Distribution Network Optimization Model of Industrial Park with Distributed Energy Resources under the Carbon Neutral Targets

Taking an industrial park as an example,this study aims to analyze the characteristics of a distribution network that incorporates distributed energy resources(DERs).The study begins by summarizing the key features of a distribution network with DERs based on recent power usage data.To predict and analyze the load growth of the industrial park,an improved back-propagation algorithm is employed.Furthermore,the study classifies users within the industrial park according to their specific power consumption and supply requirements.This user segmentation allows for the introduction of three constraints:node voltage,wire current,and capacity of DERs.By incorporating these constraints,the study constructs an optimization model for the distribution network in the industrial park,with the objective of minimizing the total operation and maintenance cost.The primary goal of these optimizations is to address the needs of DERs connected to the distribution network,while simultaneously mitigating their potential adverse impact on the network.Additionally,the study aims to enhance the overall energy efficiency of the industrial park through more efficient utilization of resources.

Investigating the components of fintech ecosystem for distributed energy investments with an integrated quantum spherical decision support system

This study aimed to evaluate the components of a fintech ecosystem for distributed energy investments.A new decision-making model was created using multiple stepwise weight assessment ratio analysis and elimination and choice translating reality techniques based on quantum spherical fuzzy sets.First,in this model,the criteria for distributed energy investment necessities were weighted.Second,we ranked the components of the fintech ecosystem for distributed energy investments.The main contribution of this study is that appropriate strategies can be presented to design effective fintech ecosystems to increase distributed energy investments,by considering an original fuzzy decision-making model.Capacity is the most critical issue with respect to distributed energy investment necessities because it has the greatest weight(0.261).Pricing is another significant factor for this condition,with a weight of 0.254.Results of the ranking of the components of the fintech ecosystem indicate that end users are of the greatest importance for the effectiveness of this system.It is necessary to develop new techniques for the energy storage process,especially with technological developments,to prevent disruptions in energy production capacity.In addition,customers’expectations should be considered for the development of effective and user-friendly financial products that are preferred by a wider audience.This would have a positive effect on fintech ecosystem performance.

Grid Side Distributed Energy Storage Cloud Group End Region Hierarchical Time-Sharing Configuration Algorithm Based onMulti-Scale and Multi Feature Convolution Neural Network

There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.

Co-Harvest Phase-Change Enthalpy and Isomerization Energy for High-Energy Heat Output by Controlling Crystallization of Alkyl-Grafted Azobenzene Molecules

Photoisomerization-induced phase change are important for co-harvesting the latent heat and isomerization energy of azobenzene molecules.Chemically optimizing heat output and energy delivery at alternating temperatures are challenging because of the differences in crystallizability and isomerization.This article reports two series of asymmetrically alkyl-grafted azobenzene(Azo-g),with and without a methyl group,that have an optically triggered phase change.Three exothermic modes were designed to utilize crystallization enthalpy(△H_(c))and photothermal(isomerization)energy(△H_(p))at different temperatures determined by the crystallization.Azo-g has high heat output(275-303 J g^(-1))by synchronously releasing△H_(c)and△H_(p)over a wide temperature range(-79℃to 25℃).We fabricated a new distributed energy utilization and delivery system to realize a temperature increase of 6.6℃at a temperature of-8℃.The findings offer insight into selective utilization of latent heat and isomerization energy by molecular optimization of crystallization and isomerization processes.

GRU-integrated constrained soft actor-critic learning enabled fully distributed scheduling strategy for residential virtual power plant

In this study,a novel residential virtual power plant(RVPP)scheduling method that leverages a gate recurrent unit(GRU)-integrated deep reinforcement learning(DRL)algorithm is proposed.In the proposed scheme,the GRU-integrated DRL algorithm guides the RVPP to participate effectively in both the day-ahead and real-time markets,lowering the electricity purchase costs and consumption risks for end-users.The Lagrangian relaxation technique is introduced to transform the constrained Markov decision process(CMDP)into an unconstrained optimization problem,which guarantees that the constraints are strictly satisfied without determining the penalty coefficients.Furthermore,to enhance the scalability of the constrained soft actor-critic(CSAC)-based RVPP scheduling approach,a fully distributed scheduling architecture was designed to enable plug-and-play in the residential distributed energy resources(RDER).Case studies performed on the constructed RVPP scenario validated the performance of the proposed methodology in enhancing the responsiveness of the RDER to power tariffs,balancing the supply and demand of the power grid,and ensuring customer comfort.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

Supply modes for renewable-based distributed energy systems and their applications:case studies in China

Distributed energy systems(DES),as an integrated energy system with coupled distributed energy resources,have great potential in reducing carbon dioxide emissions and improving energy efficiencies.Considering the background of urbanization and the energy revolution in China,the study investigates the renewable-based DESs supply modes and their application in China.A new method is proposed to classify DESs supply modes into three categories considering the renewable resource in domination,and their application domains are discussed.A comprehensive model is given for economic and environmental evaluation.Typical case studies show that the renewable-based DES systems can supply the energy in a cost-effective and environment-friendly way.Among them,the biomass waste dominated supply mode can not only achieve"zero"carbon emissions but also"zero"energy consumption,even though not yet economically attractive under the present policy and market conditions.Thus,recommendations are given to promote the further deployment of renewable-based DESs,regarding their supply modes,policy requirements,and issues to be addressed.

Distributed energy storage node controller and control strategy based on energy storage cloud platform architecture

Based on the energy storage cloud platform architecture,this study considers the extensive configuration of energy storage devices and the future large-scale application of electric vehicles at the customer side to build a new mode of smart power consumption with a flexible interaction,smooth the peak/valley difference of the load side power,and improve energy efficiency.A plug and play device for customer-side energy storage and an internet-based energy storage cloud platform are developed herein to build a new intelligent power consumption mode with a flexible interaction suitable for ordinary customers.Based on the load perception of the power grid,this study aims to investigate the operating state and service life of distributed energy storage devices.By selecting an integrated optimal control scheme,this study designs a kind of energy optimization and deployment strategy for stratified partition to reduce the operating cost of the energy storage device on the client side.The effectiveness of the system and the control strategy is verified through the Suzhou client-side distributed energy storage demonstration project.

Kinetic analysis and modeling of maize straw hydrochar combustion using a multi-Gaussian-distributed activation energy model

Combustion kinetics of the hydrochar was investigated using a multi-Gaussian-distributed activation energy model(DAEM)to ex-pand the knowledge on the combustion mechanisms.The results demonstrated that the kinetic parameters calculated by the multi-Gaussian-DAEM accurately represented the experimental conversion rate curves.Overall,the feedstock combustion could be divided into four stages:the decomposition of hemicellulose,cellulose,lignin,and char combustion.The hydrochar combustion could in turn be divided into three stages:the combustion of cellulose,lignin,and char.The mean activation energy ranges obtained for the cellulose,lignin,and char were 273.7-292.8,315.1-334.5,and 354.4-370 kJ/mol,respectively,with the standard deviations of 2.1-23.1,9.5-27.4,and 12.1-22.9 kJ/mol,re-spectively.The cellulose and lignin contents first increased and then decreased with increasing hydrothermal carbonization(HTC)temperature,while the mass fraction of char gradually increased.

Comparison of life cycle performance of distributed energy system and conventional energy system for district heating and cooling in China

The distributed energy system has achieved significant attention in respect of its application for singlebuilding cooling and heating.Researching on the life cycle environmental impact of distributed energy systems(DES)is of great significance to encourage and guide the development of DES in China.However,the environmental performance of distributed energy systems in a building cooling and heating has not yet been carefully analyzed.In this study,based on the standards of ISO14040-2006 and ISO14044-2006,a life-cycle assessment(LCA)of a DES was conducted to quantify its environmental impact and a conventional energy system(CES)was used as the benchmark.GaBi 8 software was used for the LCA.And the Centre of Environmental Science(CML)method and Eco-indicator 99(EI 99)method were used for environmental impact assessment of midpoint and endpoint levels respectively.The results indicated that the DES showed a better life-cycle performance in the usage phase compared to the CES.The life-cycle performance of the DES was better than that of the CES both at the midpoint and endpoint levels in view of the whole lifespan.It is because the CES to DES indicator ratios for acidification potential,eutrophication potential,and global warming potential are 1.5,1.5,and 1.6,respectively at the midpoint level.And about the two types of impact indicators of ecosystem quality and human health at the endpoint level,the CES and DES ratios of the other indicators are greater than1 excepting the carcinogenicity and ozone depletion indicators.The human health threat for the DES was mainly caused by energy consumption during the usage phase.A sensitivity analysis showed that the climate change and inhalable inorganic matter varied by 1.3%and 6.1%as the electricity increased by 10%.When the natural gas increased by 10%,the climate change and inhalable inorganic matter increased by 6.3%and 3.4%,respectively.The human health threat and environmental damage caused by the DES could be significantly reduced by the optimization of natural gas and electricity consumption.

Effect of parallel resonance on the electron energy distribution function in a 60 MHz capacitively coupled plasma

In general,as the radio frequency(RF)power increases in a capacitively coupled plasma(CCP),the power transfer efficiency decreases because the resistance of the CCP decreases.In this work,a parallel resonance circuit is applied to improve the power transfer efficiency at high RF power,and the effect of the parallel resonance on the electron energy distribution function(EEDF)is investigated in a 60 MHz CCP.The CCP consists of a power feed line,the electrodes,and plasma.The reactance of the CCP is positive at 60 MHz and acts like an inductive load.A vacuum variable capacitor(VVC)is connected in parallel with the inductive load,and then the parallel resonance between the VVC and the inductive load can be achieved.As the capacitance of the VVC approaches the parallel resonance condition,the equivalent resistance of the parallel circuit is considerably larger than that without the VVC,and the current flowing through the matching network is greatly reduced.Therefore,the power transfer efficiency of the discharge is improved from 76%,70%,and 68%to 81%,77%,and 76%at RF powers of 100 W,150 W,and 200 W,respectively.At parallel resonance conditions,the electron heating in bulk plasma is enhanced,which cannot be achieved without the VVC even at the higher RF powers.This enhancement of electron heating results in the evolution of the shape of the EEDF from a biMaxwellian distribution to a distribution with the smaller temperature difference between high-energy electrons and low-energy electrons.Due to the parallel resonance effect,the electron density increases by approximately 4%,18%,and 21%at RF powers of 100 W,150 W,and 200 W,respectively.

Design of the Multi-Energy Complementary Distributed Energy System for Towns

The multi-energy complementary distributed energy system (MCDES) covers a variety of energy forms, involves complex operation modes, and contains a wealth of control equipment and coupling links. It can realize the complementary and efficient use of different types of energy, which is the basic component of the physical layer of the Energy Internet. In this paper, aiming at the demand of the energy application for towns, a distributed energy system based on multi-energy complementary is constructed. Firstly, the supply condition of the distributed energy for the demonstration project is analyzed, and the architecture of the multi-energy complementary distributed energy system is established. Then the regulation strategy of the multi-energy complementary distributed energy system is proposed. Finally, an overall system scheme for the multi-energy complementary distributed energy system suitable for towns is developed, which provides a solid foundation for the development and promotion of the multi-energy complementary distributed energy system.

Risk Assessment of Distributed Energy System Based on Fuzzy Analytic Hierarchy Process

Risk assessment of distributed energy system often has uncertainty and subjective problems. The problems will have some impact on the results. To solve the problems, a method of improved fuzzy analytic hierarchy process is proposed. By using the fuzzy analytic hierarchy process method, a hierarchical analysis model is established. And then according to the given judgment matrix of each index layer, we calculate whether it meets the consistency condition. And then if the judgment matrix does not meet the consistency condition, the problem will be solved by the improving of particle swarm optimization (PSO) with Kalman filter. The practice in the distributed energy system shows that the method can not only fully reflect the fuzziness of assessment elements and process, but also reduce the influence of individual subjective factors and better evaluation results can be achieved.

Simulation of the spatio-temporal evolution of the electron energy distribution function in a pulsed hollow-cathode discharge

This article presents the 2D simulation results of a nanosecond pulsed hollow cathode discharge obtained through a combination of fluid and kinetic models.The spatio-temporal evolution of the electron energy distribution function(EEDF)of the plasma column and electrical characteristics of the nanosecond pulsed hollow cathode discharge at a gas pressure of 5 Torr are studied.The results show that the discharge development starts with the formation of an ionization front at the anode surface.The ionization front splits into two parts in the cathode cavity while propagating along its lateral surfaces.The ionization front formation leads to an increase in the fast isotropic EEDF component at its front,as well as in the anisotropic EEDF component.The accelerated electrons enter the cathode cavity,which significantly contributes to the formation of the highenergy EEDF component and EEDF anisotropy.

Comparative Study on Distributed Waste Pyrolysis Cold Emission Energy Station and Incineration Power Generation

The proper terminal disposal of organic solid waste such as domestic waste is a worldwide issue.Landfill covers a large area,with limited capacity,and a single landfill will be filled one day;incineration is costly to build and operate.These methods all need to transfer and centralized treatment,and secondary pollution is difficult to control,against the purification law of the nature."NIMBY effect"is very serious,and the social cost of treatment is increasing,becoming a heavy financial burden."The Distributed Waste Pyrolysis Cold Emission Energy Station"developed by Hunan Zhongzhou Energy-Saving Technology Co.,Ltd.overcomes these disadvantages and constructs a more appropriate environmental economic industrial chain for the treatment of organic solid waste such as urban and rural household waste.Based on its technical characteristics,this paper compares it with waste incineration power generation project in the aspects of secondary pollution control,treatment effect,energy utilization,investment and operation economy,etc.

MECHANISM OF CHANGE IN THE CATION INDUCED EXCITA TION ENERGY DISTRIBUTION BETWEEN PSⅡ AND PSⅠ IN THE CHLOROPLAST MEMBRANE FROM ZOSTERA MARINA *

The interrelations between thylakoid polypeptide components and Mg 2+ induced Chl a fluorescence and thylakoid surface charge changes were investigated in Zostera marina chloroplasts treated with Ca 2+ and trypsin. It was observed that:1. The increase of Mg 2+ induced PSⅡ fluorescence intensity was closely related to the decrease of Mg 2+ induced surface charge density of the thylakoid membrane in the normal chloroplast; 2. Removal of the 32~34 kD polypeptides of the thylakoid surface by Ca 2+ extraction of the chloroplast did not affect the Mg 2+ induced phenomena; 3. If the Ca 2+ treated chloroplast was further digested by trypsin to remove the 26 kD polypeptide of the membrane surface, the Mg 2+ induced phenomena disappeared completely. These results clearly indicated that the 26 kD polypeptide of thylakoid surface is the specific acting site of the cation that induced these two correlated phenomena in the chloroplast from Zostera marina. The mechanism on the regulating effect of the cation on excitation energy distribution between PSⅡ and PSⅠ was discussed.

Effect of Surface Potential Barrier on the Electron Energy Distribution of NEA Photocathodes

By calculating the energy distribution of electrons reaching the photocathode surface and solving the Schrodinger equation that describes the behavior of an electron tunneling through the surface potential barrier,we obtain an equation to calculate the emitted electron energy distribution of transmission-mode NEA GaAs photocathodes. Accord- ing to the equation,we study the effect of cathode surface potential barrier on the electron energy distribution and find a significant effect of the barrier-Ⅰ thickness or end height,especially the thickness,on the quantum efficiency of the cath- ode. Barrier Ⅱ has an effect on the electron energy spread, and an increase in the vacuum level will lead to a narrower electron energy spread while sacrificing a certain amount of cathode quantum efficiency. The equation is also used to fit the measured electron energy distribution curve of the transmission-mode cathode and the parameters of the surface barri- er are obtained from the fitting. The theoretical curve is in good agreement with the experimental curve.

Effects of power on ion behaviors in radio-frequency magnetron sputtering of indium tin oxide(ITO)

This study delves into ion behavior at the substrate position within RF magnetron discharges utilizing an indium tin oxide(ITO)target.The positive ion energies exhibit an upward trajectory with increasing RF power,attributed to heightened plasma potential and initial emergent energy.Simultaneously,the positive ion flux escalates owing to amplified sputtering rates and electron density.Conversely,negative ions exhibit broad ion energy distribution functions(IEDFs)characterized by multiple peaks.These patterns are clarified by a combination of radiofrequency oscillation of cathode voltage and plasma potential,alongside ion transport time.This elucidation finds validation in a one-dimensional model encompassing the initial ion energy.At higher RF power,negative ions surpassing 100 e V escalate in both flux and energy,posing a potential risk of sputtering damages to ITO layers.

Stochastic and Distributed Optimal Energy Management of Active Distribution Networks Within Integrated Office Buildings

This paper proposes a stochastic and distributed optimal energy management approach for active distribution networks(ADNs)within office buildings.The proposed approach aims at scheduling office buildings fitted with heating ventilation and air conditioning(HVAC)systems,and electric vehicle(EV)charging piles,to participate in the ADN optimization.First,an energy management approach for the ADN with aggregated office buildings is proposed.And the ADN optimization model is formulated considering the detailed building thermal dynamics and the mobile behaviors of workers.Then,to consider un-certainties of photovoltaic(PV)power,scenario-based stochastic programming is integrated into the ADN optimization model.To further realize the stochastic energy management of the ADN within office buildings in a distributed manner,the alternating direction method of multipliers(ADMM)is used to solve the ADN optimization model.The original ADN optimization problem is divided into the network-side and the building-side sub-problems to effectively protect the privacy of the ADN and the office buildings.Finally,the ADN optimization model incorporating office buildings is validated in the winter by numerical studies.In addition,the impacts of comfort temperature range and expected state of charge(SOC)at departure are analyzed.Index Terms—ADN,EV,HVAC system,Office building,Stochastic and distributed energy management.

Experimental studies of H_(2)/Ar plasma in a cylindrical inductive discharge with an expansion region

The electrical parameters of H_(2)/Ar plasma in a cylindrical inductive discharge with an expansion region are investigated by a Langmuir probe,where Ar fractions range from 0%to 100%.The influence of gas composition and pressure on electron density,the effective electron temperature and the electron energy probability functions(EEPFs)at different spatial positions are present.In driver region,with the introduction of a small amount of Ar at 0.3 Pa,there is a rapid increase in electron density accompanied by a decrease in the effective electron temperature.Additionally,the shape of the EEPF transitions from a three-temperature distribution to a bi-Maxwellian distribution due to an increase in electron-electron collision.However,this phenomenon resulting from the changes in gas composition vanishes at 5 Pa due to the prior depletion of energetic electrons caused by the increase in pressure during hydrogen discharge.The EEPFs for the total energy in expansion region is coincident to these in the driver region at 0.3 Pa,as do the patterns of electron density variation between these two regions for differing Ar fractions.At 5 Pa,as the discharge transitions from H_(2)to Ar,the EEPFs evolved from a bi-Maxwellian distribution with pronounced low energy electrons to a Maxwellian distribution in expansion region.This evolve may be attributed to a reduction in molecular vibrational excitation reactions of electrons during transport and the transition from localized electron dynamics in hydrogen discharge to non-localized electron dynamics in argon discharge.In order to validate the experimental results,we use the COMSOL simulation software to calculate electrical parameters under the same conditions.The evolution and spatial distribution of the electrical parameters of the simulation results agree well with the trend of the experimental results.