theory

The electric submersible pump(ESP) is a crucial apparatus utilized for lifting in the oil extraction process.Its lifting capacity is enhanced by the multi-stage tandem structure, but variations in energy characteristics and internal flow across stages are also introduced. In this study, the inter-stage variability of energy characteristics in ESP hydraulic systems is investigated through entropy production(EP) analysis,which incorporates numerical simulations and experimental validation. The EP theory facilitates the quantification of energy loss in each computational subdomain at all ESP stages, establishing a correlation between microscopic flow structure and energy dissipation within the system. Furthermore, the underlying causes of inter-stage variability in ESP hydraulic systems are examined, and the advantages and disadvantages of applying the EP theory in this context are evaluated. Consistent energy characteristics within the ESP, aligned with the distribution of internal flow structure, are provided by the EP theory, as demonstrated by our results. The EP theory also enables the quantitative analysis of internal flow losses and complements existing performance analysis methods to map the internal flow structure to hydraulic losses. Nonetheless, an inconsistency between the energy characterization based on EP theory and the traditional efficiency index when reflecting inter-stage differences is identified. This inconsistency arises from the exclusive focus of the EP theory on flow losses within the flow field, disregarding the quantification of external energy input to the flow field. This study provides a reference for the optimization of EP theory in rotating machinery while deeply investigating the energy dissipation characteristics of multistage hydraulic system, which has certain theoretical and practical significance.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Energy Storage Operation Modes in Typical Electricity Market and Their Implications for China

As the Chinese government proposes ambitious plans to promote low-carbon transition,energy storage will play a pivotal role in China’s future power system.However,due to the lack of a mature electricity market environment and corresponding mechanisms,current energy storage in China faces problems such as unclear operational models,insufficient cost recovery mechanisms,and a single investment entity,making it difficult to support the rapid development of the energy storage industry.In contrast,European and American countries have already embarked on certain practices in energy storage operation models.Through exploration of key issues such as investment entities,market participation forms,and cost recovery channels in both front and back markets,a wealth of mature experiences has been accumulated.Therefore,this paper first summarizes the existing practices of energy storage operation models in North America,Europe,and Australia’s electricity markets separately from front and back markets,finding that perfect market mechanisms and reasonable subsidy policies are among the main drivers for promoting the rapid development of energy storage markets.Subsequently,combined with the actual development of China’s electricity market,it explores three key issues affecting the construction of costsharing mechanisms for energy storage under market conditions:Market participation forms,investment and operation modes,and cost recovery mechanisms.Finally,in line with the development expectations of China’s future electricitymarket,suggestions are proposed fromfour aspects:Market environment construction,electricity price formation mechanism,cost sharing path,and policy subsidy mechanism,to promote the healthy and rapid development of China’s energy storage industry.

Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle performance.This study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power sources.Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces.They often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing conditions.Moreover,these algorithms suffer from low sample efficiency.Collectively,these factors contribute to convergence difficulties,low learning efficiency,and instability.To address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience samples.Additionally,the correspondingMarkovDecision Process(MDP)is established.Finally,an EMSbased on the improvedDRLmodel is presented.Comparative simulation experiments are conducted against rule-based,optimization-based,andDRL-based EMSs.The proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global information.In the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 g.Compared to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%,15.1%,and 8.37%over the Deep QNetwork(DQN),Double DRL(DDRL),and original DDPG methods,respectively.The observational outcomes demonstrate that the proposed EMS based on improved DRL framework possesses good real-time performance,stability,and reliability,effectively optimizing vehicle economy and fuel consumption.

Electricity as an Energy Vector: A Performance Comparison with Hydrogen and Biodiesel in Italy

This study presents a comparative analysis of electricity, hydrogen, and biodiesel as energy vectors, with a focus on powering an aluminum smelter in southern Italy. It evaluates these vectors in terms of efficiency, land requirements for carbon-neutral energy production, and capital expenditure, providing insights throughout the entire supply chain (upstream, midstream, and downstream) into their feasibility for industrial applications. The research reveals that biodiesel, despite being carbon neutral, is impractical due to extensive land requirements and lower efficiency if compared to other vectors. Hydrogen, downstream explored in two forms as thermal power generation and fuel cell technology, shows lower efficiency and higher capital expenditure compared to electricity. Additionally, green hydrogen production’s land requirements significantly exceed those of electricity-based systems. Electricity emerges as the most viable option, offering an overall higher efficiency, lower land requirements for its green production, and comparatively lower capital expenditure. The study’s findings highlight the importance of a holistic assessment of energy vectors, considering economic, environmental, and practical aspects along the entire energy supply chain, especially in industrial applications where the balance of these factors is crucial for long-term sustainability and feasibility. This comprehensive analysis provides valuable guidance for similar industrial applications, emphasizing the need for a balanced approach in the selection of energy vectors.

Rational design of natural leather-based water evaporator for electricity generation and functional applications

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting technology.Although abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and unadaptable shape have restricted their wide applications.Here,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and biocompatibility.Including numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-SA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series connection.Furthermore,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and seawater demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.

Techno-Economic Optimization of Novel Stand-Alone Renewable Based Electric Vehicle Charging Station near Bahria Town Karachi,Sindh Pakistan

Electric vehicles (EVs) are the most interesting and innovative technology in the 21st century because of theirenormous advantages, both technically and economically. Their emissions rate compared to fuel-based vehicles isnegligible as they do not consume fuel and hence do not emit any harmful gases. However, their bulk production,adoption and lack of charging stations increase the stress of power stations due to modern-day lifestyles. If Electricvehicles demand increases drastically then conventional power stations will not bear their demand and if theygenerate electricity by conventional means it will be very costly and may further add greenhouse gases. Therefore,this research provides the techno-economic assessment of a stand-alone renewable-dependent electric vehiclecharging station, excluding any burden on electrical utility. The proposed study is carried out in Bahria Town,Karachi, a city in Pakistan. In this study, HOMER Pro software was utilized for techno-economic assessment. Ahybrid system comprising solar Photovoltaic/Wind Turbine/Fuel cells and battery storage is included in the model.Solar and wind resources were taken from NASA’s website, where charging stations will be integrated. The overallresults show promising in terms of total Net Present Cost and the Cost of Energy which are 2.72M $ and 0.237 $,respectively. The total system generation is 3,598 Megawatt hours per year, and the total energy consumption is 885Megawatt hours per year.

Torsional vibration suppression and electromechanical coupling characteristics of electric drive system considering misalignment

The torque ripples resulting from external electromagnetic excitation and mechanical internal excitation contribute to significant torsional vibration issues within electromechanical coupling systems.To mitigate these fluctuations,a passive control strategy centered around a multi-stable nonlinear energy sink(MNES)is proposed.First,models for electromagnetic torque,gear nonlinear meshing torque,and misalignment torque are established.Building upon this foundation,an electromechanical coupling dynamic model of the electric drive system is formulated.Sensitivity analysis is conducted to determine the sensitive nodes of each mode and to provide guidance for the installation of the MNES.The structure of the MNES is introduced,and an electromechanical coupling dynamic model with the MNES is established.Based on this model,the influence of the misaligned angle on the electromechanical coupling characteristics is analyzed.In addition,the vibration suppression performance of the MNES is studied under both speed and uniform speed conditions.Finally,experimental testing is conducted to verify the vibration suppression performance of the MNES.The results indicate that misalignment triggers the emergence of its characteristic frequencies and associated sidebands.Meanwhile,the MNES effectively mitigates the torsional vibrations in the coupled system,demonstrating suppression rates of 52.69%in simulations and 63.3%in experiments.

Optimizing Household Wastes (Rice, Vegetables, and Fruit) as an Environmentally Friendly Electricity Generator

The high consumption of electricity and issues related to fossil energy have triggered an increase in energy prices and the scarcity of fossil resources.Consequently,many researchers are seeking alternative energy sources.One potential technology,the Microbial Fuel Cell(MFC)based on rice,vegetable,and fruit wastes,can convert chemical energy into electrical energy.This study aims to determine the potency of rice,vegetable,and fruit waste assisted by Cu/Mg electrodes as a generator of electricity.The method used was a laboratory experiment,including the following steps:electrode preparation,waste sample preparation,incubation of the waste samples,construction of a reactor using rice,vegetable,and fruit waste as a source of electricity,and testing.The tests included measuring electrical conductivity,electric current,voltage,current density,and power density.Based on the test results,the maximum current and voltage values for the fruit waste samples were 5.53 V and 11.5 mA,respectively,with a current density of 2.300 mA/cm^(2) and a power density of 12.719 mW/cm^(2).The results indicate the potential for a future development.The next step in development involves determining the optimum conditions for utilizing of rice,vegetable,and fruit waste.The results of the electrical conductivity test on rice,vegetable,and fruit waste samples were 1.51,2.88,and 3.98 mS,respectively,with the highest electrical conductivity value found in the fruit waste sample.

Analyzing the Wind-Dominant Electricity Market under Coexistence of Regulated and Deregulated Power Trading

Currently,both regulated and deregulated power trading exist in China’s power system,which has caused imbalanced funds in the electricity market.In this paper,a simulation analysis of the electricity market with wind energy resources is conducted,and the calculation methods of unbalanced funds are investigated systematically.In detail,the calculation formulas of unbalanced funds are illustrated based on their definition,and a two-track electricity market clearing model is established.Firstly,the concept of the dual-track system is explained,and the specific calculation formulas of various types of unbalanced funds are provided.Next,considering the renewable energy consumption,the market clearing model based on DC power flow is constructed and solved;by combining fitting methods of mid-and long-term curves,the unbalanced funds are calculated based on clearing results and formulas.

Strategic Placement of Charging Stations for Enhanced Electric Vehicle Adoption in San Diego, California

California mandated that 100% of vehicles sold must be electric by 2035. As electric vehicles (EVs) reach a higher penetration of the car sector, cities will need to provide publicly accessible charging stations to meet the charging demand of people who do not have access to a private charging spot like a personal garage. We have chosen to limit our scope to San Diego County due to its non-trivial size, well-defined shape, and dependence on personal vehicles;this project models 100% of current vehicles as electric, roughly 2.5 million. By planning for the future, our model becomes more useful as well as more equitable. We anticipate that our model will find locations that can service multiple population centers, while also maximizing distance to other stations. Sensitivity analysis and testing of our algorithms are conducted for Coronado Island, an island with 24,697 residents. Our formulation is then scaled to set the parameters for the whole county.

Opportunities to Improve the Quality of Environmental Reports and the Effectiveness of Environmental Impact Assessment: A Case of Electric Power Transmission Systems in Brazil

A good quality Environmental Impact Statement (EIS) is key for the effectiveness of Environmental Impact Assessment (EIA) processes and consequently to the acceptability of projects subject to EIA. The international literature has contributed to the understanding of the essential aspects to be verified regarding the quality of EIS, offering a wide spectrum of good practice examples related to the content of the studies. Even so, there is a need for empirical studies that allow the identification of specific aspects related to the context of application of the EIS, which could lead to the identification of opportunities to improve both the quality of the reports and also the effectiveness of EIA. Therefore, the present paper is focused on the quality review of a number of EIS submitted to the Brazilian Federal Environmental Agency (Ibama) to instruct the assessment of electric power transmission systems. Based on the application of the EIS quality review package as proposed by Lee and Colley (1992), the outcomes reveal opportunities for improving the scope of EIA, analysis of alternatives, prediction of magnitude and the assessment of impact significance. Finally, the development and/or adaptation of a similar tool for the systematic review of the quality of EIA reports is recommended.

An Energy Efficient Control Strategy for Electric Vehicle Driven by In-Wheel-Motors Based on Discrete Adaptive Sliding Mode Control

This paper presents an energy-efficient control strategy for electric vehicles(EVs)driven by in-wheel-motors(IWMs)based on discrete adaptive sliding mode control(DASMC).The nonlinear vehicle model,tire model and IWM model are established at first to represent the operation mechanism of the whole system.Based on the modeling,two virtual control variables are used to represent the longitudinal and yaw control efforts to coordinate the vehicle motion control.Then DASMC method is applied to calculate the required total driving torque and yaw moment,which can improve the tracking performance as well as the system robustness.According to the vehicle nonlinear model,the additional yaw moment can be expressed as a function of longitudinal and lateral tire forces.For further control scheme development,a tire force estimator using an unscented Kalman filter is designed to estimate real-time tire forces.On these bases,energy efficient torque allocation method is developed to distribute the total driving torque and differential torque to each IWM,considering the motor energy consumption,the tire slip energy consumption,and the brake energy~?recovery.Simulation results of the proposed control strategy using the co-platform of Matlab/Simulink and CarSim way.

Reinforcement Learning-Based Electric Vehicles Energy Management Strategy with Battery Thermal Model

The promotion of electric vehicles(EVs)is restricted due to their short cruising range.It is desirable to design an effective energy management strategy to improve their energy efficiency.Most existing work concerning energy management strategies focused on hybrids rather than the EVs.The work focusing on the energy management strategy for EVs mainly uses the traditional optimization strategies,thereby limiting the advantages of energy economy.To this end,a novel energy management strategy that considered the impact of battery thermal effects was proposed with the help of reinforcement learning.The main idea was to first analyze the energy flow path of EVs,further formulize the energy management as an optimization problem,and finally propose an online strategy based on reinforcement learning to obtain the optimal strategy.Additionally,extensive simulation results have demonstrated that our strategy reduces energy consumption by at least 27.4%compared to the existing methods.

Reducing Electrical Consumption in Stationary Long-Haul Trucks

On average, long-haul trucks in the U.S. use approximately 667 million gallons of fuel each year just for idling. This idling primarily facilitates climate control operations during driver rest periods. To mitigate this, our study explored ways to diminish the electrical consumption of climate control systems in class 8 trucks through innovative load reduction technologies. We utilized the CoolCalc software, developed by the National Renewable Energy Laboratory (NREL), which integrates heat transfer principles with extensive weather data from across the U.S. to mimic the environmental conditions trucks face year-round. The analysis of the CoolCalc simulations was performed using MATLAB. We assessed the impact of various technologies, including white paint, advanced curtains, and Thinsulate insulation on reducing electrical demand compared to standard conditions. Our findings indicate that trucks operating in the eastern U.S. could see electrical load reductions of up to 40%, while those in the western regions could achieve reductions as high as 55%. Such significant decreases in energy consumption mean that a 10 kWh battery system could sufficiently manage the HVAC needs of these trucks throughout the year without idling. Given that many long-haul trucks are equipped with battery systems of around 800 Ah (9.6 kWh), implementing these advanced technologies could substantially curtail the necessity for idling to power air conditioning systems.

The Impact of Hydrogen Energy Storage on the Electricity Harvesting

The economics,infrastructure,transportation,and level of living of a country are all influenced by energy.The gap between energy usage and availabil-ity is a global issue.Currently,all countries rely on fossil fuels for energy genera-tion,and these fossil fuels are not sustainable.The hydrogen proton exchange membrane fuel cell(PEMFC)power system is both clean and efficient.The fuel delivery system and the PEMFC make up the majority of the PEMFC power sys-tem.The lack of an efficient,safe,and cost-effective hydrogen storage system is still a major barrier to its widespread use.Solid hydrogen storage has the large capacity,safety and good reversibility.As a hydrogen source system,the hydro-gen supply characteristics affect the characteristics of the PEMFC at the output.In this paper,a mathematical model of a hydrogen source reactor and PEMFC based on chemical absorption/desorption of solid hydrogen storage is established,and a simulation model of a PEMFC power system coupled with solid hydrogen storage is established using MATLAB/SIMULINK software,and the hydrogen supply of the reactor is analyzed in detail.The influence of prominent factors is evaluated.The research results show that the proposed method improved the system perfor-mance.At the same time,increasing the PEMFC temperature,increasing the area of the proton exchange membrane and the oxygen supply pressure can increase the output power of the power system.

Overview of the Global Electricity System in Oman Considering Energy Demand Model Forecast

Lately,in modern smart power grids,energy demand for accurate forecast of electricity is gaining attention,with increased interest of research.This is due to the fact that a good energy demand forecast would lead to proper responses for electricity demand.In addition,proper energy demand forecast would ensure efficient planning of the electricity industry and is critical in the scheduling of the power grid capacity and management of the entire power network.As most power systems are been deregulated and with the rapid introduction and development of smart-metering technologies in Oman,new opportunities may arise considering the efficiency and reliability of the power system;like price-based demand response programs.These programs could either be a large scale for household,commercial or industrial users.However,excellent demand forecasting models are crucial for the deployment of these smart metering in the power grid based on good knowledge of the electricity market structure.Consequently,in this paper,an overview of the Oman regulatory regime,financial mechanism,price control,and distribution system security standard were presented.More so,the energy demand forecast in Oman was analysed,using the econometric model to forecasts its energy peak demand.The energy econometric analysis in this study describes the relationship between the growth of historical electricity consumption and macro-economic parameters(by region,and by tariff),considering a case study of Mazoon Electricity Distribution Company(MZEC),which is one of the major power distribution companies in Oman,for effective energy demand in the power grid.

Traceability Technology of DC Electric Energy Metering for On-Site Inspection of Chargers

The on-site inspection of high-power DC chargers results in new DC high-current measurement and DC energy traceability system requirements.This paper studies the traceability technology of electric energy value for automotive high-power DC chargers,including:(1)the traceability method of the built-in DC energy meter and shunt of the charger;(2)precision DC high current and small precision DC voltage output and measurement technology.This paper designs a 0.1 mA∼600 A DC high current measurement system and proposes a 0.005 level DC powermeasurement traceability system.The uncertainty evaluation experiment of theDC powermeasurement calibration system and the high-power DC charger’s on-site calibration experiment results verify the method’s effectiveness and feasibility in this paper.The experimental results show that the combined standard uncertainty of the DC power metering verification system can be 0.0451%.

Research on Optimal Configuration of Energy Storage in Wind-Solar Microgrid Considering Real-Time Electricity Price

Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.