This paper reviews recent research on the demand flexibility of residential buildings in regard to definitions,flexible loads,and quantification methods.A systematic distinction of the terminology is made,including th...This paper reviews recent research on the demand flexibility of residential buildings in regard to definitions,flexible loads,and quantification methods.A systematic distinction of the terminology is made,including the demand flexibility,operation flexibility,and energy flexibility of buildings.A comprehensive definition of building demand flexibility is proposed based on an analysis of the existing definitions.Moreover,the flexibility capabilities and operation characteristics of the main residential flexible loads are summarized and compared.Models and evaluation indicators to quantify the flexibility of these flexible loads are reviewed and summarized.Current research gaps and challenges are identified and analyzed as well.The results indicate that previous studies have focused on the flexibility of central air conditioning,electric water heaters,wet appliances,refrigerators,and lighting,where the proportion of studies focusing on each of these subjects is 36.7%,25.7%,14.7%,9.2%,and 8.3%,respectively.These flexible loads are different in running modes,usage frequencies,seasons,and capabilities for shedding,shifting,and modulation,while their response characteristics are not yet clear.Furthermore,recommendations are given for the application of white-,black-,and grey-box models for modeling flexible loads in different situations.Numerous static flexibility evaluation indicators that are based on the aspects of power,temporality,energy,efficiency,economics,and the environment have been proposed in previous publications,but a consensus and standardized evaluation framework is lacking.This review can help readers better understand building demand flexibility and learn about the characteristics of different residential flexible loads,while also providing suggestions for future research on the modeling techniques and evaluation metrics of residential building demand flexibility.展开更多
Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon ...Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon transitions.To address this challenge,this paper proposes an electricity–carbon integratedDR strategy based on a bi-level collaborative optimization framework that coordinates the interaction between the grid and EIIs.At the upper level,the grid operatorminimizes generation and curtailment costs by optimizing unit commitment while determining real-time electricity prices and dynamic carbon emission factors.At the lower level,EIIs respond to these dual signals by minimizing their combined electricity and carbon trading costs,considering their participation in medium-and long-term electricity markets,day-ahead spot markets,and carbon emissions trading schemes.The model accounts for direct and indirect carbon emissions,distributed photovoltaic(PV)generation,and battery energy storage systems.This interaction is structured as a Stackelberg game,where the grid acts as the leader and EIIs as followers,enabling dynamic feedback between pricing signals and load response.Simulation studies on an improved IEEE 30-bus system,with a cement plant as a representative user form EIIs,show that the proposed strategy reduces user-side carbon emissions by 7.95% and grid-side generation cost by 4.66%,though the user’s energy cost increases by 7.80% due to carbon trading.Theresults confirmthat the joint guidance of electricity and carbon prices effectively reshapes user load profiles,encourages peak shaving,and improves PV utilization.This coordinated approach not only achieves emission reduction and cost efficiency but also offers a theoretical and practical foundation for integrating carbon pricing into demand-side energy management in future low-carbon power systems.展开更多
With the growth of intermittent renewable energy generation in power grids,there is an increasing demand for controllable resources to be deployed to guarantee power quality and frequency stability.The flexibility of ...With the growth of intermittent renewable energy generation in power grids,there is an increasing demand for controllable resources to be deployed to guarantee power quality and frequency stability.The flexibility of demand response(DR)resources has become a valuable solution to this problem.However,existing research indicates that problems on flexibility prediction of DR resources have not been investigated.This study applied the temporal convolution network(TCN)-combined transformer,a deep learning technique to predict the aggregated flexibility of two types of DR resources,that is,electric vehicles(EVs)and domestic hot water system(DHWS).The prediction uses historical power consumption data of these DR resources and DR signals(DSs)to facilitate prediction.The prediction can generate the size and maintenance time of the aggregated flexibility.The accuracy of the flexibility prediction results was verified through simulations of case studies.The simulation results show that under different maintenance times,the size of the flexibility changed.The proposed DR resource flexibility prediction method demonstrates its application in unlocking the demand-side flexibility to provide a reserve to grids.展开更多
The time-of-use(TOU)strategy can effectively improve the energy consumption mode of customers,reduce the peak-valley difference of load curve,and optimize the allocation of energy resources.This study presents an Opti...The time-of-use(TOU)strategy can effectively improve the energy consumption mode of customers,reduce the peak-valley difference of load curve,and optimize the allocation of energy resources.This study presents an Optimal guidance mechanism of the flexible load based on strategies of direct load control and time-of-use.First,this study proposes a period partitioning model,which is based on a moving boundary technique with constraint factors,and the Dunn Validity Index(DVI)is used as the objective to solve the period partitioning.Second,a control strategy for the curtailable flexible load is investigated,and a TOU strategy is utilized for further modifying load curve.Third,a price demand response strategy for adjusting transferable load is proposed in this paper.Finally,through the case study analysis of typical daily flexible load curve,the efficiency and correctness of the proposed method and model are validated and proved.展开更多
To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimizatio...To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.展开更多
Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various ...Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.展开更多
In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the oper...In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.展开更多
With the severe challenges brought by global climate change,exploring and developing clean and renewable energy systems to upgrade the energy structure has become an inevitable trend in related research.The comprehens...With the severe challenges brought by global climate change,exploring and developing clean and renewable energy systems to upgrade the energy structure has become an inevitable trend in related research.The comprehensive park systems integrated with photovoltaic,energy storage,direct current,and flexible loads(PEDF)is able to play an important role in promoting energy transformation and achieving sustainable development.In order to fully understand the advantages of PEDF parks in energy conservation and carbon reduction,this paper summarizes existing studies and prospects future research directions on the low-carbon operation of the PEDF park.This paper first introduces carbon emission monitoring and evaluation methods,and then analyzes bi-level optimal dispatch strategies for flexible loads.Meanwhile,the paper provides a prospective analysis of the innovations that can be brought by advanced technologies to the PEDF park.Finally,this paper puts forward the challenges faced by current research and provides prospects for future research directions.This paper emphasizes that related research should focus on collaborating key technologies of PEDF systems and integrating advanced innovations to address challenges and fully leverage the advantages of PEDF technology in energy saving and carbon reduction.This paper aims to provide systematic theoretical guidance and supplements for the research and practice of the PEDF technology.展开更多
Deep exploration of user-side flexibility resources is crucial for large-scale renewable energy consumption.This paper proposed a typical integrated energy system(IES)that comprehensively includes wind power,photovolt...Deep exploration of user-side flexibility resources is crucial for large-scale renewable energy consumption.This paper proposed a typical integrated energy system(IES)that comprehensively includes wind power,photovoltaic,thermal power,combined heat and power,hybrid energy storage,and flexible load and constructed the system’s unified power flow model based on the heat current method.On this basis,the regulation capabilities of different typical industrial and residential flexible loads were considered the symmetrical source-type load,which can transfer load and align user demand with the peaks and valleys of renewable energy generation,thus achieving power-energy decoupling.This contributes effectively to renewable energy accommodation capacity when the total electrical energy consumption remains constant.In both typical industrial and residential load scenarios,flexible load reduces integrated costs,increases renewable energy consumption,lowers peak thermal power generation,and decreases the requirement for a battery energy storage system(BESS).Besides,on typical industrial and residential load days,smoothing thermal power generation necessitates 12%and 18%flexible load,respectively,while replacing BESS requires 18%and 23%flexible load,respectively.Therefore,we can obtain the feasible operation ranges of symmetrical source-type load and provide suggestions for configuration capacity design of demand response in integrated energy systems.展开更多
The existing researches on the flexibility evaluation and optimal scheduling of flexible loads in residential buildings do not fully consider the association characteristics of different loads,resulting in a large dev...The existing researches on the flexibility evaluation and optimal scheduling of flexible loads in residential buildings do not fully consider the association characteristics of different loads,resulting in a large deviation between the calculated results and experimental results of optimization scheduling.A flexibility evaluation methodology and an optimization model considering load associations characteristics are proposed for flexible loads in residential buildings.Temporal flexibility ratio,which is the ratio of temporal flexibility considering association characteristics to that without considering association characteristics,is defined in this study.The optimization model is solved using the CPLEX solver under three different scenarios,namely,a scenario only considering the temporal overlapping load associations,a scenario only considering the temporal non-overlapping load associations,and a scenario considering both types of load associations.It was shown that in the residential building case in this study,the cooking loads with association characteristics exhibit less temporal flexibility but higher temporal flexibility ratio of up to 71.21%,while laundry loads exhibit higher temporal flexibility,but their temporal flexibility ratio is only around 36.84%.Additionally,when the users adopted the time of use(TOU)price,their electricity costs under the three considered scenarios increased by 0.00%,7.57%,and 7.57%relative to the scenario without considering load associations,respectively.When installing a 3-kW household photovoltaic system,the electricity costs under the three scenarios increased by 0.00%,1.28%,and 1.28%,respectively.As highlighted in the results,temporal non-overlapping association characteristics greatly affect the optimal scheduling of flexible energy loads,especially under TOU,while temporal overlapping association characteristics have little effect on that.展开更多
Recently, the heat and electricity integrated energy system (HE-IES) has become a hot topic in both industry and academia. In the HE- IES, the potential flexibility of the buildings' thermal loads can be exploited...Recently, the heat and electricity integrated energy system (HE-IES) has become a hot topic in both industry and academia. In the HE- IES, the potential flexibility of the buildings' thermal loads can be exploited to relax the heat power balance constraints and consequently allow a more flexible operation of the combined heat and power units. In this paper, model-driven and data-driven techniques are combined to quantify the demand flexibility of the buildings' thermal loads in a non-instructive way. First, the explicit analytical equivalent thermal parameter (ETP) model of the aggregated buildings is developed. The heat transfer coefficient (k) and thermal inertia coefficient (C) of the ETP model are designated to measure the potential demand flexibility. Second, the Particle Swarm Optimization optimized Radial Basis Function neural network (PSO-RBF) is used to identify the relationship between the values of k and C and the meteorological factors. To obtain the training data, an innovative two-stage regression method based on the adaptive temporal resolution is proposed to extract k and C values from the historical thermal load data. Finally, a flexible thermal load model is built based on the predictions of the meteorological factors, which can be conveniently incorporated into the online dispatch of the HE-IES. A comprehensive simulation environment is designed to verify the accuracy and availability of the proposed technique.展开更多
The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildi...The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildings.The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid.For this purpose,this work introduces a framework of multiple incentive mechanisms for a PEDF park,a building energy system that implements PEDF technologies.The incentive mechanisms proposed in this paper include both economic and noneconomic aspects,which is the most significant innovation of this paper.By modeling the relationship between a PEDF park and the power grid into a Stackelberg game,we demonstrate the effectiveness of these incentive measures in promoting the friendly interaction between the two entities.In this game model,the power grid determines on the prices of electricity trading and incentive subsidy,aiming to maximize its revenue while reducing the peak load of the PEDF park.On the other hand,the PEDF park make its dispatch plan according to the prices established by the grid,in order to reduce electricity consumption expense,improve electricity utility,and enhance the penetration rate of renewable energy.The results show that the proposed incentive mechanisms for the PEDF park can help to optimize energy consumption and promote sustainable energy practices.展开更多
With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This st...With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.展开更多
With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable ener...With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.展开更多
The increasing penetration of wind power poses challenges to the power grid operation and scheduling. Yet, if the uncertainty of wind power can be economically and effec tively managed on the source side, it can drive...The increasing penetration of wind power poses challenges to the power grid operation and scheduling. Yet, if the uncertainty of wind power can be economically and effec tively managed on the source side, it can drive the power grids towards renewable-dominant future. In this paper, an en hanced scheduling strategy for wind farm−flexible load joint op eration system (WF-FLJOS) is proposed. The proposed strategy is designed to manage the uncertainty of wind power on the generation side when integrated into a large-scale power grid. Moreover, it can contribute to saving energy costs on the load side. Compared with the current wind farm operation rules, more stringent assessment requirements are put forward for wind power output accuracy, and the internal organization framework of WF-FLJOS is designed. For potential power vio lations of wind farms and flexible loads, the violation penalty mechanisms are developed to regulate the behavior of the par ticipants. The joint operation model of the WF-FLJOS is pro posed and the submission and tracking approach of the genera tion schedule for the wind farm is investigated. Numerical re sults indicate that the proposed strategy can not only improve the ability of the wind farm to track the generation schedule, but also consider the benefits of both the farm side and the load side. Meanwhile, the proposed strategy effectively reduces the schedule adjustment pressure on the main grid caused by the rolling correction mode of the intraday schedule for wind farms.展开更多
Due to the inherent nature of high fluctuation and randomness,it is hard for renewable energy sources to meet full-time power quality requirements,and are thus difficult to be directly consumed by loads.In this study ...Due to the inherent nature of high fluctuation and randomness,it is hard for renewable energy sources to meet full-time power quality requirements,and are thus difficult to be directly consumed by loads.In this study we propose efficient flexible load microgrid system(EFLM),which breaks through point of common coupling(PCC)connection widely adapted by traditional microgrid;with slice-based multi-source energy distribution methodology,EFLM distribute power through flexible source-load connection,to loads with classified types of consumption,achieving the goal of directly allocating otherwise wasted renewable energy,to suitable loads through principles of loads classification,dynamic source-load coupling,time-based power slicing,flow-free power control,and transparent aggregation of multi-source energy.From maximising renewable energy utilisation during its entire output period,EFLM enhances direct energy utilisation,meanwhile reduces impact due to local fluctuation to the main grid.This research also provides a new pathway to microgrids accommodating high proportion of renewable energy,grid-forming and off-grid microgrid configurations,high-capacity energy storage charge-discharge management,and medium-to-low-voltage flexible grid construction.展开更多
A model-based optimal dispatch framework was proposed to optimize operation of residential flexible loads considering their real-life operating characteristics,energy-related occupant behavior,and the benefits of diff...A model-based optimal dispatch framework was proposed to optimize operation of residential flexible loads considering their real-life operating characteristics,energy-related occupant behavior,and the benefits of different stakeholders.A pilot test was conducted for a typical household.According to the monitored appliance-level data,operating characteristics of flexible loads were identified and the models of these flexible loads were developed using multiple linear regression and K-means clustering methods.Moreover,a data-mining approach was developed to extract the occupant energy usage behavior of various flexible loads from the monitored data.Occupant behavior of appliance usage,such as daily turn-on times,turn-on moment,duration of each operation,preference of temperature setting,and flexibility window,were determined by the developed data-mining approach.Based on the established flexible load models and the identified occupant energy usage behavior,a many-objective nonlinear optimal dispatch model was developed aiming at minimizing daily electricity costs,occupants’dissatisfaction,CO_(2) emissions,and the average ramping index of household power profiles.The model was solved with the assistance of the NSGA-III and TOPSIS methods.Results indicate that the proposed framework can effectively optimize the operation of household flexible loads.Compared with the benchmark,the daily electricity costs,CO_(2) emissions,and average ramping index of household power profiles of the optimal plan were reduced by 7.3%,6.5%,and 14.4%,respectively,under the TOU tariff,while those were decreased by 9.5%,8.8%,and 23.8%,respectively,under the dynamic price tariff.The outputs of this work can offer guidance for the day-ahead optimal scheduling of household flexible loads in practice.展开更多
End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability,reduce costs,and support increased hosting of distributed r...End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability,reduce costs,and support increased hosting of distributed renewable generation.This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling.We consider services delivered to(1)the high-voitage bulk power system through the coordinated action of many,distributed building loads working together,and(2)targeted support provided to the operation of low-voltage electric distribution grids.Although an exhaustive exploration is not possible,we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling(BEM)tools,suggesting pathways for future research and development.展开更多
In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and fl...In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming(MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency.展开更多
For optimal operation of microgrids,energy management is indispensable to reduce the operation cost and the emission of conventional units.The goals can be impeded by several factors including uncertainties of market ...For optimal operation of microgrids,energy management is indispensable to reduce the operation cost and the emission of conventional units.The goals can be impeded by several factors including uncertainties of market price,renewable generation,and loads.Real-time energy management system(EMS)can effectively address uncertainties due to the online information of market price,renewable generation,and loads.However,some issues arise in real-time EMS as batterylimited energy levels.In this paper,Lyapunov optimization is used to minimize the operation cost of the microgrid and the emission of conventional units.Therefore,the problem is multiobjective and a Pareto front is derived to compromise between the operation cost and the emission.With a modified IEEE 33-bus distribution system,general algebraic modeling system(GAMS)is utilized for implementing the proposed EMS on two case studies to verify its applicability.展开更多
基金the financial support of the Science and Technology Innovation Program of Hunan Province(2020RC5003)the research and application of key technologies for zero-energy buildings based on distributed energy storage and air conditioning demand response(2020-K-165)+1 种基金the Technology Innovation Program of Hunan Province(2017XK2015)the Technology Innovation Program of Hunan Province(2020RC2017)。
文摘This paper reviews recent research on the demand flexibility of residential buildings in regard to definitions,flexible loads,and quantification methods.A systematic distinction of the terminology is made,including the demand flexibility,operation flexibility,and energy flexibility of buildings.A comprehensive definition of building demand flexibility is proposed based on an analysis of the existing definitions.Moreover,the flexibility capabilities and operation characteristics of the main residential flexible loads are summarized and compared.Models and evaluation indicators to quantify the flexibility of these flexible loads are reviewed and summarized.Current research gaps and challenges are identified and analyzed as well.The results indicate that previous studies have focused on the flexibility of central air conditioning,electric water heaters,wet appliances,refrigerators,and lighting,where the proportion of studies focusing on each of these subjects is 36.7%,25.7%,14.7%,9.2%,and 8.3%,respectively.These flexible loads are different in running modes,usage frequencies,seasons,and capabilities for shedding,shifting,and modulation,while their response characteristics are not yet clear.Furthermore,recommendations are given for the application of white-,black-,and grey-box models for modeling flexible loads in different situations.Numerous static flexibility evaluation indicators that are based on the aspects of power,temporality,energy,efficiency,economics,and the environment have been proposed in previous publications,but a consensus and standardized evaluation framework is lacking.This review can help readers better understand building demand flexibility and learn about the characteristics of different residential flexible loads,while also providing suggestions for future research on the modeling techniques and evaluation metrics of residential building demand flexibility.
基金supported by the Science and Technology Project of Yunnan Power Grid Co.,Ltd.under Grant No.YNKJXM20222410.
文摘Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon transitions.To address this challenge,this paper proposes an electricity–carbon integratedDR strategy based on a bi-level collaborative optimization framework that coordinates the interaction between the grid and EIIs.At the upper level,the grid operatorminimizes generation and curtailment costs by optimizing unit commitment while determining real-time electricity prices and dynamic carbon emission factors.At the lower level,EIIs respond to these dual signals by minimizing their combined electricity and carbon trading costs,considering their participation in medium-and long-term electricity markets,day-ahead spot markets,and carbon emissions trading schemes.The model accounts for direct and indirect carbon emissions,distributed photovoltaic(PV)generation,and battery energy storage systems.This interaction is structured as a Stackelberg game,where the grid acts as the leader and EIIs as followers,enabling dynamic feedback between pricing signals and load response.Simulation studies on an improved IEEE 30-bus system,with a cement plant as a representative user form EIIs,show that the proposed strategy reduces user-side carbon emissions by 7.95% and grid-side generation cost by 4.66%,though the user’s energy cost increases by 7.80% due to carbon trading.Theresults confirmthat the joint guidance of electricity and carbon prices effectively reshapes user load profiles,encourages peak shaving,and improves PV utilization.This coordinated approach not only achieves emission reduction and cost efficiency but also offers a theoretical and practical foundation for integrating carbon pricing into demand-side energy management in future low-carbon power systems.
基金This work was supported by the National Natural Science Foundation of China(51877078 and 52061635102)the Beijing Nova Program(Z201100006820106).
文摘With the growth of intermittent renewable energy generation in power grids,there is an increasing demand for controllable resources to be deployed to guarantee power quality and frequency stability.The flexibility of demand response(DR)resources has become a valuable solution to this problem.However,existing research indicates that problems on flexibility prediction of DR resources have not been investigated.This study applied the temporal convolution network(TCN)-combined transformer,a deep learning technique to predict the aggregated flexibility of two types of DR resources,that is,electric vehicles(EVs)and domestic hot water system(DHWS).The prediction uses historical power consumption data of these DR resources and DR signals(DSs)to facilitate prediction.The prediction can generate the size and maintenance time of the aggregated flexibility.The accuracy of the flexibility prediction results was verified through simulations of case studies.The simulation results show that under different maintenance times,the size of the flexibility changed.The proposed DR resource flexibility prediction method demonstrates its application in unlocking the demand-side flexibility to provide a reserve to grids.
基金supported by open fund of state key laboratory of operation and control of renewable energy&storage systems(China electric power research institute)(No.NYB51202201709).
文摘The time-of-use(TOU)strategy can effectively improve the energy consumption mode of customers,reduce the peak-valley difference of load curve,and optimize the allocation of energy resources.This study presents an Optimal guidance mechanism of the flexible load based on strategies of direct load control and time-of-use.First,this study proposes a period partitioning model,which is based on a moving boundary technique with constraint factors,and the Dunn Validity Index(DVI)is used as the objective to solve the period partitioning.Second,a control strategy for the curtailable flexible load is investigated,and a TOU strategy is utilized for further modifying load curve.Third,a price demand response strategy for adjusting transferable load is proposed in this paper.Finally,through the case study analysis of typical daily flexible load curve,the efficiency and correctness of the proposed method and model are validated and proved.
基金supported by the Basic Science(Natural Science)Research Project of Jiangsu Higher Education Institutions(No.23KJB470020)the Natural Science Foundation of Jiangsu Province(Youth Fund)(No.BK20230384)。
文摘To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.
基金supported in part by Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.,China,under Grant J2022011.
文摘Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.
文摘In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.
基金This work was supported by National Key R&D Program of China for International S&T Cooperation Projects(Grant No.2019YFE0118700)which was provided by the Ministry of Science and Technology of the People’s Republic of China(https://www.most.gov.cn/(accessed on 1 January 2025))+2 种基金the grant was received by Yun Zhao.This work was supported by Science and Technology Project of CSG Electric Power Research Institute(Grant No.SEPRIK23B052)which was provided by CSG Electric Power Research Institute(http://www.sepri.csg.cn/(accessed on 1 January 2025))the grant was received by Ziwen Cai.
文摘With the severe challenges brought by global climate change,exploring and developing clean and renewable energy systems to upgrade the energy structure has become an inevitable trend in related research.The comprehensive park systems integrated with photovoltaic,energy storage,direct current,and flexible loads(PEDF)is able to play an important role in promoting energy transformation and achieving sustainable development.In order to fully understand the advantages of PEDF parks in energy conservation and carbon reduction,this paper summarizes existing studies and prospects future research directions on the low-carbon operation of the PEDF park.This paper first introduces carbon emission monitoring and evaluation methods,and then analyzes bi-level optimal dispatch strategies for flexible loads.Meanwhile,the paper provides a prospective analysis of the innovations that can be brought by advanced technologies to the PEDF park.Finally,this paper puts forward the challenges faced by current research and provides prospects for future research directions.This paper emphasizes that related research should focus on collaborating key technologies of PEDF systems and integrating advanced innovations to address challenges and fully leverage the advantages of PEDF technology in energy saving and carbon reduction.This paper aims to provide systematic theoretical guidance and supplements for the research and practice of the PEDF technology.
基金the National Natural Science Foundation of China(Grant No.52176068)the National key research and development program Intergovernmental projects(2022YFE0129400).
文摘Deep exploration of user-side flexibility resources is crucial for large-scale renewable energy consumption.This paper proposed a typical integrated energy system(IES)that comprehensively includes wind power,photovoltaic,thermal power,combined heat and power,hybrid energy storage,and flexible load and constructed the system’s unified power flow model based on the heat current method.On this basis,the regulation capabilities of different typical industrial and residential flexible loads were considered the symmetrical source-type load,which can transfer load and align user demand with the peaks and valleys of renewable energy generation,thus achieving power-energy decoupling.This contributes effectively to renewable energy accommodation capacity when the total electrical energy consumption remains constant.In both typical industrial and residential load scenarios,flexible load reduces integrated costs,increases renewable energy consumption,lowers peak thermal power generation,and decreases the requirement for a battery energy storage system(BESS).Besides,on typical industrial and residential load days,smoothing thermal power generation necessitates 12%and 18%flexible load,respectively,while replacing BESS requires 18%and 23%flexible load,respectively.Therefore,we can obtain the feasible operation ranges of symmetrical source-type load and provide suggestions for configuration capacity design of demand response in integrated energy systems.
基金supported by the National Natural Science Foundation of China(52378109)Innovation Capability Support Program of Shaanxi(2023KJXX-043)+1 种基金Young Talent Fund of Association for Science and Technology in Shaanxi(20220425)the Key Research and Development Program of Shaanxi,General Project(2023-YBSF-177).
文摘The existing researches on the flexibility evaluation and optimal scheduling of flexible loads in residential buildings do not fully consider the association characteristics of different loads,resulting in a large deviation between the calculated results and experimental results of optimization scheduling.A flexibility evaluation methodology and an optimization model considering load associations characteristics are proposed for flexible loads in residential buildings.Temporal flexibility ratio,which is the ratio of temporal flexibility considering association characteristics to that without considering association characteristics,is defined in this study.The optimization model is solved using the CPLEX solver under three different scenarios,namely,a scenario only considering the temporal overlapping load associations,a scenario only considering the temporal non-overlapping load associations,and a scenario considering both types of load associations.It was shown that in the residential building case in this study,the cooking loads with association characteristics exhibit less temporal flexibility but higher temporal flexibility ratio of up to 71.21%,while laundry loads exhibit higher temporal flexibility,but their temporal flexibility ratio is only around 36.84%.Additionally,when the users adopted the time of use(TOU)price,their electricity costs under the three considered scenarios increased by 0.00%,7.57%,and 7.57%relative to the scenario without considering load associations,respectively.When installing a 3-kW household photovoltaic system,the electricity costs under the three scenarios increased by 0.00%,1.28%,and 1.28%,respectively.As highlighted in the results,temporal non-overlapping association characteristics greatly affect the optimal scheduling of flexible energy loads,especially under TOU,while temporal overlapping association characteristics have little effect on that.
基金supported by the National Natural Science Foundation of China(52107072)International Cooperation and Exchange of NSFC(51861145406).
文摘Recently, the heat and electricity integrated energy system (HE-IES) has become a hot topic in both industry and academia. In the HE- IES, the potential flexibility of the buildings' thermal loads can be exploited to relax the heat power balance constraints and consequently allow a more flexible operation of the combined heat and power units. In this paper, model-driven and data-driven techniques are combined to quantify the demand flexibility of the buildings' thermal loads in a non-instructive way. First, the explicit analytical equivalent thermal parameter (ETP) model of the aggregated buildings is developed. The heat transfer coefficient (k) and thermal inertia coefficient (C) of the ETP model are designated to measure the potential demand flexibility. Second, the Particle Swarm Optimization optimized Radial Basis Function neural network (PSO-RBF) is used to identify the relationship between the values of k and C and the meteorological factors. To obtain the training data, an innovative two-stage regression method based on the adaptive temporal resolution is proposed to extract k and C values from the historical thermal load data. Finally, a flexible thermal load model is built based on the predictions of the meteorological factors, which can be conveniently incorporated into the online dispatch of the HE-IES. A comprehensive simulation environment is designed to verify the accuracy and availability of the proposed technique.
基金supported by Guangxi Power Grid Science and Technology Project(GXKJXM20222069).
文摘The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildings.The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid.For this purpose,this work introduces a framework of multiple incentive mechanisms for a PEDF park,a building energy system that implements PEDF technologies.The incentive mechanisms proposed in this paper include both economic and noneconomic aspects,which is the most significant innovation of this paper.By modeling the relationship between a PEDF park and the power grid into a Stackelberg game,we demonstrate the effectiveness of these incentive measures in promoting the friendly interaction between the two entities.In this game model,the power grid determines on the prices of electricity trading and incentive subsidy,aiming to maximize its revenue while reducing the peak load of the PEDF park.On the other hand,the PEDF park make its dispatch plan according to the prices established by the grid,in order to reduce electricity consumption expense,improve electricity utility,and enhance the penetration rate of renewable energy.The results show that the proposed incentive mechanisms for the PEDF park can help to optimize energy consumption and promote sustainable energy practices.
基金supported by State Grid Shanxi Electric Power Company Science and Technology Project“Research on key technologies of carbon tracking and carbon evaluation for new power system”(Grant:520530230005)。
文摘With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.
基金supported by State Grid Corporation of China Project“Research and Application of Key Technologies for Active Power Control in Regional Power Grid with High Penetration of Distributed Renewable Generation”(5108-202316044A-1-1-ZN).
文摘With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.
基金supported by National Natural Science Foundation of China(No.51877049).
文摘The increasing penetration of wind power poses challenges to the power grid operation and scheduling. Yet, if the uncertainty of wind power can be economically and effec tively managed on the source side, it can drive the power grids towards renewable-dominant future. In this paper, an en hanced scheduling strategy for wind farm−flexible load joint op eration system (WF-FLJOS) is proposed. The proposed strategy is designed to manage the uncertainty of wind power on the generation side when integrated into a large-scale power grid. Moreover, it can contribute to saving energy costs on the load side. Compared with the current wind farm operation rules, more stringent assessment requirements are put forward for wind power output accuracy, and the internal organization framework of WF-FLJOS is designed. For potential power vio lations of wind farms and flexible loads, the violation penalty mechanisms are developed to regulate the behavior of the par ticipants. The joint operation model of the WF-FLJOS is pro posed and the submission and tracking approach of the genera tion schedule for the wind farm is investigated. Numerical re sults indicate that the proposed strategy can not only improve the ability of the wind farm to track the generation schedule, but also consider the benefits of both the farm side and the load side. Meanwhile, the proposed strategy effectively reduces the schedule adjustment pressure on the main grid caused by the rolling correction mode of the intraday schedule for wind farms.
文摘Due to the inherent nature of high fluctuation and randomness,it is hard for renewable energy sources to meet full-time power quality requirements,and are thus difficult to be directly consumed by loads.In this study we propose efficient flexible load microgrid system(EFLM),which breaks through point of common coupling(PCC)connection widely adapted by traditional microgrid;with slice-based multi-source energy distribution methodology,EFLM distribute power through flexible source-load connection,to loads with classified types of consumption,achieving the goal of directly allocating otherwise wasted renewable energy,to suitable loads through principles of loads classification,dynamic source-load coupling,time-based power slicing,flow-free power control,and transparent aggregation of multi-source energy.From maximising renewable energy utilisation during its entire output period,EFLM enhances direct energy utilisation,meanwhile reduces impact due to local fluctuation to the main grid.This research also provides a new pathway to microgrids accommodating high proportion of renewable energy,grid-forming and off-grid microgrid configurations,high-capacity energy storage charge-discharge management,and medium-to-low-voltage flexible grid construction.
基金This work was supported by the National Natural Science Foundation of China(52278104)the Science and Technology Innovation Program of Hunan Province(2017XK2015).
文摘A model-based optimal dispatch framework was proposed to optimize operation of residential flexible loads considering their real-life operating characteristics,energy-related occupant behavior,and the benefits of different stakeholders.A pilot test was conducted for a typical household.According to the monitored appliance-level data,operating characteristics of flexible loads were identified and the models of these flexible loads were developed using multiple linear regression and K-means clustering methods.Moreover,a data-mining approach was developed to extract the occupant energy usage behavior of various flexible loads from the monitored data.Occupant behavior of appliance usage,such as daily turn-on times,turn-on moment,duration of each operation,preference of temperature setting,and flexibility window,were determined by the developed data-mining approach.Based on the established flexible load models and the identified occupant energy usage behavior,a many-objective nonlinear optimal dispatch model was developed aiming at minimizing daily electricity costs,occupants’dissatisfaction,CO_(2) emissions,and the average ramping index of household power profiles.The model was solved with the assistance of the NSGA-III and TOPSIS methods.Results indicate that the proposed framework can effectively optimize the operation of household flexible loads.Compared with the benchmark,the daily electricity costs,CO_(2) emissions,and average ramping index of household power profiles of the optimal plan were reduced by 7.3%,6.5%,and 14.4%,respectively,under the TOU tariff,while those were decreased by 9.5%,8.8%,and 23.8%,respectively,under the dynamic price tariff.The outputs of this work can offer guidance for the day-ahead optimal scheduling of household flexible loads in practice.
基金This work was authored in part by the National Renewable Energy Laboratory,operated by Alliance for Sustainable Energy,LLC,for the U.S.Department of Energy(DOE)under Contract No.DE-AC36-08GO28308Funding provided by the National Renewable Energy Laboratory(NREL)Laboratory Directed Research and Development(LDRD)program.
文摘End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability,reduce costs,and support increased hosting of distributed renewable generation.This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling.We consider services delivered to(1)the high-voitage bulk power system through the coordinated action of many,distributed building loads working together,and(2)targeted support provided to the operation of low-voltage electric distribution grids.Although an exhaustive exploration is not possible,we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling(BEM)tools,suggesting pathways for future research and development.
文摘In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming(MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency.
基金supported by a research grant of the University of Tabriz,Vice Chancellery for Research and Technology,University of Tabriz,Tabriz,Iran
文摘For optimal operation of microgrids,energy management is indispensable to reduce the operation cost and the emission of conventional units.The goals can be impeded by several factors including uncertainties of market price,renewable generation,and loads.Real-time energy management system(EMS)can effectively address uncertainties due to the online information of market price,renewable generation,and loads.However,some issues arise in real-time EMS as batterylimited energy levels.In this paper,Lyapunov optimization is used to minimize the operation cost of the microgrid and the emission of conventional units.Therefore,the problem is multiobjective and a Pareto front is derived to compromise between the operation cost and the emission.With a modified IEEE 33-bus distribution system,general algebraic modeling system(GAMS)is utilized for implementing the proposed EMS on two case studies to verify its applicability.
