The economy of distribution networks largely depends on the utilization rate of distribution network equipment.Most of the emerging intelligent power consumption technologies have a positive effect on equipment utiliz...The economy of distribution networks largely depends on the utilization rate of distribution network equipment.Most of the emerging intelligent power consumption technologies have a positive effect on equipment utilization and their use can save investment of distribution networks.In this paper,the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment is reviewed.The evaluation methods and indexes are assessed first and then intelligent power consumption equipment with energy storage function,vehicle-to-grid(V2G)technology and time-of-use(TOU)tariff are reviewed respectively.It is concluded that these intelligent power consumption technologies and measures have great potential to improve utilization rate of distribution network equipment because of their effective improvement to power load.Meanwhile,recommendations on how to utilize these intelligent power consumption technologies to improve utilization rate of distribution network equipment are proposed.展开更多
A system combining photovoltaic power generation and cogeneration is proposed to improve the photoelectric absorption capacity. First, a time-of-use price strategy is adopted to guide users to change their electricity...A system combining photovoltaic power generation and cogeneration is proposed to improve the photoelectric absorption capacity. First, a time-of-use price strategy is adopted to guide users to change their electricity consumption habits for participation in the demand response, and a demand response model is established. Then, particle swarm optimization(PSO)is used with the aim of minimizing the operation cost of the microgrid to achieve economic dispatching of the microgrid. This considers power balance equation constraints, unit operation constraints, energy storage constraints, and heat storage constraints. Finally, the simulation results show the improved level of photoelectric consumption using the proposed scheme and the economic benefits of the microgrid.展开更多
A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cos...A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power（CHP）units,and waste heat and energy recovery generators（WHERG）,were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization（IPSO）algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach.展开更多
Purpose–This paper aims to optimize the charging schedule for battery electric buses(BEBs)to minimize the charging cost considering the time-ofuse electricity price.Design/methodology/approach–The BEBs charging sche...Purpose–This paper aims to optimize the charging schedule for battery electric buses(BEBs)to minimize the charging cost considering the time-ofuse electricity price.Design/methodology/approach–The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model.The objective is to minimize the total charging cost of the BEB fleet.The charge decision of each BEB at the end of each trip is to be determined.Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.Findings–This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line.The results show that the total charge cost with the optimized charging schedule is 15.56%lower than the actual total charge cost under given conditions.The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent,which can provide a reference for planning the number of charging piles.Originality/value–Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.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
Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally inte...Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.展开更多
While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited...While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited by its high costs.In this study,we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system,that comprises a government agent,local utility company agent,and different types of consumer agents.In the proposed model,we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward induction.Two pricing strategies,namely,the TOU seasonal pricing and TOU monthly pricing,are evaluated and compared with traditional fixed pricing.The numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed pricing.Additionally,TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.展开更多
Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed...Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency.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
Large-scale new energy pressures on the grids bring challenges to power system's security and stability.In order to optimize the user's electricity consumption behavior and ease pressure,which is caused by new...Large-scale new energy pressures on the grids bring challenges to power system's security and stability.In order to optimize the user's electricity consumption behavior and ease pressure,which is caused by new energy on the grid,this paper proposes a time-of-use price model that takes wind power uncertainty into account.First,the interval prediction method is used to predict wind power.Then typical wind power scenes are selected by random sampling and bisecting the K-means algorithm.On this basis,integer programming is used to divide the peak-valley period of the multi-scenes load.Finally,under the condition of many factors such as user response based on consumer psychology,user electricity charge and power consumption,this paper takes the peak-valley difference of equivalent net load and the user dissatisfaction degree as the goal,and using the NSGA-II multi-objective optimization algorithm,evaluates the Pareto solution set to obtain the optimal solution.In order to test the validity of the model proposed in this paper,we apply it to an industrial user and wind farms in Yan'an city,China.The results show that the model can effectively ensure the user's electrical comfort while achieving the role of peak shaving and valley flling.展开更多
基金This work is supported by State Grid Corporation of China(5216A018000M).
文摘The economy of distribution networks largely depends on the utilization rate of distribution network equipment.Most of the emerging intelligent power consumption technologies have a positive effect on equipment utilization and their use can save investment of distribution networks.In this paper,the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment is reviewed.The evaluation methods and indexes are assessed first and then intelligent power consumption equipment with energy storage function,vehicle-to-grid(V2G)technology and time-of-use(TOU)tariff are reviewed respectively.It is concluded that these intelligent power consumption technologies and measures have great potential to improve utilization rate of distribution network equipment because of their effective improvement to power load.Meanwhile,recommendations on how to utilize these intelligent power consumption technologies to improve utilization rate of distribution network equipment are proposed.
基金supported by the key projects of the National Natural Science Foundation of China (No.61833008,No.61573300)Jiangsu Provincial Natural Science Foundation of China (No.BK20171445)Key Research and Development Plan of Jiangsu Province (No.BE2016184)。
文摘A system combining photovoltaic power generation and cogeneration is proposed to improve the photoelectric absorption capacity. First, a time-of-use price strategy is adopted to guide users to change their electricity consumption habits for participation in the demand response, and a demand response model is established. Then, particle swarm optimization(PSO)is used with the aim of minimizing the operation cost of the microgrid to achieve economic dispatching of the microgrid. This considers power balance equation constraints, unit operation constraints, energy storage constraints, and heat storage constraints. Finally, the simulation results show the improved level of photoelectric consumption using the proposed scheme and the economic benefits of the microgrid.
基金Sponsored by National Natural Science Foundation of China(51304053)International Science and Technology Cooperation Program of China(2013DFA10810)
文摘A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power（CHP）units,and waste heat and energy recovery generators（WHERG）,were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization（IPSO）algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China(72001007)the China Postdoctoral Science Foundation(2021M700304).
文摘Purpose–This paper aims to optimize the charging schedule for battery electric buses(BEBs)to minimize the charging cost considering the time-ofuse electricity price.Design/methodology/approach–The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model.The objective is to minimize the total charging cost of the BEB fleet.The charge decision of each BEB at the end of each trip is to be determined.Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.Findings–This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line.The results show that the total charge cost with the optimized charging schedule is 15.56%lower than the actual total charge cost under given conditions.The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent,which can provide a reference for planning the number of charging piles.Originality/value–Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.
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.
基金King Saud University for funding this research through the Researchers Supporting Program Number(RSPD2024R704),King Saud University,Riyadh,Saudi Arabia.
文摘Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.
基金supported by the National Natural Science Foundation of China(52277107,51977115)Shenzhen Science and Technology Innovation Program(WDZC20220808143010001).
文摘While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited by its high costs.In this study,we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system,that comprises a government agent,local utility company agent,and different types of consumer agents.In the proposed model,we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward induction.Two pricing strategies,namely,the TOU seasonal pricing and TOU monthly pricing,are evaluated and compared with traditional fixed pricing.The numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed pricing.Additionally,TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.
基金Project(3502Z20179026)supported by Xiamen Science and Technology Project,China。
文摘Large-scale electric vehicles(EVs) connected to the micro grid would cause many problems. In this paper, with the consideration of vehicle to grid(V2 G), two charging and discharging load modes of EVs were constructed. One was the disorderly charging and discharging mode based on travel habits, and the other was the orderly charging and discharging mode based on time-of-use(TOU) price;Monte Carlo method was used to verify the case. The scheme of the capacity optimization of photovoltaic charging station under two different charging and discharging modes with V2 G was proposed. The mathematical models of the objective function with the maximization of energy efficiency, the minimization of the investment and the operation cost of the charging system were established. The range of decision variables, constraints of the requirements of the power balance and the strategy of energy exchange were given. NSGA-Ⅱ and NSGA-SA algorithm were used to verify the cases, respectively. In both algorithms, by comparing with the simulation results of the two different modes, it shows that the orderly charging and discharging mode with V2 G is obviously better than the disorderly charging and discharging mode in the aspects of alleviating the pressure of power grid, reducing system investment and improving energy efficiency.
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.
基金supported by the Research Fund of the State Key Laboratory of Eco-hydraulics in Northwest Arid Region,Xi'an University of Technology(Grant No.2019KJCXTD-5)the Natural Science Basic Research Program of Shaanxi(Grant No.2019JLZ-15)the Key Research and Development Plan of Shaanxi Province(Grant No.2018-ZDCXL-GY-10-04).
文摘Large-scale new energy pressures on the grids bring challenges to power system's security and stability.In order to optimize the user's electricity consumption behavior and ease pressure,which is caused by new energy on the grid,this paper proposes a time-of-use price model that takes wind power uncertainty into account.First,the interval prediction method is used to predict wind power.Then typical wind power scenes are selected by random sampling and bisecting the K-means algorithm.On this basis,integer programming is used to divide the peak-valley period of the multi-scenes load.Finally,under the condition of many factors such as user response based on consumer psychology,user electricity charge and power consumption,this paper takes the peak-valley difference of equivalent net load and the user dissatisfaction degree as the goal,and using the NSGA-II multi-objective optimization algorithm,evaluates the Pareto solution set to obtain the optimal solution.In order to test the validity of the model proposed in this paper,we apply it to an industrial user and wind farms in Yan'an city,China.The results show that the model can effectively ensure the user's electrical comfort while achieving the role of peak shaving and valley flling.
