Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electric...Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.展开更多
换电服务价格高是电动汽车换电模式普及率低的重要因素之一,为了提高换电模式使用程度,充分发挥换电模式参与系统调度时所发挥的削峰填谷作用,该文提出一种考虑用户参与度的换电服务定价策略及动态调控方法。首先,建立计及时间成本的充...换电服务价格高是电动汽车换电模式普及率低的重要因素之一,为了提高换电模式使用程度,充分发挥换电模式参与系统调度时所发挥的削峰填谷作用,该文提出一种考虑用户参与度的换电服务定价策略及动态调控方法。首先,建立计及时间成本的充电服务与换电服务总费用差价模型,并依据消费者心理学原理构建服务差价-用户参与度曲线;其次,制定换电服务定价策略,并提出相应的动态调控方法;最后,建立含充换电站(battery charging and swapping station,BCSS)的微电网联合系统双层优化模型。上层根据换电服务定价策略及动态调控方法,制定出用户参与度高的换电服务电价;下层根据用户响应换电服务电价后的负荷量,以微电网联合系统总运行成本最低为目标调度机组出力,并以用户满意度作为衡量换电服务电价的指标,合理调整下一时段换电服务电价。通过算例分析,所提方法在实现系统负荷削峰的同时,降低微电网联合系统总运行成本,体现了所提定价策略及动态调控方法的有效性。展开更多
针对传统电动汽车集群调度过程中未能充分考虑用户响应度及其影响因素对可调度容量影响的问题,提出了计及用户响应度的电动汽车充放电调度策略。首先基于用户出行数据,对电动汽车集群的充电负荷模型进行建模;其次建立了基于韦伯-费希纳...针对传统电动汽车集群调度过程中未能充分考虑用户响应度及其影响因素对可调度容量影响的问题,提出了计及用户响应度的电动汽车充放电调度策略。首先基于用户出行数据,对电动汽车集群的充电负荷模型进行建模;其次建立了基于韦伯-费希纳定律的电动汽车用户响应度模型,并综合考虑聚合商设定的充放电价和车辆荷电状态(state of charge,SOC)对用户充放电响应度的影响;最终将聚合商设定的充放电价与电动汽车的充放电功率作为决策变量,统筹考虑电网、聚合商以及电动汽车用户的三方收益,构建以最小化配电网负荷波动、最小化用户充电成本和最大化聚合商收益为目标的电动汽车充放电优化调度模型,采用粒子群优化算法(particle swarm optinization,PSO)求解该优化问题。通过算例结果表明,该模型能够在实现削峰填谷的同时,保证了聚合商以及电动汽车用户的利益。展开更多
Currently,oil companies face the "new normal" condition that the profit of their upstream business is shrinking with the plunge of oil price.This problem challenges the operation and management of the upstre...Currently,oil companies face the "new normal" condition that the profit of their upstream business is shrinking with the plunge of oil price.This problem challenges the operation and management of the upstream business.Therefore,it is essential to find out the new approaches and key points of work,to achieve the goal of realizing a quality and sustainable development.From ten aspects,this paper discusses the challenges facing the upstream business of oil companies and puts forward corresponding roadmaps and strategies.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
基金a phased achievement of Gansu Province’s Major Science and Technology Project(W22KJ2722005)“Research on Optimal Configuration and Operation Strategy of Energy Storage under“New Energy+Energy Storage”Mode”.
文摘Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.
文摘换电服务价格高是电动汽车换电模式普及率低的重要因素之一,为了提高换电模式使用程度,充分发挥换电模式参与系统调度时所发挥的削峰填谷作用,该文提出一种考虑用户参与度的换电服务定价策略及动态调控方法。首先,建立计及时间成本的充电服务与换电服务总费用差价模型,并依据消费者心理学原理构建服务差价-用户参与度曲线;其次,制定换电服务定价策略,并提出相应的动态调控方法;最后,建立含充换电站(battery charging and swapping station,BCSS)的微电网联合系统双层优化模型。上层根据换电服务定价策略及动态调控方法,制定出用户参与度高的换电服务电价;下层根据用户响应换电服务电价后的负荷量,以微电网联合系统总运行成本最低为目标调度机组出力,并以用户满意度作为衡量换电服务电价的指标,合理调整下一时段换电服务电价。通过算例分析,所提方法在实现系统负荷削峰的同时,降低微电网联合系统总运行成本,体现了所提定价策略及动态调控方法的有效性。
文摘针对传统电动汽车集群调度过程中未能充分考虑用户响应度及其影响因素对可调度容量影响的问题,提出了计及用户响应度的电动汽车充放电调度策略。首先基于用户出行数据,对电动汽车集群的充电负荷模型进行建模;其次建立了基于韦伯-费希纳定律的电动汽车用户响应度模型,并综合考虑聚合商设定的充放电价和车辆荷电状态(state of charge,SOC)对用户充放电响应度的影响;最终将聚合商设定的充放电价与电动汽车的充放电功率作为决策变量,统筹考虑电网、聚合商以及电动汽车用户的三方收益,构建以最小化配电网负荷波动、最小化用户充电成本和最大化聚合商收益为目标的电动汽车充放电优化调度模型,采用粒子群优化算法(particle swarm optinization,PSO)求解该优化问题。通过算例结果表明,该模型能够在实现削峰填谷的同时,保证了聚合商以及电动汽车用户的利益。
文摘Currently,oil companies face the "new normal" condition that the profit of their upstream business is shrinking with the plunge of oil price.This problem challenges the operation and management of the upstream business.Therefore,it is essential to find out the new approaches and key points of work,to achieve the goal of realizing a quality and sustainable development.From ten aspects,this paper discusses the challenges facing the upstream business of oil companies and puts forward corresponding roadmaps and strategies.
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.