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
Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours ...Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.展开更多
Increasing railway traffic and energy utilization issues prompt electrified railway systems to be more economical,efficient and sustainable.As regenerative braking energy in railway systems has huge potential for opti...Increasing railway traffic and energy utilization issues prompt electrified railway systems to be more economical,efficient and sustainable.As regenerative braking energy in railway systems has huge potential for optimized utilization,a lot of research has been focusing on how to use the energy efficiently and gain sustainable benefits.The energy storage system is an alternative because it not only deals with regenerative braking energy but also smooths drastic fluctuation of load power profile and optimizes energy management.In this work,we propose a co-phase traction power supply system with super capacitor(CSS_SC)for the purpose of realizing the function of energy management and power quality management in electrified railways.Besides,the coordinated control strategy is presented to match four working modes,including traction,regenerative braking,peak shaving and valley filling.A corresponding simulation model is built in MATLAB/Simulink to verify the feasibility of the proposed system under dynamic working conditions.The results demonstrate that CSS_SC is flexible to deal with four different working conditions and can realize energy saving within the allowable voltage unbalance of 0.008%in simulation in contrast to 1.3%of the standard limit.With such a control strategy,the performance of super capacitor is controlled to comply with efficiency and safety constraints.Finally,a case study demonstrates the improvement in power fluctuation with the valley-to-peak ratio reduced by 20.3%and the daily load factor increased by 17.9%.展开更多
Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribu...Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribution network’s challenges,which affect network performance,are:(i)Load disconnection or technical constraints violation,which may happen during reconfiguration after fault,(ii)Unpredictable power generation change due to Photovoltaic(PV)penetration,(iii)Undesirable PV reverse power,and(iv)Low Load Factor(LF)which may affect electricity price.In this paper,the BESS is used to support distribution networks in reconfiguration after a fault,increasing Photovoltaic(PV)penetration,cutting peak load,and loading valley filling.The paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation changes.For determining themaximumpower generation change due to PV,actual power registration of connected PV plants in South Cairo Electricity Distribution Company(SCEDC)was considered for a year.In addition,the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as:the ability to absorb PV power surplus,cut peak load and fill load valley for improving network’s performances.The methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC zone.The simulation studies are performed using the DIgSILENT PowerFactory software andDPL programming language.The Mixed Integer Linear Programming optimization technique(MILP)in MATLAB is employed to choose the best locations and sizing of BESS.展开更多
The rainflow counting method is a reasonable cyclecounting procedure for fatigue life calculation and simulation testing of structures.It defines cycles as closed stress /strain hysteresis loops.Application of the rai...The rainflow counting method is a reasonable cyclecounting procedure for fatigue life calculation and simulation testing of structures.It defines cycles as closed stress /strain hysteresis loops.Application of the rainflow counting method requires a data processing of the loading spectrum,which consists of the elimination of non-peak value data points,load time histories adjustment and loop extraction.In the data processing of the loading spectrum,if a stress point is neither the peak nor the valley,it will be identified and eliminated from the loading spectrum.Generally,the loading process is idealized as a single peak-valley straight line.But in actually,there are polylines or nearly straight lines between peaks and valleys which can't be ignored.Therefore,in the process of eliminating such data points,it will produce error in method itself.To reduce the error produced by the traditional method itself,a new method which can well simplify the polylines in data processing of loading spectrum is proposed in this paper.Comparing with the original approximation method,the proposed method has higher precision.展开更多
Typically extrema filtration techniques are based on non-parametric properties such as magnitude of prominences and the widths at half prominence, which cannot be used with data that possess a dynamic nature. In this ...Typically extrema filtration techniques are based on non-parametric properties such as magnitude of prominences and the widths at half prominence, which cannot be used with data that possess a dynamic nature. In this work, an extrema identification that is totally independent of derivative-based approaches and independent of quantitative attributes is introduced. For three consecutive positive terms arranged in a line, the ratio (R) of the sum of the maximum and minimum to the sum of the three terms is always 2/n, where n is the number of terms and 2/3 ≤ R ≤ 1 when n = 3. R > 2/3 implies that one term is away from the other two terms. Applying suitable modifications for the above stated hypothesis, the method was developed and the method is capable of identifying peaks and valleys in any signal. Furthermore, three techniques were developed for filtering non-dominating, sharp, gradual, low and high extrema. Especially, all the developed methods are non-parametric and suitable for analyzing processes that have dynamic nature such as biogas data. The methods were evaluated using automatically collected biogas data. Results showed that the extrema identification method was capable of identifying local extrema with 0% error. Furthermore, the non-parametric filtering techniques were able to distinguish dominating, flat, sharp, high, and low extrema in the biogas data with high robustness.展开更多
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Key R&D Program of Tianjin,China(No.20YFYSGX00060).
文摘Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.
文摘Increasing railway traffic and energy utilization issues prompt electrified railway systems to be more economical,efficient and sustainable.As regenerative braking energy in railway systems has huge potential for optimized utilization,a lot of research has been focusing on how to use the energy efficiently and gain sustainable benefits.The energy storage system is an alternative because it not only deals with regenerative braking energy but also smooths drastic fluctuation of load power profile and optimizes energy management.In this work,we propose a co-phase traction power supply system with super capacitor(CSS_SC)for the purpose of realizing the function of energy management and power quality management in electrified railways.Besides,the coordinated control strategy is presented to match four working modes,including traction,regenerative braking,peak shaving and valley filling.A corresponding simulation model is built in MATLAB/Simulink to verify the feasibility of the proposed system under dynamic working conditions.The results demonstrate that CSS_SC is flexible to deal with four different working conditions and can realize energy saving within the allowable voltage unbalance of 0.008%in simulation in contrast to 1.3%of the standard limit.With such a control strategy,the performance of super capacitor is controlled to comply with efficiency and safety constraints.Finally,a case study demonstrates the improvement in power fluctuation with the valley-to-peak ratio reduced by 20.3%and the daily load factor increased by 17.9%.
文摘Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribution network’s challenges,which affect network performance,are:(i)Load disconnection or technical constraints violation,which may happen during reconfiguration after fault,(ii)Unpredictable power generation change due to Photovoltaic(PV)penetration,(iii)Undesirable PV reverse power,and(iv)Low Load Factor(LF)which may affect electricity price.In this paper,the BESS is used to support distribution networks in reconfiguration after a fault,increasing Photovoltaic(PV)penetration,cutting peak load,and loading valley filling.The paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation changes.For determining themaximumpower generation change due to PV,actual power registration of connected PV plants in South Cairo Electricity Distribution Company(SCEDC)was considered for a year.In addition,the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as:the ability to absorb PV power surplus,cut peak load and fill load valley for improving network’s performances.The methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC zone.The simulation studies are performed using the DIgSILENT PowerFactory software andDPL programming language.The Mixed Integer Linear Programming optimization technique(MILP)in MATLAB is employed to choose the best locations and sizing of BESS.
基金National Natural Science Foundation of China(No.11272082)
文摘The rainflow counting method is a reasonable cyclecounting procedure for fatigue life calculation and simulation testing of structures.It defines cycles as closed stress /strain hysteresis loops.Application of the rainflow counting method requires a data processing of the loading spectrum,which consists of the elimination of non-peak value data points,load time histories adjustment and loop extraction.In the data processing of the loading spectrum,if a stress point is neither the peak nor the valley,it will be identified and eliminated from the loading spectrum.Generally,the loading process is idealized as a single peak-valley straight line.But in actually,there are polylines or nearly straight lines between peaks and valleys which can't be ignored.Therefore,in the process of eliminating such data points,it will produce error in method itself.To reduce the error produced by the traditional method itself,a new method which can well simplify the polylines in data processing of loading spectrum is proposed in this paper.Comparing with the original approximation method,the proposed method has higher precision.
文摘Typically extrema filtration techniques are based on non-parametric properties such as magnitude of prominences and the widths at half prominence, which cannot be used with data that possess a dynamic nature. In this work, an extrema identification that is totally independent of derivative-based approaches and independent of quantitative attributes is introduced. For three consecutive positive terms arranged in a line, the ratio (R) of the sum of the maximum and minimum to the sum of the three terms is always 2/n, where n is the number of terms and 2/3 ≤ R ≤ 1 when n = 3. R > 2/3 implies that one term is away from the other two terms. Applying suitable modifications for the above stated hypothesis, the method was developed and the method is capable of identifying peaks and valleys in any signal. Furthermore, three techniques were developed for filtering non-dominating, sharp, gradual, low and high extrema. Especially, all the developed methods are non-parametric and suitable for analyzing processes that have dynamic nature such as biogas data. The methods were evaluated using automatically collected biogas data. Results showed that the extrema identification method was capable of identifying local extrema with 0% error. Furthermore, the non-parametric filtering techniques were able to distinguish dominating, flat, sharp, high, and low extrema in the biogas data with high robustness.
