The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.Wh...The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.While the DR market offers the load aggregator(LA)additional profitable opportunities beyond the electricity spot market,it also introduces new trading risks due to the significant uncertainty in users’behaviors.Dispatching energy storage systems(ESSs)is an effective means to enhance the risk management capabilities of LAs;however,coordinating ESS operations with dual-market trading strategies remains an urgent challenge.To this end,this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market,which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market.First,the intrinsic coupling characteristics of the LA participating in the dual market are analyzed,and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed.Second,an uncertain user response model is developed based on price‒response mechanisms,and actual market settlement rules accounting for under-and over-responses are employed to calculate trading revenues,where possible revenue losses are quantified via conditional value at risk.Third,by imposing these terms and the capacity allocation mechanism of ESS,the risk-aware stochastic coordinated trading model of the LA is built,where the bidding and pricing strategies in the dual model that trade off risk and profit are derived.The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.展开更多
Pressure has been introduced into power systems owing to the intermittent and uncertain nature of renewable energy.As a result,energy resource aggregators are emerging in the electricity market to realize sustainable ...Pressure has been introduced into power systems owing to the intermittent and uncertain nature of renewable energy.As a result,energy resource aggregators are emerging in the electricity market to realize sustainable and economic advantages through distributed generation,energy storage,and demand response resources.However,resource aggregators face the challenge of dealing with the uncertainty of renewable energy generation and setting appropriate incentives to exploit substantial energy flexibility in the building sector.In this study,a risk-aware optimal dispatch strategy that integrates probabilistic renewable energy prediction and bi-level building flexibility engagements is proposed.A natural gradient boosting algorithm(NGBoost),which requires no prior knowledge of uncertain variables,was adopted to develop a probabilistic photovoltaic(PV)forecasting model.The lack of suitable flexibility incentives is addressed by a novel interactive flexibility engagement scheme that can take into account building users'willingness and optimize the building flexibility provision.The chance-constrained programming method was applied to manage the supply-demand balance of the resource aggregator and ensure risk-aware decision-making in power dispatch.The case study results show the strong economic and environmental performance of the proposed strategy.The proposed strategy leads to a win-win situation in which profit increases through a load reduction of 13% and a carbon emission reduction of 3% is achieved for different stakeholders,which also shows a trade-off between the economic benefits and the risk of supply shortage.展开更多
With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this prob...With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.展开更多
Forested areas are extremely vulnerable to disasters leading to environmental destruction.Forest Fire is one among them which requires immediate attention.There are lot of works done by authors where Wireless Sensors ...Forested areas are extremely vulnerable to disasters leading to environmental destruction.Forest Fire is one among them which requires immediate attention.There are lot of works done by authors where Wireless Sensors and IoT have been used for forest fire monitoring.So,towards monitoring the forest fire and managing the energy efficiently in IoT,Energy Efficient Routing Protocol for Low power lossy networks(E-RPL)was developed.There were challenges about the scalability of the network resulting in a large end-to-end delay and less packet delivery which led to the development of Aggregator-based Energy Efficient RPL with Data Compression(CAAERPL).Though CAA-ERPL proved effective in terms of reduced packet delivery,less energy consumption,and increased packet delivery ratio for varying number of nodes,there is still challenge in the selection of aggregator which is based purely on probability percentage of nodes.There has been research work where fuzzy logic been employed for Mobile Ad-hoc Routing,RPL routing and cluster head selection in Wireless Sensor.There has been no work where fuzzy logic is employed for aggregator selection in Energy Efficient RPL.So accordingly,we here have proposed Fuzzy Based Aggregator selection in Energy-efficient RPL for region thereby forming DODAG for communicating to Fog/Edge.We here have developed fuzzy inference rules for selecting the aggregator based on strength which takes residual power,Node degree,and Expected Transmission Count(ETX)as input metrics.The Fuzzy Aggregator Energy Efficient RPL(FA-ERPL)based on fuzzy inference rules were analysed against E-RPL in terms of scalability(First and Half Node die),Energy Consumption,and aggregator node energy deviation.From the analysis,it was found that FA-ERPL performed better than E-RPL.These were simulated using MATLAB and results.展开更多
There is uncertainty in the electricity price of spot electricity market,which makes load aggregators undertake price risks for their agent users.In order to allow load aggregators to reduce the spot market price risk...There is uncertainty in the electricity price of spot electricity market,which makes load aggregators undertake price risks for their agent users.In order to allow load aggregators to reduce the spot market price risk,scholars have proposed many solutions,such as improving the declaration decision-making model,signing power mutual insurance contracts,and adding energy storage and mobilizing demand-side resources to respond.In terms of demand side,calling flexible demand-side resources can be considered as a key solution.The user’s power consumption rights(PCRs)are core contents of the demand-side resources.However,there have been few studies on the pricing of PCR contracts and transaction decisions to solve the problem of price forecast deviation and to manage the uncertainty of spot market prices.In addition,in traditional PCR contracts,PCRs are mostly priced using a single price mechanism,that is,the power user is compensated for part of the electricity that was interrupted or reduced in power supply.However,some power users might engage in speculative behaviours under this mechanism.Further,for load aggregators,their price risk avoidance ability has not substantially improved.As a financial derivative,options can solve the above problems.In this article,firstly,the option method is used to build an option pricing optimization model for power consumption right contracts that can calculate the optimal option premium and strike price of option contracts of power consumption rights.Secondly,from the perspective of power users and load aggregators,a simulation model of power consumption right transaction decision-making is constructed.The results of calculation examples show that(1)Under the model in this article,the pricing of option contracts for power consumption rights with better risk aversion capabilities than traditional compensation contracts can be obtained.(2)The decision to sell or purchase the power consumption rights will converge at respective highvalue periods,and option contracts will expedite the process.(3)Option contracts can significantly reduce the loss caused by the uncertainty of spot electricity prices for load aggregators without reducing users’willingness to sell power consumption rights.展开更多
The paper proposes a model for a micro-grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model ta...The paper proposes a model for a micro-grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model takes the form of a mixed-integer linear programming model. This model is solved using the CPLEX solver via GAMS by having a consistent data set.展开更多
The proliferation of electric vehicles(EVs)introduces transformative opportunities and challenges for the stability of distribution networks.Unregulated EV charging will further exacerbate the inherent three-phase imb...The proliferation of electric vehicles(EVs)introduces transformative opportunities and challenges for the stability of distribution networks.Unregulated EV charging will further exacerbate the inherent three-phase imbalance of the power grid,while regulated EV charging will alleviate such imbalance.To systematically address this challenge,this study proposes a two-stage bidding strategy with dispatch potential of electric vehicle aggregators(EVAs).By constructing a coordinated framework that integrates the day-ahead and real-time markets,the proposed two-stage bidding strategy reconfigures distributed EVA clusters into a controllable dynamic energy storage system,with a particular focus on dynamic compensation for deviations between scheduled and real-time operations.A bilevel Stackelberg game resolves three-phase imbalance by achieving Nash equilibrium for inter-phase balance,with Karush-Kuhn-Tucker(KKT)conditions and mixed-integer secondorder cone programming(MISOCP)ensuring feasible solutions.The proposed coordinated framework is validated with different bidding modes includes independent bidding,full price acceptance,and cooperative bidding modes.The proposed twostage bidding strategy provides an EVA-based coordinated scheduling solution that balances the economic efficiency and phase stability in electricity market.展开更多
The increasing number of photovoltaic(PV)generation and electric vehicles(EVs)on the load side has necessitated an aggregator(Agg)in power system operation.In this paper,an Agg is used to manage the energy profiles of...The increasing number of photovoltaic(PV)generation and electric vehicles(EVs)on the load side has necessitated an aggregator(Agg)in power system operation.In this paper,an Agg is used to manage the energy profiles of PV generation and EVs.However,the daily management of the Agg is challenged by uncertain PV fluctuations.To address this problem,a robust multi-time scale energy management strategy for the Agg is proposed.In a day-ahead phase,robust optimization is developed to determine the power schedule.In a real-time phase,a rolling horizon-based convex optimization model is established to track the day-ahead power schedule based on the flexibilities of the EVs.A case study indicates a good scheduling performance under an uncertain PV output.Through the convexification,the solving efficiency of the real-time operation model is improved,and the over-charging and over-discharging problems of EVs can be suppressed to a certain extent.Moreover,the power deviation between day-ahead and real-time scheduling is controllable when the EV dispatching capacity is sufficient.The strategy can ensure the flexibility of the Agg for real-time operation.展开更多
Distributed energy resources(DERs),including photovoltaic(PV)systems,small wind turbines,and energy storage systems(ESSs)are being increasingly installed in many residential units and the industry sector at large.DER ...Distributed energy resources(DERs),including photovoltaic(PV)systems,small wind turbines,and energy storage systems(ESSs)are being increasingly installed in many residential units and the industry sector at large.DER installations in apartment buildings,however,pose a more complex issue particularly in the context of property ownership and the distribution of DR benefits.In this paper,a novel aggregator service is proposed to provide centralized management services for residents and DER asset owners in apartment buildings.The proposed service consists of a business model for billing and benefits distribution,and a model predictive control(MPC)control algorithm for managing and optimizing DER operations.Both physical and communication structures are proposed to ensure the implementation of such aggregator services for buildings.Three billing tariffs,i.e.,flat rate,time-of-use(TOU),and real time pricing(RTP)are compared by way of case studies.The results indicate that the proposed aggregator service is compatible with the business model.It is shown to offer good performance in load shifting,bill savings,and energy trading of DERs.Overall,the aggregator service is expected to provide benefits in reducing the pay back periods of the investment.展开更多
The increase in global electricity consumption has made energy efficiency a priority for governments.Consequently,there has been a focus on the efficient integration of a massive penetration of electric vehicles(EVs)i...The increase in global electricity consumption has made energy efficiency a priority for governments.Consequently,there has been a focus on the efficient integration of a massive penetration of electric vehicles(EVs)into energy markets.This study presents an assessment of various strategies for EV aggregators.In this analysis,the smart charging methodology proposed in a previous study is considered.The smart charging technique employs charging power rate modulation and considers user preferences.To adopt several strategies,this study simulates the effect of these actions in a case study of a distribution system from the city of Quito,Ecuador.Different actions are simulated,and the EV aggregator costs and technical conditions are evaluated.展开更多
In power market environment,the growing importance of demand response(DR)and renewable energy source(RES)attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.Meanwhile,th...In power market environment,the growing importance of demand response(DR)and renewable energy source(RES)attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.Meanwhile,the intermittent natures of these alternative sources along with the competition add to the probable financial risk of the aggregators.The objective of the paper is to highlight this financial risk of aggregators in such uncertain environment while estimating DR magnitude and power generated by RES.This work develops DR modeling incorporating the effect of estimating power at different confidence levels and uncertain participation of customers.In this paper,two well-known risk assessment techniques,value at risk and conditional value at risk,are applied to predict the power from RES and DR programs at a particular level of risk in different scenarios generated by Monte Carlo method.To establish the linkage between financial risk taking ability of individuals,the aggregators are classified into risk neutral aggregator,risk averse aggregator and risk taking aggregator.The paper uses data from Indian Energy Exchange to produce realistic results and refers certain policies of Indian Energy Exchange to frame mathematical expressions for benefit function considering uncertainties for each type of three aggregators.Extensive results show the importance of assessing the risks involved with two unpredictable variables and possible impacts on technical and financial attributes of the microgrid energy market.展开更多
This paper addresses a two-stage stochastic-robust model for the day-ahead self-scheduling problem of an aggrega-tor considering uncertainties.The aggregator,which integrates power and capacity of small-scale prosumer...This paper addresses a two-stage stochastic-robust model for the day-ahead self-scheduling problem of an aggrega-tor considering uncertainties.The aggregator,which integrates power and capacity of small-scale prosumers and flex-ible community-owned devices,trades electric energy in the day-ahead(DAM)and real-time energy markets(RTM),and trades reserve capacity and deployment in the reserve capacity(RCM)and reserve deployment markets(RDM).The ability of the aggregator providing reserve service is constrained by the regulations of reserve market rules,including minimum offer/bid size and minimum delivery duration.A combination approach of stochastic program-ming(SP)and robust optimization(RO)is used to model different kinds of uncertainties,including those of market price,power/demand and reserve deployment.The risk management of the aggregator is considered through con-ditional value at risk(CVaR)and fluctuation intervals of the uncertain parameters.Case studies numerically show the economic revenue and the energy-reserve schedule of the aggregator with participation in different markets,reserve regulations,and risk preferences.展开更多
Demand response(DR)has received much attention for its ability to balance the changing power supply and demand with flexibility.DR aggregators play an important role in aggregating flexible loads that are too small to...Demand response(DR)has received much attention for its ability to balance the changing power supply and demand with flexibility.DR aggregators play an important role in aggregating flexible loads that are too small to participate in electricity markets.In this work,a DR operation framework is presented to enable local management of customers to participate in electricity market.A novel optimization model is proposed for the DR aggregator with multiple objectives.On one hand,it attempts to obtain the optimal design of different DR contracts as well as the portfolio management so that the DR aggregator can maximize its profit.On the other hand,the customers’welfare should be maximized to incentivize users to enroll in DR programs which ensure the effective and flexible load control.The consumer psychology is introduced to model the consumers’behavior during contract signing.Several simulation studies are performed to demonstrate the feasibility of the proposed model.The results illustrate that the proposed model can ensure the profit of the DR aggregator whereas the customers’welfare is considered.展开更多
With the rapid integration of distributed energy resources(DERs),distribution utilities are faced with new and unprecedented issues.New challenges introduced by high penetra-tion of DERs range from poor observability ...With the rapid integration of distributed energy resources(DERs),distribution utilities are faced with new and unprecedented issues.New challenges introduced by high penetra-tion of DERs range from poor observability to overload and reverse power flow problems,under-/over-voltages,maloperation of legacy protection systems,and requirements for new planning procedures.Distribution utility personnel are not adequately trained,and legacy control centers are not properly equipped to cope with these issues.Fortunately,distribution energy resource management systems(DERMSs)are emerging software technologies aimed to provide distribution system operators(DSOs)with a specialized set of tools to enable them to overcome the issues caused by DERs and to maximize the benefits of the presence of high penetration of these novel resources.However,as DERMS technology is still emerging,its definition is vague and can refer to very different levels of software hierarchies,spanning from decentralized virtual power plants to DER aggregators and fully centralized enterprise systems(called utility DERMS).Although they are all frequently simply called DERIMS,these software technologies have different sets of tools and aim to provide different services to different stakeholders.This paper explores how these different software technologies can complement each other,and how they can provide significant benefits to DSOs in enabling them to successfully manage evolving distribution networks with high penetration of DERs when they are integrated together into the control centers of distribution utilities.展开更多
This paper investigates the impact of electric vehicle(EV)aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control(LFC)system.Primarily,a graphi...This paper investigates the impact of electric vehicle(EV)aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control(LFC)system.Primarily,a graphical method characterizing stability boundary locus is implemented.For a given time delay,the method computes all the stabilizing proportional-integral(PI)controller gains,which constitutes a stability region in the parameter space of PI controller.Secondly,in order to complement the stability regions,a frequency-domain exact method is used to calculate stability delay margins for various values of PI controller gains.The qualitative impact of EV aggregator on both stability regions and stability delay margins is thoroughly analyzed and the results are authenticated by time-domain simulations and quasi-polynomial mapping-based root finder(QPmR)algorithm.展开更多
Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly ...Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly participating in day-ahead scheduling to support demand response.The first stage is on the profit of aggregators and peak load of the grid.The line loss and voltage deviation of regulation are considered to ensure stable operation of the power grid at the second stage,which guarantees the fairness of the regulation and the comfort of users.A single tempera-ture adjustment strategy is used to control TCLs to maximize the response potential in the third stage.Finally,digital simulation based on the IEEE 33-bus distribution network system proves that the proposed three-stage scheduling strategy can keep the voltage deviation within±5%in different situations.In addition,the Gini coefficient of distribu-tion increases by 20%and the predicted percentage of dissatisfied is 48%lower than those without distribution.展开更多
The uncertainty of user-side resource response will affect the response quality and economic benefit of load aggregator(LA).Therefore,this paper regards the flexible user-side resources as a virtual energy storage(VES...The uncertainty of user-side resource response will affect the response quality and economic benefit of load aggregator(LA).Therefore,this paper regards the flexible user-side resources as a virtual energy storage(VES),and uses the traditional narrow sense energy storage(NSES)to alleviate the uncertainty of VES.In order to further enhance the competitive advantage of LA in electricity market transactions,the operation mechanism of LA in day-ahead and real-time market is analyzed,respectively.Besides,truncated normal distribution is used to simulate the response accuracy of VES,and the response model of NSES is constructed at the same time.Then,the hierarchical market access index(HMAI)is introduced to quantify the risk of LA being eliminated in the market competition.Finally,combined with the priority response strategy of VES and HMAI,the capacity allocation model of NSES is established.As the capacity model is nonlinear,Monte Carlo simulation and adaptive particle swarm optimization algorithm are used to solve it.In order to verify the effectiveness of the model,the data from PJM market in the United States is used for testing.Simulation results show that the model established can provide the effective NSES capacity allocation strategy for LA to compensate the uncertainty of VES response,and the economic benefit of LA can be increased by 52.2%at its maximum.Through the reasonable NSES capacity allocation,LA is encouraged to improve its own resource level,thus forming a virtuous circle of market competition.展开更多
In this paper we present a designated verifier-set signature(DVSS),in which the signer allows to designate many verifiers rather than one verifier,and each designated verifier can verify the validity of signature by h...In this paper we present a designated verifier-set signature(DVSS),in which the signer allows to designate many verifiers rather than one verifier,and each designated verifier can verify the validity of signature by himself.Our research starts from identity-based aggregator(IBA)that compresses a designated set of verifier’s identities to a constant-size random string in cryptographic space.The IBA is constructed by mapping the hash of verifier’s identity into zero or pole of a target curve,and extracting one curve’s point as the result of aggregation according to a specific secret.Considering the different types of target curves,these two IBAs are called as zeros-based aggregator and poles-based aggregator,respectively.Based on them,we propose a practical DVSS scheme constructed from the zero-pole cancellation method which can eliminate the same elements between zeros-based aggregator and poles-based aggregator.Due to this design,our DVSS scheme has some distinct advantages:(1)the signature supporting arbitrary dynamic verifiers extracted from a large number of users;and(2)the signature with short and constant length.We rigorously prove that our DVSS scheme satisfies the security properties:correctness,consistency,unforgeability and exclusivity.This is a preview of subscription content,log in to check access.展开更多
Protein aggregates,mitochondrial import stress and neurodegenerative disorders:A salient hallmark of several neurodegenerative diseases,including Parkinson’s disease,is the abundance of protein aggregates(Goiran et a...Protein aggregates,mitochondrial import stress and neurodegenerative disorders:A salient hallmark of several neurodegenerative diseases,including Parkinson’s disease,is the abundance of protein aggregates(Goiran et al.,2022).This molecular event is believed to lead to activation of stress pathways ultimately resulting in cellular dysfunction(Eldeeb et al.,2022).Accordingly,many lines of research investigations focused on dampening the formation of protein aggregates or augmenting the clearance of protein aggregates as a potential therapeutic strategy to counteract the progression of neurodegenerative diseases,albeit with little success(Costa-Mattioli and Walter,2020).Cell stress cues such as the accumulation of protein aggregates lead to the activation of stress response pathways that aid cells in responding to the damage.Despite the notion that the transient activation of these pathways helps cells cope with stressors,persistent activation can induce unwanted apoptosis of cells and reduce overall tissue strength as well as lead to an accumulation of aggregation-prone proteins(Hetz and Papa,2018).Mutations in proteins involved in stress signaling termination can cause conditions like ataxia and early-onset dementia(Conroy et al.,2014).Therefore,it is crucial for stress response signaling to be turned off once conditions have improved.Nevertheless,the mechanisms by which cells silence these signals are still elusive.展开更多
We investigated the effects of fly ash(FA)content on the mechanical properties of recycled aggregate concrete(RAC)and its regeneration potential under freeze and thaw(F-T)cycles.The physical properties of second-gener...We investigated the effects of fly ash(FA)content on the mechanical properties of recycled aggregate concrete(RAC)and its regeneration potential under freeze and thaw(F-T)cycles.The physical properties of second-generation recycled concrete aggregates(RCA)were used to analyze the regeneration potential of RAC after F-T cycles.Scanning electron microscopy was used to study the interfacial transition zone microstructure of RAC after F-T cycles.Results showed that adding 20%FA to RAC significantly enhanced its mechanical properties and frost resistance.Before the F-T cycles,the compressive strength of RAC with 20%FA reached 48.3 MPa,exceeding research strength target of 40 MPa.A majority of second-generation RCA with FA had been verified to attain class Ⅲ,which enabled their practical application in non-structural projects such as backfill trenches and road pavement.However,the second-generation RCA with 20%FA can achieve class Ⅱ,making it ideal for 40 MPa structural concrete.展开更多
基金supported by National Natural Science Foundation of China(52407126).
文摘The demand response(DR)market,as a vital complement to the electricity spot market,plays a key role in evoking user-side regulation capability to mitigate system-level supply‒demand imbalances during extreme events.While the DR market offers the load aggregator(LA)additional profitable opportunities beyond the electricity spot market,it also introduces new trading risks due to the significant uncertainty in users’behaviors.Dispatching energy storage systems(ESSs)is an effective means to enhance the risk management capabilities of LAs;however,coordinating ESS operations with dual-market trading strategies remains an urgent challenge.To this end,this paper proposes a novel systematic risk-aware coordinated trading model for the LA in concurrently participating in the day-ahead electricity spot market and DR market,which incorporates the capacity allocation mechanism of ESS based on market clearing rules to jointly formulate bidding and pricing decisions for the dual market.First,the intrinsic coupling characteristics of the LA participating in the dual market are analyzed,and a joint optimization framework for formulating bidding and pricing strategies that integrates ESS facilities is proposed.Second,an uncertain user response model is developed based on price‒response mechanisms,and actual market settlement rules accounting for under-and over-responses are employed to calculate trading revenues,where possible revenue losses are quantified via conditional value at risk.Third,by imposing these terms and the capacity allocation mechanism of ESS,the risk-aware stochastic coordinated trading model of the LA is built,where the bidding and pricing strategies in the dual model that trade off risk and profit are derived.The simulation results of a case study validate the effectiveness of the proposed trading strategy in controlling trading risk and improving the trading income of the LA.
基金financially supported by the Collaborative Research Fund(C5018-20GF)of the Research Grant Council(RGC)of Hong Kong Special Administrative Regionthe Shenzhen Science and Technology Innovation Commission Grant(KCXST20221021111203007)。
文摘Pressure has been introduced into power systems owing to the intermittent and uncertain nature of renewable energy.As a result,energy resource aggregators are emerging in the electricity market to realize sustainable and economic advantages through distributed generation,energy storage,and demand response resources.However,resource aggregators face the challenge of dealing with the uncertainty of renewable energy generation and setting appropriate incentives to exploit substantial energy flexibility in the building sector.In this study,a risk-aware optimal dispatch strategy that integrates probabilistic renewable energy prediction and bi-level building flexibility engagements is proposed.A natural gradient boosting algorithm(NGBoost),which requires no prior knowledge of uncertain variables,was adopted to develop a probabilistic photovoltaic(PV)forecasting model.The lack of suitable flexibility incentives is addressed by a novel interactive flexibility engagement scheme that can take into account building users'willingness and optimize the building flexibility provision.The chance-constrained programming method was applied to manage the supply-demand balance of the resource aggregator and ensure risk-aware decision-making in power dispatch.The case study results show the strong economic and environmental performance of the proposed strategy.The proposed strategy leads to a win-win situation in which profit increases through a load reduction of 13% and a carbon emission reduction of 3% is achieved for different stakeholders,which also shows a trade-off between the economic benefits and the risk of supply shortage.
基金supported by the Science and Technology Project from the State Grid Shanghai Municipal Electric Power Company of China (52094019006U)the Shanghai Rising-Star Program (18QB1400200)。
文摘With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.
基金This work is partially funded by FCT/MCTES through national funds and,when applicable,co-funded EU funds under the Project UIDB/50008/2020Ministry of Science and Higher Education of the Russian Federation,Grant 08-08by the Brazilian National Council for Scientific and Technological Development-CNPq,via Grant No.313036/2020-9.
文摘Forested areas are extremely vulnerable to disasters leading to environmental destruction.Forest Fire is one among them which requires immediate attention.There are lot of works done by authors where Wireless Sensors and IoT have been used for forest fire monitoring.So,towards monitoring the forest fire and managing the energy efficiently in IoT,Energy Efficient Routing Protocol for Low power lossy networks(E-RPL)was developed.There were challenges about the scalability of the network resulting in a large end-to-end delay and less packet delivery which led to the development of Aggregator-based Energy Efficient RPL with Data Compression(CAAERPL).Though CAA-ERPL proved effective in terms of reduced packet delivery,less energy consumption,and increased packet delivery ratio for varying number of nodes,there is still challenge in the selection of aggregator which is based purely on probability percentage of nodes.There has been research work where fuzzy logic been employed for Mobile Ad-hoc Routing,RPL routing and cluster head selection in Wireless Sensor.There has been no work where fuzzy logic is employed for aggregator selection in Energy Efficient RPL.So accordingly,we here have proposed Fuzzy Based Aggregator selection in Energy-efficient RPL for region thereby forming DODAG for communicating to Fog/Edge.We here have developed fuzzy inference rules for selecting the aggregator based on strength which takes residual power,Node degree,and Expected Transmission Count(ETX)as input metrics.The Fuzzy Aggregator Energy Efficient RPL(FA-ERPL)based on fuzzy inference rules were analysed against E-RPL in terms of scalability(First and Half Node die),Energy Consumption,and aggregator node energy deviation.From the analysis,it was found that FA-ERPL performed better than E-RPL.These were simulated using MATLAB and results.
基金This research was funded by the National Natural Science Foundation of China,China(Grant No.72174062)the 2018 Key Projects of Philosophy and Social Sciences Research,Ministry of Education,China(Grant No.18JZD032).The completion of this articlewas accomplished with the help of many teachers and classmates.We sincerely thank them for their help and guidance.
文摘There is uncertainty in the electricity price of spot electricity market,which makes load aggregators undertake price risks for their agent users.In order to allow load aggregators to reduce the spot market price risk,scholars have proposed many solutions,such as improving the declaration decision-making model,signing power mutual insurance contracts,and adding energy storage and mobilizing demand-side resources to respond.In terms of demand side,calling flexible demand-side resources can be considered as a key solution.The user’s power consumption rights(PCRs)are core contents of the demand-side resources.However,there have been few studies on the pricing of PCR contracts and transaction decisions to solve the problem of price forecast deviation and to manage the uncertainty of spot market prices.In addition,in traditional PCR contracts,PCRs are mostly priced using a single price mechanism,that is,the power user is compensated for part of the electricity that was interrupted or reduced in power supply.However,some power users might engage in speculative behaviours under this mechanism.Further,for load aggregators,their price risk avoidance ability has not substantially improved.As a financial derivative,options can solve the above problems.In this article,firstly,the option method is used to build an option pricing optimization model for power consumption right contracts that can calculate the optimal option premium and strike price of option contracts of power consumption rights.Secondly,from the perspective of power users and load aggregators,a simulation model of power consumption right transaction decision-making is constructed.The results of calculation examples show that(1)Under the model in this article,the pricing of option contracts for power consumption rights with better risk aversion capabilities than traditional compensation contracts can be obtained.(2)The decision to sell or purchase the power consumption rights will converge at respective highvalue periods,and option contracts will expedite the process.(3)Option contracts can significantly reduce the loss caused by the uncertainty of spot electricity prices for load aggregators without reducing users’willingness to sell power consumption rights.
文摘The paper proposes a model for a micro-grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model takes the form of a mixed-integer linear programming model. This model is solved using the CPLEX solver via GAMS by having a consistent data set.
基金supported by Science and Technology Project of State Grid Corporation of China(No.5400-202318246A-1-1-ZN)。
文摘The proliferation of electric vehicles(EVs)introduces transformative opportunities and challenges for the stability of distribution networks.Unregulated EV charging will further exacerbate the inherent three-phase imbalance of the power grid,while regulated EV charging will alleviate such imbalance.To systematically address this challenge,this study proposes a two-stage bidding strategy with dispatch potential of electric vehicle aggregators(EVAs).By constructing a coordinated framework that integrates the day-ahead and real-time markets,the proposed two-stage bidding strategy reconfigures distributed EVA clusters into a controllable dynamic energy storage system,with a particular focus on dynamic compensation for deviations between scheduled and real-time operations.A bilevel Stackelberg game resolves three-phase imbalance by achieving Nash equilibrium for inter-phase balance,with Karush-Kuhn-Tucker(KKT)conditions and mixed-integer secondorder cone programming(MISOCP)ensuring feasible solutions.The proposed coordinated framework is validated with different bidding modes includes independent bidding,full price acceptance,and cooperative bidding modes.The proposed twostage bidding strategy provides an EVA-based coordinated scheduling solution that balances the economic efficiency and phase stability in electricity market.
基金supported in part by the National Natural Science Foundation of China(No.51877078)the Fundamental Research Funds for the Central Universities(No.2018MS012)
文摘The increasing number of photovoltaic(PV)generation and electric vehicles(EVs)on the load side has necessitated an aggregator(Agg)in power system operation.In this paper,an Agg is used to manage the energy profiles of PV generation and EVs.However,the daily management of the Agg is challenged by uncertain PV fluctuations.To address this problem,a robust multi-time scale energy management strategy for the Agg is proposed.In a day-ahead phase,robust optimization is developed to determine the power schedule.In a real-time phase,a rolling horizon-based convex optimization model is established to track the day-ahead power schedule based on the flexibilities of the EVs.A case study indicates a good scheduling performance under an uncertain PV output.Through the convexification,the solving efficiency of the real-time operation model is improved,and the over-charging and over-discharging problems of EVs can be suppressed to a certain extent.Moreover,the power deviation between day-ahead and real-time scheduling is controllable when the EV dispatching capacity is sufficient.The strategy can ensure the flexibility of the Agg for real-time operation.
文摘Distributed energy resources(DERs),including photovoltaic(PV)systems,small wind turbines,and energy storage systems(ESSs)are being increasingly installed in many residential units and the industry sector at large.DER installations in apartment buildings,however,pose a more complex issue particularly in the context of property ownership and the distribution of DR benefits.In this paper,a novel aggregator service is proposed to provide centralized management services for residents and DER asset owners in apartment buildings.The proposed service consists of a business model for billing and benefits distribution,and a model predictive control(MPC)control algorithm for managing and optimizing DER operations.Both physical and communication structures are proposed to ensure the implementation of such aggregator services for buildings.Three billing tariffs,i.e.,flat rate,time-of-use(TOU),and real time pricing(RTP)are compared by way of case studies.The results indicate that the proposed aggregator service is compatible with the business model.It is shown to offer good performance in load shifting,bill savings,and energy trading of DERs.Overall,the aggregator service is expected to provide benefits in reducing the pay back periods of the investment.
文摘The increase in global electricity consumption has made energy efficiency a priority for governments.Consequently,there has been a focus on the efficient integration of a massive penetration of electric vehicles(EVs)into energy markets.This study presents an assessment of various strategies for EV aggregators.In this analysis,the smart charging methodology proposed in a previous study is considered.The smart charging technique employs charging power rate modulation and considers user preferences.To adopt several strategies,this study simulates the effect of these actions in a case study of a distribution system from the city of Quito,Ecuador.Different actions are simulated,and the EV aggregator costs and technical conditions are evaluated.
文摘In power market environment,the growing importance of demand response(DR)and renewable energy source(RES)attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.Meanwhile,the intermittent natures of these alternative sources along with the competition add to the probable financial risk of the aggregators.The objective of the paper is to highlight this financial risk of aggregators in such uncertain environment while estimating DR magnitude and power generated by RES.This work develops DR modeling incorporating the effect of estimating power at different confidence levels and uncertain participation of customers.In this paper,two well-known risk assessment techniques,value at risk and conditional value at risk,are applied to predict the power from RES and DR programs at a particular level of risk in different scenarios generated by Monte Carlo method.To establish the linkage between financial risk taking ability of individuals,the aggregators are classified into risk neutral aggregator,risk averse aggregator and risk taking aggregator.The paper uses data from Indian Energy Exchange to produce realistic results and refers certain policies of Indian Energy Exchange to frame mathematical expressions for benefit function considering uncertainties for each type of three aggregators.Extensive results show the importance of assessing the risks involved with two unpredictable variables and possible impacts on technical and financial attributes of the microgrid energy market.
基金supported by National Key Research and Development Project of China under Grant 2018YFB1503000China Scholarship Council.
文摘This paper addresses a two-stage stochastic-robust model for the day-ahead self-scheduling problem of an aggrega-tor considering uncertainties.The aggregator,which integrates power and capacity of small-scale prosumers and flex-ible community-owned devices,trades electric energy in the day-ahead(DAM)and real-time energy markets(RTM),and trades reserve capacity and deployment in the reserve capacity(RCM)and reserve deployment markets(RDM).The ability of the aggregator providing reserve service is constrained by the regulations of reserve market rules,including minimum offer/bid size and minimum delivery duration.A combination approach of stochastic program-ming(SP)and robust optimization(RO)is used to model different kinds of uncertainties,including those of market price,power/demand and reserve deployment.The risk management of the aggregator is considered through con-ditional value at risk(CVaR)and fluctuation intervals of the uncertain parameters.Case studies numerically show the economic revenue and the energy-reserve schedule of the aggregator with participation in different markets,reserve regulations,and risk preferences.
基金supported in part by the National Natural Science Foundation of China(No.51777030)in part by CURENT,a U.S.NSF/DOE Engineering Research Center+1 种基金through NSF under Award EEC-1081477the China Scholarship Council(No.201706090150)。
文摘Demand response(DR)has received much attention for its ability to balance the changing power supply and demand with flexibility.DR aggregators play an important role in aggregating flexible loads that are too small to participate in electricity markets.In this work,a DR operation framework is presented to enable local management of customers to participate in electricity market.A novel optimization model is proposed for the DR aggregator with multiple objectives.On one hand,it attempts to obtain the optimal design of different DR contracts as well as the portfolio management so that the DR aggregator can maximize its profit.On the other hand,the customers’welfare should be maximized to incentivize users to enroll in DR programs which ensure the effective and flexible load control.The consumer psychology is introduced to model the consumers’behavior during contract signing.Several simulation studies are performed to demonstrate the feasibility of the proposed model.The results illustrate that the proposed model can ensure the profit of the DR aggregator whereas the customers’welfare is considered.
基金the U.S.Department of Energy under Contract No.DE-AC36-08GO28308.
文摘With the rapid integration of distributed energy resources(DERs),distribution utilities are faced with new and unprecedented issues.New challenges introduced by high penetra-tion of DERs range from poor observability to overload and reverse power flow problems,under-/over-voltages,maloperation of legacy protection systems,and requirements for new planning procedures.Distribution utility personnel are not adequately trained,and legacy control centers are not properly equipped to cope with these issues.Fortunately,distribution energy resource management systems(DERMSs)are emerging software technologies aimed to provide distribution system operators(DSOs)with a specialized set of tools to enable them to overcome the issues caused by DERs and to maximize the benefits of the presence of high penetration of these novel resources.However,as DERMS technology is still emerging,its definition is vague and can refer to very different levels of software hierarchies,spanning from decentralized virtual power plants to DER aggregators and fully centralized enterprise systems(called utility DERMS).Although they are all frequently simply called DERIMS,these software technologies have different sets of tools and aim to provide different services to different stakeholders.This paper explores how these different software technologies can complement each other,and how they can provide significant benefits to DSOs in enabling them to successfully manage evolving distribution networks with high penetration of DERs when they are integrated together into the control centers of distribution utilities.
基金This work was supported by the Project of Scientific and Technological Research Council of Turkey(TUBITAK)(No.118E744).
文摘This paper investigates the impact of electric vehicle(EV)aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control(LFC)system.Primarily,a graphical method characterizing stability boundary locus is implemented.For a given time delay,the method computes all the stabilizing proportional-integral(PI)controller gains,which constitutes a stability region in the parameter space of PI controller.Secondly,in order to complement the stability regions,a frequency-domain exact method is used to calculate stability delay margins for various values of PI controller gains.The qualitative impact of EV aggregator on both stability regions and stability delay margins is thoroughly analyzed and the results are authenticated by time-domain simulations and quasi-polynomial mapping-based root finder(QPmR)algorithm.
基金supported in part by the National Natural Science Foundation of China(No.52007126 and No.U2166209).
文摘Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly participating in day-ahead scheduling to support demand response.The first stage is on the profit of aggregators and peak load of the grid.The line loss and voltage deviation of regulation are considered to ensure stable operation of the power grid at the second stage,which guarantees the fairness of the regulation and the comfort of users.A single tempera-ture adjustment strategy is used to control TCLs to maximize the response potential in the third stage.Finally,digital simulation based on the IEEE 33-bus distribution network system proves that the proposed three-stage scheduling strategy can keep the voltage deviation within±5%in different situations.In addition,the Gini coefficient of distribu-tion increases by 20%and the predicted percentage of dissatisfied is 48%lower than those without distribution.
基金This work was supported in part by the National Natural Science Foundation of China(No.51777126).
文摘The uncertainty of user-side resource response will affect the response quality and economic benefit of load aggregator(LA).Therefore,this paper regards the flexible user-side resources as a virtual energy storage(VES),and uses the traditional narrow sense energy storage(NSES)to alleviate the uncertainty of VES.In order to further enhance the competitive advantage of LA in electricity market transactions,the operation mechanism of LA in day-ahead and real-time market is analyzed,respectively.Besides,truncated normal distribution is used to simulate the response accuracy of VES,and the response model of NSES is constructed at the same time.Then,the hierarchical market access index(HMAI)is introduced to quantify the risk of LA being eliminated in the market competition.Finally,combined with the priority response strategy of VES and HMAI,the capacity allocation model of NSES is established.As the capacity model is nonlinear,Monte Carlo simulation and adaptive particle swarm optimization algorithm are used to solve it.In order to verify the effectiveness of the model,the data from PJM market in the United States is used for testing.Simulation results show that the model established can provide the effective NSES capacity allocation strategy for LA to compensate the uncertainty of VES response,and the economic benefit of LA can be increased by 52.2%at its maximum.Through the reasonable NSES capacity allocation,LA is encouraged to improve its own resource level,thus forming a virtuous circle of market competition.
基金The work was supported by the National Key Technologies R&D Programs of China(2018YFB1402702 and 2017YFB0802500)the“13th”Five-Year National Cryptographic Development Foundation(MMJJ20180208)+1 种基金NSFC-Genertec Joint Fund For Basic Research(U1636104)the National Natural Science Foundation of China(Grant Nos.61572132,61972032 and U1705264).
文摘In this paper we present a designated verifier-set signature(DVSS),in which the signer allows to designate many verifiers rather than one verifier,and each designated verifier can verify the validity of signature by himself.Our research starts from identity-based aggregator(IBA)that compresses a designated set of verifier’s identities to a constant-size random string in cryptographic space.The IBA is constructed by mapping the hash of verifier’s identity into zero or pole of a target curve,and extracting one curve’s point as the result of aggregation according to a specific secret.Considering the different types of target curves,these two IBAs are called as zeros-based aggregator and poles-based aggregator,respectively.Based on them,we propose a practical DVSS scheme constructed from the zero-pole cancellation method which can eliminate the same elements between zeros-based aggregator and poles-based aggregator.Due to this design,our DVSS scheme has some distinct advantages:(1)the signature supporting arbitrary dynamic verifiers extracted from a large number of users;and(2)the signature with short and constant length.We rigorously prove that our DVSS scheme satisfies the security properties:correctness,consistency,unforgeability and exclusivity.This is a preview of subscription content,log in to check access.
文摘Protein aggregates,mitochondrial import stress and neurodegenerative disorders:A salient hallmark of several neurodegenerative diseases,including Parkinson’s disease,is the abundance of protein aggregates(Goiran et al.,2022).This molecular event is believed to lead to activation of stress pathways ultimately resulting in cellular dysfunction(Eldeeb et al.,2022).Accordingly,many lines of research investigations focused on dampening the formation of protein aggregates or augmenting the clearance of protein aggregates as a potential therapeutic strategy to counteract the progression of neurodegenerative diseases,albeit with little success(Costa-Mattioli and Walter,2020).Cell stress cues such as the accumulation of protein aggregates lead to the activation of stress response pathways that aid cells in responding to the damage.Despite the notion that the transient activation of these pathways helps cells cope with stressors,persistent activation can induce unwanted apoptosis of cells and reduce overall tissue strength as well as lead to an accumulation of aggregation-prone proteins(Hetz and Papa,2018).Mutations in proteins involved in stress signaling termination can cause conditions like ataxia and early-onset dementia(Conroy et al.,2014).Therefore,it is crucial for stress response signaling to be turned off once conditions have improved.Nevertheless,the mechanisms by which cells silence these signals are still elusive.
基金Funded by the Natural Science Foundation of Jiangsu Province(No.BK20220626)the National Natural Science Foundation of China(No.52078068)+2 种基金Science and Technology Innovation Foundation of NIT(No.KCTD006)Jiangsu Marine Structure Service Performance Improvement Engineering Research CenterKey Laboratory of Jiangsu"Marine Floating Wind Power Technology and Equipment"。
文摘We investigated the effects of fly ash(FA)content on the mechanical properties of recycled aggregate concrete(RAC)and its regeneration potential under freeze and thaw(F-T)cycles.The physical properties of second-generation recycled concrete aggregates(RCA)were used to analyze the regeneration potential of RAC after F-T cycles.Scanning electron microscopy was used to study the interfacial transition zone microstructure of RAC after F-T cycles.Results showed that adding 20%FA to RAC significantly enhanced its mechanical properties and frost resistance.Before the F-T cycles,the compressive strength of RAC with 20%FA reached 48.3 MPa,exceeding research strength target of 40 MPa.A majority of second-generation RCA with FA had been verified to attain class Ⅲ,which enabled their practical application in non-structural projects such as backfill trenches and road pavement.However,the second-generation RCA with 20%FA can achieve class Ⅱ,making it ideal for 40 MPa structural concrete.
