Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

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.

Optimal Time-of-use Pricing for Renewable Energy-powered Microgrids: A Multi-agent Evolutionary Game Theory-based Approach

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.

Impact of Electric Vehicle Charging on Power Load Based on TOU Price

Large-scale electric vehicle charging has a significant impact on power grid load, disorderly charging will increase power grid peak load. This article proposes an orderly charging mechanism based on TOU price. To build an orderly charging model by researching TOU price and user price reaction model. This article research the impact of electric vehicle charging on grid load by orderly charging model. With this model the grid’s peak and valley characteristics, the utilization of charging equipment, the economics of grid operation can all be improved.

分时电价下的充电站负荷预测

为有效应对分时电价(ToU)策略对充电站的影响,给充电站运营商、电力系统管理者和政策制定者提供科学依据,通过分析历史充电数据、用户行为模式和气象信息,识别定价对用户充电行为的直接影响。针对这一问题,采用一种混合模型,将时间序列模型与用户行为模型相结合。通过设计特征嵌入层等方法引入Transformer模型以更好地捕捉时间序列数据中的复杂模式,而用户行为模型则有助于全面考虑用户充电偏好和响应。实验结果表明,混合模型在充电站负荷预测方面表现了卓越的性能。通过对分时电价的重点关注,成功地预测了未来一段时间内充电站的负荷需求。

分时电价下油田分压周期注水优化研究

为降低由各注水井需求压力不一致导致的阀组节流损失,以泵站总能耗成本最低为目标函数,以站内泵机组及站外注水井服务要求为约束条件,借助数学规划和优化高级建模系统(GAMS)建模编程,调用内嵌分枝减小最优化导航(BARON)求解器求解,建立了一种分时电价下分压周期注水的数学模型。针对实际注水情况,考虑各压力范围注水井组交叉注水与顺次注水2种运行方案,通过对比分析确定了最佳注水方案。研究结果表明,优化后低压注水井组节流损失平均降低约7 MPa,中压注水井组节流损失平均降低约3 MPa,分时分压周期注水方式一周期内能耗成本可降低约13000元,极大降低了现场因节流损失带来的能耗成本,具有良好的经济效益。同时,顺次注水相较交叉注水具有更好的实用价值与可操作性,可为现场实际运行生产提供一定参考。

基于充电预约与分时电价的带时间窗电动车辆路径问题研究

本文考虑充电预约和分时电价,将客运需求的电动车辆路径问题建模为0-1的整数规划模型。模型中目标函数是最小化总运营成本,约束条件主要包括车辆路径约束、分时电价约束、充电预约约束等。基于遗传算法框架,设计了1个求解算法,计算后得出结论:(1)考虑分时电价时,EV充电时间会尽可能集中于电价低谷期;(2)进一步考虑充电预约,EV的总运营成本减少6.74%。

A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering Hot Dry Rock Co-Generation

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.

基于改进量子遗传算法的光伏智能楼宇负荷优化

针对楼宇用电负荷优化的问题,考虑用电成本、储能折损、用电舒适性和电网侧峰谷差波动的因素,提出一种多目标动态规划的办公楼宇负荷优化模型。结合分时电价建立楼宇净用电成本最小的目标函数,采用改进旋转门动态调整的量子遗传算法进行求解,通过动态调整量子旋转门,改变量子态的概率,提高了量子遗传算法求解的精确度;在保证得到全局最优解的同时完成负荷优化和供给侧的能量调度。实验结果表明,所提算法保证了用电舒适性,有效降低了楼宇用电成本和储能装置的折损费用,具有良好的经济收益;在降低峰谷差方面也起到了较好的效果。

一种基于回归方程的峰谷分时电价模型

峰谷分时电价是在不同时间段实施不同价格,由此达到削峰填谷、平衡负荷的目的。鉴于表示用户对电价响应的方法较少,而传统负荷电价弹性矩阵存在获取困难的问题以及缺少指标验证其精确性,创新性地提出建立含高次项与交互项的多元回归模型来反映用户对电价的响应,并分别从供给侧和需求侧考虑,建立了基于回归方程的峰谷分时电价优化模型。根据新加坡能源市场公司提供的负荷与电价数据,分别对基于负荷电价弹性矩阵和基于回归方程的多目标优化问题进行算例分析,对比两种模型并验证了基于回归方程模型的可行性和有效性。

Power ＂Smart Pricing＂ with and without Smart Meters

Over the past several years, the Taiwan Power Company has launched two smart pricing programs to assess the demand response of residential customers： the TOU （time-of-use） rate scheme and the DRI （demand reduction incentive） scheme. This paper discusses these two programs and evaluates their respective performances. We develop an efficient approach based on marginal cost pricing to redesign the TOU rate scheme. In our finding, the TOU price levels could be revised to encourage more customers to participate by enlarging the price gap. Moreover, the DRI scheme can be further improved in order to reach an efficient win-win solution among customers, the utility and society. This can be achieved via a careful design of incentive tariff discounts to take account of the time-of-use or location-specific features of the power supply/demand condition.

基于用户响应的分时电价策略研究

针对因不恰当电价政策改变负荷曲线的峰谷特性而引起的用电时段需要频繁重新划分的问题,首先,引入弹性效应权重对需求价格弹性矩阵进行改进,建立了用户响应模型。然后,基于模糊聚类对负荷峰谷时段进行了划分。最后,以负荷峰值和负荷波动系数最小为目标,建立了峰谷分时电价的决策模型,讨论了峰谷倒置对优化结果的影响。结果表明,应用所提模型可使负荷曲线保持原有峰谷特性,同时可使负荷波动有效降低。

Time-of-use Pricing Model Considering Wind Power Uncertainty

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.

考虑分时电价机制的微电网优化调度

微电网作为消纳清洁能源的重要途径,优化调度直接影响微电网系统的稳定性与经济性。对微电网各部分进行了详细数学建模,同时引入分时电价机制,综合考虑微电网系统运行约束,建立了多目标优化模型,并调用商业求解器cplex对优化模型进行求解。以某地微电网数据为例进行运行仿真,结果表明该优化模型在考虑环保的同时对经济性有明显提升。

Battery electric buses charging schedule optimization considering time-of-use electricity price

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.

Short-term Scheduling of Steam Power System in Iron and Steel Industry under Time-of-use Power Price

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.

基于改进粒子群算法的综合能源系统经济优化运行

针对综合能源系统的最优经济化运行,将整个系统分为新能源供应商、综合园区服务商、用户三个主体,以新能源供应商收益最大化,园区服务商收益最大化,用户购能成本最小化为综合目标,建立基于分时电价的综合能源系统经济优化模型。改进传统的粒子群算法,用所有粒子的个体最优值的平均值代替个体最优值,提高算法的精准度。利用改进后的粒子群算法对模型进行求解,并通过算例进行验证分析。

基于用户对电价反应曲线的分时电价的研究

运用统计学原理对用户进行调查,拟合不同类型用电对电价反应的曲线,得到全社会对电价的综合反应曲线。建立基于用户对电价反应曲线的分时电价模型,并运用MATLAB计算了不同需求侧管理目标下的最优分时电价方案,验证模型优化负荷曲线的可行性。

峰谷分时电价的实施及大工业用户的响应

峰谷分时电价是实施需求侧管理的措施之一。文中利用电价理论及有关经济学原理阐述了峰谷分时电价的结构、定价策略以及大用户响应的经济计量模型 ,并对南京市实施峰谷分时电价以来部分大工业用户的响应进行了分析。通过对一些重点用户的响应分析 ,认为合理的峰谷电价结构能收到较好的负荷调整效果 。

促进风电消纳的发电侧、储能及需求侧联合优化模型

将需求侧响应与储能技术纳入发电调度优化,借助需求侧管理与储能技术对负荷分布的调控能力提高风电的消纳水平。以经济效益最大化为优化目标,考虑功率供需平衡、用电侧电价弹性、储能系统能量损耗、机组启停时间、爬坡能力、发电出力界限、发电备用等约束条件,构建含大规模风电的电力调度模型。模拟结果表明,借助需求侧与储能技术的协作效应,系统对风电的消纳能力将有所提高,风电机组的经济效益将更有保证,系统的发电煤耗水平有所下降。

峰谷分时电价的分析与建模

分时电价是实现电力需求侧管理预期目标的一项重要举措。从湖南省分时电价的应用现状出发,基于在发电侧引入竞争、实行发电竞价上网的改革取向,提出了适宜湖南电网采用的需求侧和上网侧电价联动的分时电价模型,并据此确定了丰枯季节性电价,为市场化改革后湖南电网电价体系的构建提供了参考依据。