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.

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.

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.

Power Generation Enhancement in a Solar Energy and Biomass-Based Distributed Energy System using H_(2)O/CO_(2)Hybrid Gasification

A new solar energy and biomass-based distributed energy system using H_(2)O/CO_(2)hybrid gasification is proposed,and their complementarity to enhance the system's energy efficiency is investigated and shown.In the system,concentrated solar energy is used to provide heat for biomass gasification;two gasifying agents(H_(2)O and CO_(2))are adopted to enhance syngas yields,and the produced solar fuel is further burned for power production in a combined cycle plant.Results show that CO share in gasification products is remarkably increased with the increment of CO_(2)/H_(2)O mole ratio caused by the boudouard reaction with the consumption of fixed carbon,while the H_(2)share is decreased;the optimal solar-to-fuel efficiency,27.88%,is achieved when the temperature and CO_(2)/H_(2)O mole ratio are 1050℃and 0.45,respectively.The emission reduction rate of CO_(2)in the system under design conditions is reduced by 2.31%compared with that using only H_(2)O agent.The annual power production of the system is increased by 1.39%,and the thermodynamic and environmental performances are significantly improved.Moreover,an economic assessment is conducted to forecast the technical feasibility of the hybrid gasification technology.This work provides a promising route to improving the thermochemical utilization efficiency of solar energy and solid fuel.

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.

Multi-stage Sensitivity Analysis of Distributed Energy Systems: A Variance-based Sobol Method

In the face of the pressing environmental issues,the past decade witnessed the booming development of the distributed energy systems(DESs).A notable problem of DESs is the inevitable uncertainty that may make DESs deviate significantly from the deterministically obtained expectations,in both aspects of optimal design and economic operation.It thus necessitates the sensitivity analysis to quantify the impacts of the massive parametric uncertainties.This paper aims to give a comprehensive quantification,and carries out a multi-stage sensitivity analysis on DESs from the perspectives of evaluation criteria,optimal design and economic operation.First,a mathematical model of a DES is developed to present the solutions to the three stages of the DES.Second,the Monte-Carlo simulation is carried out subject to the probabilistic distributions of the energy,technical and economic parameters.Based on the simulation results,the variance-based Sobol method is applied to calculate the individual importance,interactional importance and total importance of various parameters.The comparison of the multi-stage results shows that only a few parameters play critical roles while the uncertainty of most of the massive parameters has little impact on the system performance.In addition,the influence of parameter interactions in the optimal design stage are much stronger than that in the evaluation criteria and operation strategy stages.

A comprehensive review of planning,modeling,optimization,and control of distributed energy systems

Distributed energy system,a decentralized low-carbon energy system arranged at the customer side,is characterized by multi-energy complementarity,multi-energy flow synergy,multi-process coupling,and multi-temporal scales(n-M characteristics).This review provides a systematic and comprehensive summary and presents the current research on distributed energy systems in three dimensions:system planning and evaluation,modeling and optimization,and operation and control.Under the regional environmental,resource,and policy constraints,planning distributed energy systems should fully integrate technical,economic,environmental,and social factors and consider device characteristics,system architecture,and source-load uncertainties.Further,this review presents four modeling perspectives for optimizing and analyzing distributed energy systems,including energy hub,thermodynamics,heat current,and data-driven.The system’s optimal operation and scheduling strategies,disturbance analysis,and related control methods are also discussed from the power system and thermal system,respectively.In all,more research is required for distributed energy systems based on an integrated energy perspective in optimal system structure,hybrid modeling approaches,data-driven system state estimation,cross-system disturbance spread,and multi-subject interaction control.

Study on operation strategy and load forecasting for distributed energy system based on Chinese supply-side power grid reform

This study focuses on the development and analysis of a real-time updated operations strategy of a distributed energy system(DES).Owing to the relevant Chinese policy of electrical transmission and distribution,combined cooling,heating,and power system(CCHP)and photovoltaic(PV)systems are not currently allowed.However,with the Chinese supply-side power grid reform,the permissions for connections between DESs and utilities are gradually evolving.By performing building simulation and using mixed integer linear programming(MILP),a real-time updated operation strategy of a DES is established.Then,considering the DES from Tianjin Eco-city as a case study,a comparative analysis between this updated strategy and the current operation strategy is performed by evaluating three factors:economic efficiency,energy consumption,and CO2 emission.The results show that the updated strategy can reduce 29.12%of electricity time-of-use cost,10.11%of total fuel consumption,and 18.40%of CO2 emission during the cooling season.Besides,a method of“rolling load forecasting”for DES by using Support vector regression machine(SVR)is proposed and discussed.The testing shows that the Mean Absolute Percentage Error(MAPE)is below 7.5%.And when the training sample is large,the particle swarm optimization algorithm can be used to shorten the modeling time of the air conditioning load forecasting model.

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.

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.

A Distributed Energy System with Advanced Utilization of Internal Combustion Engine Waste Heat

New trigeneration system consists of an internal combustion engine,a power and cooling cogeneration system and an absorption heat transformer system.The exhaust gas is recovered by the power and cooling cogeneration subsystem producing the cooling and power.The jacket water is recovered by the absorption heat transformer subsystem producing lowpressure steam.The exergy performance and the energy saving performance which is evaluated by the primary energy saving ratio of the new distributed energy system are analyzed.The effects of the ratio of the output power and cooling of the power and cooling cogeneration subsystem and the generator outlet temperature of the absorption heat transformer subsystem to the primary energy saving ratio are considered.The contributions of the subsystems to the primary energy saving ratio are quantified.The maximum primary energy saving ratio of the new distributed energy system is 15.8%,which is 3.9 percentage points higher than that of the conventional distributed energy system due to the cascade utilization of the waste heat from the internal combustion engine.

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.

State-of-charge Balance Control and Safe Region Analysis for Distributed Energy Storage Systems with Constant Power Loads

This paper presents a fully distributed state-of-charge balance control (DSBC) strategy for a distributed energy storage system (DESS). In this framework, each energy storage unit (ESU) processes the state-of-charge (SoC) information from its neighbors locally and adjusts the virtual impedance of the droop controller in real-time to change the current sharing. It is shown that the SoC balance of all ESUs can be achieved. Due to virtual impedance, voltage deviation of the bus occurs inevitably and increases with load power. Meanwhile, widespread of the constant power load (CPL) in the power system may cause instability. To ensure reliable operation of DESS under the proposed DSBC, the concept of the safe region is put forward. Within the safe region, DESS is stable and voltage deviation is acceptable. The boundary conditions of the safe region are derived from the equivalent model of DESS, in which stability is analyzed in terms of modified Brayton-Moser's criterion. Both simulations and hardware experiments verify the accuracy of the safe region and effectiveness of the proposed DSBC strategy.

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.

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.

Simulations of electron energy distribution of Pd-like Xe system based on OFI

X-ray laser based on OFI is a promising way to realize the table-top X-ray laser.A simple model to describe the electron energy distribution in plasma produced by circularly polarized optical-field-induced ionization is constructed on the basis of ADK tunneling ionization theory.The ionization rate,threshold intensity,residual energy and electron energy distribution of Pd-like Xe system based on optical-field-induced ionization are calculated.The results are useful to further experments on X-ray laser of Pa-like Xe system.