Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the...Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy transition.This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons.Smart meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns separately.The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series data.The intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire population.For the first time,a step function approach is applied to reduce time series dimensionality.Customer attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy usage.In addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined clusters.The application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the results.Further research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditions.展开更多
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
Demand-side flexibility is crucial to balancing supply and demand,as renewable energy sources are increasingly integrated into the energy mix,and heating and transport systems are becoming more and more electrified.Hi...Demand-side flexibility is crucial to balancing supply and demand,as renewable energy sources are increasingly integrated into the energy mix,and heating and transport systems are becoming more and more electrified.Historically,this balancing has been managed from the supply side.However,the shift towards renewable energy sources limits the controllability of traditional fossil fuel plants,increasing the importance of demand response(DR)techniques to achieve the required flexibility.Aggregators participating in flexibility markets need to accurately forecast the adaptability they can offer,a task complicated by numerous influencing variables.Based on a top-down approach,this study addresses the problem of forecasting electricity demand in the presence of flexibility from thermostatically controlled loads.We propose a hybrid model that combines data-driven techniques for probabilistic estimation of electricity consumption with a disaggregation of electricity consumption to identify the fraction of thermal loads,subject to flexibility,which is simulated by a virtual battery model.The technique is applied to a synthetic dataset that simulates the response of a European neighborhood to demand response interventions.The results demonstrate the model’s ability to accurately predict both the reduction in electricity demand during DR events and the subsequent rebound in consumption.The model achieves a mean absolute percentage error(MAPE)lower than 17.0%,comparable to the accuracy without flexibility.The results obtained are compared with a direct data-driven approach,demonstrating the validity and effectiveness of our model.展开更多
This paper proposes a novel approach for the provision of non-frequency ancillary service(AS)by consumers connected to low-voltage distribution networks.The proposed approach considers an asymmetric pool-based local m...This paper proposes a novel approach for the provision of non-frequency ancillary service(AS)by consumers connected to low-voltage distribution networks.The proposed approach considers an asymmetric pool-based local market for AS negotiation,allowing consumers to set a flexibility quantity and desired price to trade.A case study with 98 consumers illustrates the proposed market-based non-frequency AS provision approach.Also,three different strategies of consumers’participation are implemented and tested in a real low-voltage distribution network with radial topology.It is shown that consumers can make a profit from the sale of their flexibility while contributing to keeping the network power losses,voltage,and current within pre-defined limits.Ultimately,the results demonstrate the value of AS coming directly from end-users.展开更多
Large-scale development of electric vehicles(EVs)exposes power grids and transportation networks with limited capacity to increased fault risks.In this paper,a method to prevent fault risks in advance by using the fle...Large-scale development of electric vehicles(EVs)exposes power grids and transportation networks with limited capacity to increased fault risks.In this paper,a method to prevent fault risks in advance by using the flexibility of EV travel to coordinate the operation of dis-tribution and transportation networks is proposed.Since EV travel decisions are influenced by the charging and travel time costs,adjusting charging price and travel time price can help guide behavior and enable coordinated operation of power and transportation networks.First,risk-based distribution locational marginal prices(RDLMPs)are established to restrain the distribution network risks.Second,traffic risks are formulated using origin-destination(OD)risk marginal prices(ODRMPs)considering the degree of traffic congestion fault risks.Under the guidance of the RDLMPs and ODRMPs,EV fleets optimize their travel plans to minimize overall costs,including charging and time costs.Finally,case studies verify that the proposed method can reduce the opera-tional risks of both distribution and transportation net-works.展开更多
Aggregating demand side flexibility is essential to complementing the inflexible and variable renewable energy supply in achieving low carbon energy systems.Sources of demand side flexibility,e.g.,dispatchable generat...Aggregating demand side flexibility is essential to complementing the inflexible and variable renewable energy supply in achieving low carbon energy systems.Sources of demand side flexibility,e.g.,dispatchable generators,storage,and flexible loads,can be structured in a form of microgrids and collectively provided to utility grids through transactive energy in local energy markets.This paper proposes a framework of local energy markets to manage this transactive energy and facilitate the flexibility provision.The distribution system operator aims to achieve local energy balance by scheduling the operation of multi-microgrids and determining the imbalance prices.Multiple microgrid traders aim to maximize profits for their prosumers through dispatching flexibility sources and participating in localised energy trading.The decision making and interactions between a distribution system operator and multiple microgrid traders are formulated as the Stackelberg game-theoretic problem.Case studies using the IEEE 69-bus distribution system demonstrate the effectiveness of the developed model in terms of facilitating local energy balance and reducing dependency on the utility grids.展开更多
The deregulation of the power industry requires avoiding market power abuse to maintain the market competitiveness. To this end, a sequence of assessment measurements or mitigation mechanisms is required. Meanwhile, t...The deregulation of the power industry requires avoiding market power abuse to maintain the market competitiveness. To this end, a sequence of assessment measurements or mitigation mechanisms is required. Meanwhile, the increasing renewable energy resources(RESs) and flexible demand response resources(DRSs) are changing the behaviors of market participants and creating new cases of market power abuse.Such new circumstances bring the new evaluation and control methods of market power to the forefront. This paper provides a comprehensive review of market power in the reshaping of power systems due to the increasing RES and the development of DRS. The market power at the supply side, demand side,and in the multi-energy system is categorized and reviewed. In addition, the applications of market power supervision measures in the US, the Nordics, UK, and China are summarized.Furthermore, the unsolved issues, possible key technologies,and potential research topics on market power are discussed.展开更多
Industrial,commercial,and residential facilities are progressively adopting automation and generation capabilities.By having flexible demand and renewable energy generation,traditional passive customers are becoming a...Industrial,commercial,and residential facilities are progressively adopting automation and generation capabilities.By having flexible demand and renewable energy generation,traditional passive customers are becoming active participants in electric power system operations.Through profound coordination among grid operators and active customers,the facilities’capability for demand response(DR)and distributed energy resource(DER)management will be valuable asset for ancillary services(ASs).To comply with the increasing demand and flexible energy,utilities urgently require standards,regulations,and programs to efficiently handle load-side resources without trading off stability and reliability.This study reviews different types of customers’flexibilities for DR,highlighting their capabilities and limitations in performing local ancillary services(LASs),which should benefit the power grid by profiting from it through incentive mechanisms.Different financial incentives and techniques employed around the world are presented and discussed.The potential barriers in technical and regulatory aspects are successfully identified and potential solutions along with future guidance are discussed.展开更多
基金supported by the Spanish Ministry of Science and Innovation under Projects PID2022-137680OB-C32 and PID2022-139187OB-I00.
文摘Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy transition.This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons.Smart meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns separately.The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series data.The intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire population.For the first time,a step function approach is applied to reduce time series dimensionality.Customer attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy usage.In addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined clusters.The application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the results.Further research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditions.
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the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No.957755,project SENDER:Sustainable consumer engagement and demand response.
文摘Demand-side flexibility is crucial to balancing supply and demand,as renewable energy sources are increasingly integrated into the energy mix,and heating and transport systems are becoming more and more electrified.Historically,this balancing has been managed from the supply side.However,the shift towards renewable energy sources limits the controllability of traditional fossil fuel plants,increasing the importance of demand response(DR)techniques to achieve the required flexibility.Aggregators participating in flexibility markets need to accurately forecast the adaptability they can offer,a task complicated by numerous influencing variables.Based on a top-down approach,this study addresses the problem of forecasting electricity demand in the presence of flexibility from thermostatically controlled loads.We propose a hybrid model that combines data-driven techniques for probabilistic estimation of electricity consumption with a disaggregation of electricity consumption to identify the fraction of thermal loads,subject to flexibility,which is simulated by a virtual battery model.The technique is applied to a synthetic dataset that simulates the response of a European neighborhood to demand response interventions.The results demonstrate the model’s ability to accurately predict both the reduction in electricity demand during DR events and the subsequent rebound in consumption.The model achieves a mean absolute percentage error(MAPE)lower than 17.0%,comparable to the accuracy without flexibility.The results obtained are compared with a direct data-driven approach,demonstrating the validity and effectiveness of our model.
基金supported by the EU Horizon 2020 research and innovation program under project DOMINOES(No.771066)FEDER Funds through COMPETE program and National Funds through FCT under projects UID/EEA/00760/2019 and CEECIND/01811/2017supported by the Ph.D.grant SFRH/BD/133086/2017。
文摘This paper proposes a novel approach for the provision of non-frequency ancillary service(AS)by consumers connected to low-voltage distribution networks.The proposed approach considers an asymmetric pool-based local market for AS negotiation,allowing consumers to set a flexibility quantity and desired price to trade.A case study with 98 consumers illustrates the proposed market-based non-frequency AS provision approach.Also,three different strategies of consumers’participation are implemented and tested in a real low-voltage distribution network with radial topology.It is shown that consumers can make a profit from the sale of their flexibility while contributing to keeping the network power losses,voltage,and current within pre-defined limits.Ultimately,the results demonstrate the value of AS coming directly from end-users.
基金supported by the Project of State Grid Corporation of China(No.5108-202299265A-1-0-ZB).
文摘Large-scale development of electric vehicles(EVs)exposes power grids and transportation networks with limited capacity to increased fault risks.In this paper,a method to prevent fault risks in advance by using the flexibility of EV travel to coordinate the operation of dis-tribution and transportation networks is proposed.Since EV travel decisions are influenced by the charging and travel time costs,adjusting charging price and travel time price can help guide behavior and enable coordinated operation of power and transportation networks.First,risk-based distribution locational marginal prices(RDLMPs)are established to restrain the distribution network risks.Second,traffic risks are formulated using origin-destination(OD)risk marginal prices(ODRMPs)considering the degree of traffic congestion fault risks.Under the guidance of the RDLMPs and ODRMPs,EV fleets optimize their travel plans to minimize overall costs,including charging and time costs.Finally,case studies verify that the proposed method can reduce the opera-tional risks of both distribution and transportation net-works.
基金supported by National Key Research and Development Program of China (2019YFE0123600)National Natural Science Foundation of China (U2066211,52177124)+2 种基金in part by the Institute of Electrical Engineering,CAS (E155610101)the Youth Innovation Promotion Association of CAS (No.2019143)in part by the Ministry of Science and Technology of Chinese Taiwan under Grant MOST 109-2221-E007-020.
文摘Aggregating demand side flexibility is essential to complementing the inflexible and variable renewable energy supply in achieving low carbon energy systems.Sources of demand side flexibility,e.g.,dispatchable generators,storage,and flexible loads,can be structured in a form of microgrids and collectively provided to utility grids through transactive energy in local energy markets.This paper proposes a framework of local energy markets to manage this transactive energy and facilitate the flexibility provision.The distribution system operator aims to achieve local energy balance by scheduling the operation of multi-microgrids and determining the imbalance prices.Multiple microgrid traders aim to maximize profits for their prosumers through dispatching flexibility sources and participating in localised energy trading.The decision making and interactions between a distribution system operator and multiple microgrid traders are formulated as the Stackelberg game-theoretic problem.Case studies using the IEEE 69-bus distribution system demonstrate the effectiveness of the developed model in terms of facilitating local energy balance and reducing dependency on the utility grids.
文摘The deregulation of the power industry requires avoiding market power abuse to maintain the market competitiveness. To this end, a sequence of assessment measurements or mitigation mechanisms is required. Meanwhile, the increasing renewable energy resources(RESs) and flexible demand response resources(DRSs) are changing the behaviors of market participants and creating new cases of market power abuse.Such new circumstances bring the new evaluation and control methods of market power to the forefront. This paper provides a comprehensive review of market power in the reshaping of power systems due to the increasing RES and the development of DRS. The market power at the supply side, demand side,and in the multi-energy system is categorized and reviewed. In addition, the applications of market power supervision measures in the US, the Nordics, UK, and China are summarized.Furthermore, the unsolved issues, possible key technologies,and potential research topics on market power are discussed.
基金supported by the US Department of Defense(DOD)’s Environmental Security Technology Certification Program(ESTCP)(No.W912HQ20C0022)the support from the National Institute of Science and Technology on Distributed Generation Power Systems(INCT-GD)+3 种基金Higher Level Personnel Training Coordination(CAPES-No.23038.000776/2017-54)Foundation for Research of the State of Rio Grande do Sul(FAPERGS-No.17/2551-0000517-1)Federal University of Santa Maria(UFSM),(CAPES/PROEX)—Financial code 001 and CNPqthe Brazilian National Council for Scientific and Technological Development,process 465640/2014-1 and process CNPq PQ 1-D 310761/2018-2。
文摘Industrial,commercial,and residential facilities are progressively adopting automation and generation capabilities.By having flexible demand and renewable energy generation,traditional passive customers are becoming active participants in electric power system operations.Through profound coordination among grid operators and active customers,the facilities’capability for demand response(DR)and distributed energy resource(DER)management will be valuable asset for ancillary services(ASs).To comply with the increasing demand and flexible energy,utilities urgently require standards,regulations,and programs to efficiently handle load-side resources without trading off stability and reliability.This study reviews different types of customers’flexibilities for DR,highlighting their capabilities and limitations in performing local ancillary services(LASs),which should benefit the power grid by profiting from it through incentive mechanisms.Different financial incentives and techniques employed around the world are presented and discussed.The potential barriers in technical and regulatory aspects are successfully identified and potential solutions along with future guidance are discussed.
