After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally alte...After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and utilized.This change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized approach.At the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy resources.The effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and sustainability.This allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy management.However,there is still no extensive implementation of such sharing models in today’s electricitymarkets.Research on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading market.This paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.展开更多
This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards grea...This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards greater decentralization and renewable integration,traditional optimization methods struggle to address the inherent complexities and uncertainties.Our proposed MARL framework enables adaptive,decentralized decision-making for both the distribution system operator and individual VPPs,optimizing economic efficiency while maintaining grid stability.We formulate the problem as a Markov decision process and develop a custom MARL algorithm that leverages actor-critic architectures and experience replay.Extensive simulations across diverse scenarios demonstrate that our approach consistently outperforms baseline methods,including Stackelberg game models and model predictive control,achieving an 18.73%reduction in costs and a 22.46%increase in VPP profits.The MARL framework shows particular strength in scenarios with high renewable energy penetration,where it improves system performance by 11.95%compared with traditional methods.Furthermore,our approach demonstrates superior adaptability to unexpected events and mis-predictions,highlighting its potential for real-world implementation.展开更多
The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context ...The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context of large-scale distributed renewable energy integration into the power grid,conventional island power grid line layouts can no longer meet actual demands.It is necessary to combine the operational characteristics of island power systems and historical load data to perform load forecasting,thereby generating power grid line layout paths.This article focuses on large-scale distributed renewable energy integration,summarizing optimization strategies for island power grid line layouts,and providing a solid guarantee for the safe and stable operation of island power systems.展开更多
A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncer...A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncertainties of renewable energy sources(RESs)is constructed without requiring the full distribution knowledge of the uncertainties.The power balance chance constraint is reformulated within the framework of the distributionally robust optimization(DRO)approach.With the exchange of information and energy flow,each microgrid can achieve its local supply-demand balance.Furthermore,the closed-loop stability and recursive feasibility of the proposed algorithm are proved.The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.展开更多
To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model...To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model mainly consists of two parts, the determination of initial configuration schemes according to user preference and the selection of the optimal scheme. The comprehensive evaluation index（CEI）, which is acquired through the analytic hierarchy process（AHP） weight calculation method, is adopted as the evaluation criterion to rank the initial schemes. The optimal scheme is obtained according to the ranking results. The proposed model takes the diversity of different equipment parameters and investment cost into consideration and can give relatively suitable and economical suggestions for system configuration.Additionally, unlike Homer Pro, the proposed model considers the complementation of different renewable energy resources, and thus the rationality of the multi-energy DG system is improved compared with the single evaluation criterion method which only considers the total cost.展开更多
Device-to-Device(D2D) communication has been proposed as a promising implementation of green communication to benefit the existed cellular network.In order to limit cross-tier interference while explore the gain of sh...Device-to-Device(D2D) communication has been proposed as a promising implementation of green communication to benefit the existed cellular network.In order to limit cross-tier interference while explore the gain of short-range communication,we devise a series of distributed power control(DPC) schemes for energy conservation(EC)and enhancement of radio resource utilization in the hybrid system.Firstly,a constrained opportunistic power control model is built up to take advantage of the interference avoidance methodology in the presence of service requirement and power constraint.Then,biasing scheme and admission control are added to evade ineffective power consumption and maintain the feasibility of the system.Upon feasibility,a non-cooperative game is further formulated to exploit the profit in EC with minor influence on spectral efficiency(SE).The convergence of the DPC schemes is validated and their performance is confirmed via simulation results.展开更多
Under the Kyoto Protocol,Japanwas supposed to reduce six percent of the green house gas (GHG) emission in 2012. However, until the year 2010, the statistics suggested that the GHG emission increased 4.2%. What is more...Under the Kyoto Protocol,Japanwas supposed to reduce six percent of the green house gas (GHG) emission in 2012. However, until the year 2010, the statistics suggested that the GHG emission increased 4.2%. What is more challenge is, afterFukushimacrisis, without the nuclear energy,Japanmay produce about 15 percent more GHG emissions than1990 inthis fiscal year. It still has to struggle to meet the target set by Kyoto Protocol. The demonstration area of “smart community” suggests Japanese exploration for new low carbon strategies. The study proposed a demand side response energy system, a dynamic tree-like hierarchical model for smart community. The model not only conveyed the concept of smart grid, but also built up a smart heat energy supply chain by offline heat transport system. Further, this model promoted a collaborative energy utilization mode between the industrial sector and the civil sector. In addition, the research chose the smart community inKitakyushuas case study and executed the model. The simulation and the analysis of the model not only evaluate the environmental effect of different technologies but also suggest that the smart community inJapanhas the potential but not easy to achieve the target, cut down 50% of the CO2 emission.展开更多
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 back...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.展开更多
The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high co...The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.展开更多
Global renewable energy has maintained a steady growth in recent years, mainly fostered by national policies and increasing demand. Analyzing the experience of renewable energy development in developed countries can b...Global renewable energy has maintained a steady growth in recent years, mainly fostered by national policies and increasing demand. Analyzing the experience of renewable energy development in developed countries can be important to provide reference and guidance for its adoption in other countries. First, we compare and summarize definitions of distributed generation from 18 leading countries and organizations in renewable energy. On this basis, we provide three basic characteristics for successful distributed generation using renewable resources. Then, we empirically analyze the distributed and centralized development of renewable energy in Germany with focus on wind and photovoltaic power. We determined that 95% of the photovoltaic generation and 85% of the wind power generation is distributed in Germany, suggesting that the most suitable generation mode for renewable energy is the distributed approach.展开更多
Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power o...Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.展开更多
With the rapid increasing of maritime activities, maritime wireless networks(MWNs) with high reliability, high energy efficiency, and low delay are required. However, the centralized networking with fixed resource sch...With the rapid increasing of maritime activities, maritime wireless networks(MWNs) with high reliability, high energy efficiency, and low delay are required. However, the centralized networking with fixed resource scheduling is not suitable for MWNs due to the special environment. In this paper,we introduce the collaborative relay communication in distributed MWNs to improve the link reliability, and propose an orthogonal time-frequency resource block reservation based multiple access(RRMA) scheme for both one-hop direct link and two-hop collaborative relay link to reduce the interference. To further improve the network performance, we formulate an energy efficiency(EE) maximization resource allocation problem and solve it by an iterative algorithm based on the Dinkelbach method. Finally, numerical results are provided to investigate the proposed RRMA scheme and resource allocation algorithm, showing that the low outage probability and transmission delay can be attained by the proposed RRMA scheme. Moreover,the proposed resource allocation algorithm is capable of achieving high EE in distributed MWNs.展开更多
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 bu...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.展开更多
Highly penetration of Distributed Energy Resources (DER) on the grid systems nowadays makes the systems grow dynamically. The system become more complex and the protection system become more complicated. The protectio...Highly penetration of Distributed Energy Resources (DER) on the grid systems nowadays makes the systems grow dynamically. The system become more complex and the protection system become more complicated. The protection relay should accommodate the system changes according to the system conditions and topologies. As part of developmental aspect of Distributed Artificial Intelligent, Multi Agent System (MAS) is a challenging method for improving the intelligent properties of relay protection. This paper introduces the use of MAS approach on radial distribution system protection dominated with DER using dispersed adaptive rule-based protection supported by distributed database agent. The simulation results confirmed that the proposed algorithm can respond within 15.05 ms.展开更多
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(DE...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.展开更多
This paper advocates the use of the distributed compressed sensing(DCS)paradigm to deploy energy harvesting(EH)Internet of Thing(IoT)devices for energy self-sustainability.We consider networks with signal/energy model...This paper advocates the use of the distributed compressed sensing(DCS)paradigm to deploy energy harvesting(EH)Internet of Thing(IoT)devices for energy self-sustainability.We consider networks with signal/energy models that capture the fact that both the collected signals and the harvested energy of different devices can exhibit correlation.We provide theoretical analysis on the performance of both the classical compressive sensing(CS)approach and the proposed distributed CS(DCS)-based approach to data acquisition for EH IoT.Moreover,we perform an in-depth comparison of the proposed DCSbased approach against the distributed source coding(DSC)system.These performance characterizations and comparisons embody the effect of various system phenomena and parameters including signal correlation,EH correlation,network size,and energy availability level.Our results unveil that,the proposed approach offers significant increase in data gathering capability with respect to the CS-based approach,and offers a substantial reduction of the mean-squared error distortion with respect to the DSC system.展开更多
This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices.This method integrates features including photovoltaic(PV)systems,energy storage coupling,varied energy rol...This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices.This method integrates features including photovoltaic(PV)systems,energy storage coupling,varied energy roles,and energy supply and demand dynamics.The systemmodel is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously.To strike a balance between optimality and feasibility,renewable energy resources are modeled with considerations for forecasting errors,Gaussian distribution,and penalty factors.Furthermore,this study introduces a distributed event-triggered surplus algorithm designed to address the economic dispatch problem by minimizing production costs.Rooted in surplus theory and finite time projection,the algorithm effectively rectifies network imbalances caused by directed graphs and addresses local inequality constraints.The algorithm greatly reduces the communication burden through event triggering mechanism.Finally,both theoretical proofs and numerical simulations verify the convergence and event-triggered nature of the algorithm.展开更多
Penetration of Distributed Renewable Energy in active distribution network has increased year by year, and the distributed characteristics of active distribution network has become increasingly prominent;it is difficu...Penetration of Distributed Renewable Energy in active distribution network has increased year by year, and the distributed characteristics of active distribution network has become increasingly prominent;it is difficult for traditional centralized energy scheduling to solve the coordination of random output of distributed energy and the communication pressure of a large number of distributed data. In this paper, we propose a Distributed Renewable Energy Coordination Strategy based on price guidance, through hierarchical multi-agent model. The coordination model of each agent is introduced in detail, regional target, price coordination response strategy and regional security constraints, using Agent’s Distributed Autonomy and Global Collaboration to realize the Energy Balance of Active Distribution Network and promote the Storage of Distributed Renewable Energy;the coordination strategy focuses on the impact of price adjustment on energy storage and flexible load response capacity to improve the distributed renewable energy consumption. Finally, through the quantitative analysis of the comprehensive performance of the index, the evaluation results of the traditional sequential simulation method are compared, and the rationality and validity of the proposed method are verified.展开更多
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...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.展开更多
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 par...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.展开更多
基金funded by the National Natural Science Foundation of China(52167013)the Key Program of Natural Science Foundation of Gansu Province(24JRRA225)Natural Science Foundation of Gansu Province(23JRRA891).
文摘After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and utilized.This change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized approach.At the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy resources.The effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and sustainability.This allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy management.However,there is still no extensive implementation of such sharing models in today’s electricitymarkets.Research on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading market.This paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.
基金supported by the Science and Technology Project of State Grid Sichuan Electric Power Company Chengdu Power Supply Company under Grant No.521904240005.
文摘This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards greater decentralization and renewable integration,traditional optimization methods struggle to address the inherent complexities and uncertainties.Our proposed MARL framework enables adaptive,decentralized decision-making for both the distribution system operator and individual VPPs,optimizing economic efficiency while maintaining grid stability.We formulate the problem as a Markov decision process and develop a custom MARL algorithm that leverages actor-critic architectures and experience replay.Extensive simulations across diverse scenarios demonstrate that our approach consistently outperforms baseline methods,including Stackelberg game models and model predictive control,achieving an 18.73%reduction in costs and a 22.46%increase in VPP profits.The MARL framework shows particular strength in scenarios with high renewable energy penetration,where it improves system performance by 11.95%compared with traditional methods.Furthermore,our approach demonstrates superior adaptability to unexpected events and mis-predictions,highlighting its potential for real-world implementation.
文摘The construction of island power grids is a systematic engineering task.To ensure the safe operation of power grid systems,optimizing the line layout of island power grids is crucial.Especially in the current context of large-scale distributed renewable energy integration into the power grid,conventional island power grid line layouts can no longer meet actual demands.It is necessary to combine the operational characteristics of island power systems and historical load data to perform load forecasting,thereby generating power grid line layout paths.This article focuses on large-scale distributed renewable energy integration,summarizing optimization strategies for island power grid line layouts,and providing a solid guarantee for the safe and stable operation of island power systems.
基金Supported by the National Natural Science Foundation of China(No.U24B20156)the National Defense Basic Scientific Research Program of China(No.JCKY2021204B051)the National Laboratory of Space Intelligent Control of China(Nos.HTKJ2023KL502005 and HTKJ2024KL502007)。
文摘A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncertainties of renewable energy sources(RESs)is constructed without requiring the full distribution knowledge of the uncertainties.The power balance chance constraint is reformulated within the framework of the distributionally robust optimization(DRO)approach.With the exchange of information and energy flow,each microgrid can achieve its local supply-demand balance.Furthermore,the closed-loop stability and recursive feasibility of the proposed algorithm are proved.The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.
基金The National Natural Science Foundation of China(No.51377021)the Science and Technology Project of State Grid Corporation of China(No.SGTJDK00DWJS1600014)
文摘To integrate different renewable energy resources effectively in a microgrid, a configuration optimization model of a multi-energy distributed generation（DG） system and its auxiliary equipment is proposed. The model mainly consists of two parts, the determination of initial configuration schemes according to user preference and the selection of the optimal scheme. The comprehensive evaluation index（CEI）, which is acquired through the analytic hierarchy process（AHP） weight calculation method, is adopted as the evaluation criterion to rank the initial schemes. The optimal scheme is obtained according to the ranking results. The proposed model takes the diversity of different equipment parameters and investment cost into consideration and can give relatively suitable and economical suggestions for system configuration.Additionally, unlike Homer Pro, the proposed model considers the complementation of different renewable energy resources, and thus the rationality of the multi-energy DG system is improved compared with the single evaluation criterion method which only considers the total cost.
基金This work has been partly supported by National Natural Science Foundation of China，National High Technology Research and Development Program of China (863 Program)
文摘Device-to-Device(D2D) communication has been proposed as a promising implementation of green communication to benefit the existed cellular network.In order to limit cross-tier interference while explore the gain of short-range communication,we devise a series of distributed power control(DPC) schemes for energy conservation(EC)and enhancement of radio resource utilization in the hybrid system.Firstly,a constrained opportunistic power control model is built up to take advantage of the interference avoidance methodology in the presence of service requirement and power constraint.Then,biasing scheme and admission control are added to evade ineffective power consumption and maintain the feasibility of the system.Upon feasibility,a non-cooperative game is further formulated to exploit the profit in EC with minor influence on spectral efficiency(SE).The convergence of the DPC schemes is validated and their performance is confirmed via simulation results.
文摘Under the Kyoto Protocol,Japanwas supposed to reduce six percent of the green house gas (GHG) emission in 2012. However, until the year 2010, the statistics suggested that the GHG emission increased 4.2%. What is more challenge is, afterFukushimacrisis, without the nuclear energy,Japanmay produce about 15 percent more GHG emissions than1990 inthis fiscal year. It still has to struggle to meet the target set by Kyoto Protocol. The demonstration area of “smart community” suggests Japanese exploration for new low carbon strategies. The study proposed a demand side response energy system, a dynamic tree-like hierarchical model for smart community. The model not only conveyed the concept of smart grid, but also built up a smart heat energy supply chain by offline heat transport system. Further, this model promoted a collaborative energy utilization mode between the industrial sector and the civil sector. In addition, the research chose the smart community inKitakyushuas case study and executed the model. The simulation and the analysis of the model not only evaluate the environmental effect of different technologies but also suggest that the smart community inJapanhas the potential but not easy to achieve the target, cut down 50% of the CO2 emission.
基金supported by National Key Research and Development Program of China(No.2016YFB0900100)Sate Grid of China(Research on the development potential evaluation of distributed generation and its management and control and operation optimization technology under scaleup development stage.No.1400-201927279A-0-0-00)
文摘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.
基金supported by The National Key R&D Program of China(2020YFB0905900):Research on artificial intelligence application of power internet of things.
文摘The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.
基金supported by National Natural Science Foundation of China (No.U1766201)the State Grid Science and Technology Project (Title: Research on China’s New Energy Resources & Development Roadmap)
文摘Global renewable energy has maintained a steady growth in recent years, mainly fostered by national policies and increasing demand. Analyzing the experience of renewable energy development in developed countries can be important to provide reference and guidance for its adoption in other countries. First, we compare and summarize definitions of distributed generation from 18 leading countries and organizations in renewable energy. On this basis, we provide three basic characteristics for successful distributed generation using renewable resources. Then, we empirically analyze the distributed and centralized development of renewable energy in Germany with focus on wind and photovoltaic power. We determined that 95% of the photovoltaic generation and 85% of the wind power generation is distributed in Germany, suggesting that the most suitable generation mode for renewable energy is the distributed approach.
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.
基金supported in part by the National Natural Science Foundation of China under Grant 62001056, 61925101, U21A20444in part by the Fundamental Research Funds for the Central Universities under Grant 500421336 and Grant 505021163。
文摘With the rapid increasing of maritime activities, maritime wireless networks(MWNs) with high reliability, high energy efficiency, and low delay are required. However, the centralized networking with fixed resource scheduling is not suitable for MWNs due to the special environment. In this paper,we introduce the collaborative relay communication in distributed MWNs to improve the link reliability, and propose an orthogonal time-frequency resource block reservation based multiple access(RRMA) scheme for both one-hop direct link and two-hop collaborative relay link to reduce the interference. To further improve the network performance, we formulate an energy efficiency(EE) maximization resource allocation problem and solve it by an iterative algorithm based on the Dinkelbach method. Finally, numerical results are provided to investigate the proposed RRMA scheme and resource allocation algorithm, showing that the low outage probability and transmission delay can be attained by the proposed RRMA scheme. Moreover,the proposed resource allocation algorithm is capable of achieving high EE in distributed MWNs.
基金supported by the State Grid Corporation of China Science and Technological Project(Research and demonstration application of key technology of energy storage cloud for mobile energy storage application of electric vehicles 5419-20197121 7a-0-0-00)
文摘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.
文摘Highly penetration of Distributed Energy Resources (DER) on the grid systems nowadays makes the systems grow dynamically. The system become more complex and the protection system become more complicated. The protection relay should accommodate the system changes according to the system conditions and topologies. As part of developmental aspect of Distributed Artificial Intelligent, Multi Agent System (MAS) is a challenging method for improving the intelligent properties of relay protection. This paper introduces the use of MAS approach on radial distribution system protection dominated with DER using dispersed adaptive rule-based protection supported by distributed database agent. The simulation results confirmed that the proposed algorithm can respond within 15.05 ms.
基金Projects(51676209,22008265)supported by the National Natural Science Foundation of ChinaProjects(2020JJ6072,2021JJ50007)supported by the Hunan Province Natural Science Foundation,China。
文摘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.
基金This work has been supported by the National Key R&D Program of China(Grant No.2018YFE0207600)EPSRC Research Grant(EP/K033700/1,EP/K033166/1)+2 种基金the Natural Science Foundation of China(61671046,61911530216,U1834210)the Beijing Natural Science Foundation(4182050)the FWO(Grants G0A2617N and G093817N).
文摘This paper advocates the use of the distributed compressed sensing(DCS)paradigm to deploy energy harvesting(EH)Internet of Thing(IoT)devices for energy self-sustainability.We consider networks with signal/energy models that capture the fact that both the collected signals and the harvested energy of different devices can exhibit correlation.We provide theoretical analysis on the performance of both the classical compressive sensing(CS)approach and the proposed distributed CS(DCS)-based approach to data acquisition for EH IoT.Moreover,we perform an in-depth comparison of the proposed DCSbased approach against the distributed source coding(DSC)system.These performance characterizations and comparisons embody the effect of various system phenomena and parameters including signal correlation,EH correlation,network size,and energy availability level.Our results unveil that,the proposed approach offers significant increase in data gathering capability with respect to the CS-based approach,and offers a substantial reduction of the mean-squared error distortion with respect to the DSC system.
基金The Science and Technology Project of the State Grid Corporation of China(Research and Demonstration of Loss Reduction Technology Based on Reactive Power Potential Exploration and Excitation of Distributed Photovoltaic-Energy Storage Converters:5400-202333241A-1-1-ZN).
文摘This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices.This method integrates features including photovoltaic(PV)systems,energy storage coupling,varied energy roles,and energy supply and demand dynamics.The systemmodel is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously.To strike a balance between optimality and feasibility,renewable energy resources are modeled with considerations for forecasting errors,Gaussian distribution,and penalty factors.Furthermore,this study introduces a distributed event-triggered surplus algorithm designed to address the economic dispatch problem by minimizing production costs.Rooted in surplus theory and finite time projection,the algorithm effectively rectifies network imbalances caused by directed graphs and addresses local inequality constraints.The algorithm greatly reduces the communication burden through event triggering mechanism.Finally,both theoretical proofs and numerical simulations verify the convergence and event-triggered nature of the algorithm.
文摘Penetration of Distributed Renewable Energy in active distribution network has increased year by year, and the distributed characteristics of active distribution network has become increasingly prominent;it is difficult for traditional centralized energy scheduling to solve the coordination of random output of distributed energy and the communication pressure of a large number of distributed data. In this paper, we propose a Distributed Renewable Energy Coordination Strategy based on price guidance, through hierarchical multi-agent model. The coordination model of each agent is introduced in detail, regional target, price coordination response strategy and regional security constraints, using Agent’s Distributed Autonomy and Global Collaboration to realize the Energy Balance of Active Distribution Network and promote the Storage of Distributed Renewable Energy;the coordination strategy focuses on the impact of price adjustment on energy storage and flexible load response capacity to improve the distributed renewable energy consumption. Finally, through the quantitative analysis of the comprehensive performance of the index, the evaluation results of the traditional sequential simulation method are compared, and the rationality and validity of the proposed method are verified.
基金supported by the Shanghai Municipal Social Science Foundation(No.2020BGL032).
文摘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.
基金the National Nat-ural Science Foundation of China(Nos.52074029,51804026)the USTB-NTUT Joint Research Program(No.06310063)Chuan Wang would like to acknowledge the funding support from Vinnova(dnr:2017-01327).
文摘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.
