Electric Vehicle Charging Load Optimization Strategy Based on Dynamic Time-of-Use Tariff

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.

Scheduling optimization problem considering time-of-use tariffs and piece-rate machine maintenance in EAF steelmaking

An operating schedule of the parallel electric arc furnaces(EAFs)considering both productivity and energy related criteria is investigated.A mathematical model is established to minimize the total completion time and the total electricity cost.This problem is proved to be an NP-hard problem,and an effective solution algorithm,longest processing time-genetic(LPT-gene)algorithm,is proposed.The impacts of varied processing energy consumption and electricity price on the optimal schedules are analyzed.The integrated influence of the different weight values and the variation between the peak price and the trough price on the optimal solution is studied.Computational experiments illustrate that considering the energy consumption costs in production has little influence on makespan;the computational performance of the proposed longest processing time-genetic algorithm is better than the genetic algorithm(GA)in the issue to be studied;considerable reductions in the energy consumption costs can be achieved by avoiding producing during high-energy price periods and reducing the machining energy consumption difference.The results can be a guidance for managers to improve productivity and to save energy costs under the time-of-use tariffs.

电动汽车参与V2G的最优峰谷电价研究

电动汽车与电网互动(vehicle-to-grid,V2G)的市场机制是V2G实施的重要基础。在分析电动汽车放电成本和效益的基础上,给出了电动汽车放电电价定价的上下限。考虑了用户起始充放电时刻的Poisson分布特性,基于经济学理论提出了电动汽车放电需求函数。建立了以电网总负荷波动最小为目标,以满足用户充放电时间、充放电需求等为约束条件的电动汽车与电网互动的最优峰谷电价模型。以京津唐电网为例,得到了电动汽车充放电的最优峰谷电价和对应时段,验证了所提方法的有效性。

一种可操作的需求侧管理峰谷分时电价定价方法

运用经济学原理研究了峰谷分时电价的市场效应,建立了基于电力需求价格弹性矩阵的峰谷分时电价数学模型,提出了电网总售电收入(用户电费支出)对电网负荷变化的反应灵敏度概念。通过对该模型的目标函数进行优化,得到了一种可操作的峰谷分时电价定价方法。算例仿真分析表明所提出的分时电价定价方法是切实可行的,它有利于减小电网的高峰负荷,改善负荷曲线,提高系统运行的可靠性和经济性,实现资源的优化配置和电力工业的可持续发展。

浅析阶梯电价对供电企业的影响及对策

国家发改委拟推行的居民生活用电阶梯电价引起了社会的广泛关注,这也对供电企业提出了新的要求。通过对政策的解读,初步分析了实行阶梯电价可能对供电企业在计量系统、抄表管理、核算管理、运行管理和经营管理等方面的影响,并提出一些管理和技术方面的应对措施,为实行居民生活用电阶梯电价的供电企业提供参考。

分时电价政策影响上海城镇居民用电的定量分析

居民分时电价是削峰填谷的重要手段,但效果很难量化.通过从上海市用电营销数据库中抽取分别代表高、中、低端用户的3个典型小区居民的用电数据,建立居民谷电段用电倾向的数学模型.该模型包括谷电量占日电量比例、谷电量增长、平电量增长、电费支出增长等指标.结果表明,分时电价政策促进了居民用电量的增长,大部分居民倾向于谷时段用电,填谷效果较为明显.

分时电价对上海城镇居民用电的影响研究

居民分时电价是削峰填谷的一项重要手段,但效果很难衡量.通过向高、中、低端用户发放调查问卷,分析家电因素、人均居住面积对居民谷电消费倾向的影响,以及由此产生的电量和电费支出的变化,结果表明:分时电价的政策促进了居民用电量的增长,居民倾向于谷时段用电,中端用户削峰填谷的效果最明显.

淮南市居民分时电价实施效果分析

为了解淮南市居民分时电价政策的实施效果,从淮南市供电局用电营销数据库提取相关数据,按用电量将用户分成3类,分析各类用户的户均月谷电系数、户均谷电量增长、户均平电量增长、户均电费支出等指标。结果表明,分时电价政策以价格为杠杆,促进了居民用电量的增长,使大部分居民倾向于在谷时段用电,填谷效果明显。

电价调节电动汽车负荷的微电网经济调度研究

针对含电动汽车负荷的微电网经济调度问题,提出了采用动态电价调节电动汽车负荷的微电网调度策略的求解方法。在分析固定电价下电动汽车负荷计算后,建立了一个调度周期内电动汽车负荷对电价变化的响应模型,反映了动态电价对电动汽车负荷的影响。根据响应模型,建立了含电动汽车、多种微电源和负荷的微电网成本最小的优化调度模型,并采用粒子群算法(PSO)进行求解调度策略。算例表明,所提调度策略能引导微电网中电动汽车有序充电,实现负荷削峰填谷,降低微电网运行成本。

分时电价下多目标绿色可重入混合流水车间调度

针对多目标绿色可重入混合流水车间调度问题(RHFSP)的特点,在机器分配和工序排序的基础上引入分时电价机制,构建了以最小化最大完工时间、总能耗成本和碳排放为目标的绿色调度优化模型,提出了一种改进的多目标文化基因算法(MOMA)来求解该问题,通过数值实验验证了所设计的MOMA算法的可行性。实验结果表明MOMA算法在非劣解的收敛性、多样性和支配性指标方面都显著优于多目标蚁狮优化算法(MOALO)、多目标粒子群优化算法(MOPSO)和带精英策略的非支配排序遗传算法(NSGA-Ⅱ),四种算法的分布性指标无显著差异。所提出的模型能够使企业有效避开高电价时段作业,合理转移用电负荷,达到降低总用电成本和碳排放的目的。

峰谷电价政策对发电公司和电网公司效益的影响

针对峰谷电价政策实施后发电企业、电网企业出现的效益变化及收益转移等问题,通过实例分析和理论分析,从不同角度探讨了这一政策实施后对发电公司和电网公司效益的影响。其中理论分析模型较好地描述了峰谷电价政策对发电公司和电网公司的效益影响,可为政府部门在制定峰谷电价政策时提供参考。

爱尔兰中小型电力用户的智能用电行为分析

爱尔兰智能电能表试点项目中的用户行为试验对象主要为居民用户和中小型商业用户,试验探讨了分时电价、各类信息反馈技术、其他差异化因素对用户减少总用电量及高峰用电量的影响。通过对试验设计的详细阐述,分析了执行不同激励机制的试验组、不同社会群体、不同企业类型用电行为的试验结果,并探讨了造成结果差异化的原因,分析了影响试验实行效果的潜在障碍,对挖掘不同需求响应对象的响应潜力和设计需求响应项目有着现实指导意义。

集群电动汽车充电行为的深度强化学习优化方法

随着用电信息采集系统的推广,数据驱动的机器学习方法在用户侧用电行为优化领域的应用已引起广泛关注。利用深度强化学习方法(deep reinforcement learning,DRL),基于充电监测系统实时反馈的数据与分时电价信号,从负荷聚合商层面优化电动汽车(electric vehicles,EVs)充电行为。通过双延迟深度确定性策略梯度算法(twin delay deep deterministic policy gradient,TD3)对单辆电动汽车充电过程进行建模。通过在训练智能体时向其状态中引入随机噪声,该模型获得了对不同状态下的电动汽车充电行为的泛化控制能力。通过将训练得到的智能体进行分布式部署,该方法实现了对集群电动汽车充电行为的快速实时优化,其效果在算例中得到了验证。

营口地区调整大工业电价政策探讨

营口地区现行大工业电价的不完善使特殊行业用电负荷曲线出现大峰谷差、低负荷率的现象。按需求侧管理理念,针对营口地区电熔镁用电负荷在现行大工业电价引导下形成的低负荷率、大峰谷差问题进行了分析,提出调整大工业电价政策的设想,包括提高基本电价比例和增加负荷率调整电费。通过调整大工业电价,旨在以电价政策为引导,以经济利益为杠杆,调整电力负荷峰谷差,促进电网和国民经济健康、协调发展。

A framework for stochastic estimation of electric vehicle charging behavior for risk assessment of distribution networks

Power systems are being transformed to enhance the sustainability.This paper contributes to the knowledge regarding the operational process of future power networks by developing a realistic and stochastic charging model of electric vehicles(EVs).Large-scale integration of EVs into residential distribution networks(RDNs)is an evolving issue of paramount significance for utility operators.Unbalanced voltages prevent effective and reliable operation of RDNs.Diversified EV loads require a stochastic approach to predict EVs charging demand,consequently,a probabilistic model is developed to account several realistic aspects comprising charging time,battery capacity,driving mileage,state-of-charge,traveling frequency,charging power,and time-of-use mechanism under peak and off-peak charging strategies.An attempt is made to examine risks associated with RDNs by applying a stochastic model of EVs charging pattern.The output of EV stochastic model obtained from Monte-Carlo simulations is utilized to evaluate the power quality parameters of RDNs.The equipment capability of RDNs must be evaluated to determine the potential overloads.Performance specifications of RDNs including voltage unbalance factor,voltage behavior,domestic transformer limits and feeder losses are assessed in context to EV charging scenarios with various charging power levels at different penetration levels.Moreover,the impact assessment of EVs on RDNs is found to majorly rely on the type and location of a power network.

基于用户用电特性及供电成本分摊的销售侧电价机制研究

针对现行销售电价机制中用户分类不够科学规范、繁简不当的问题,借助模糊C均值算法,根据用户的典型日负荷曲线对用户进行分类并得到了典型用户负荷率曲线及用电参数。在此基础上,考虑用户需求响应建立了分时电价的最优化模型,分别计算分析了在峰荷最小、谷荷最大和峰谷差最小三种优化目标下的负荷曲线及各方收益变化。结果表明,在执行所设计的分时电价后,削峰填谷、改善负荷曲线的目标得以实现,有效缓解了电力供应高峰时段的负荷缺口,同时各方收益也得到了保证。