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.

Cross-Subsidy in Electricity Tariffs in China

With the incessant development of power market reform,the existing cross-subsidy in electricity tariffs has become a critical problem in China's power industry development.On the basis of the theories of cross-subsidy and electricity universal service,the authors take foreign countries' experience as reference to design several solutions to cross-subsidies in electricity tariffs in different phases of China's power industry development.Furthermore,the application and implementation of these solutions are analyzed in this paper.

Analysis of Nigerian Electricity Generation Multi Year Tariff Order Pricing Model

The Multi Year Tariff Order (MYTO) is the Nigerian Electricity Regulatory Commission (NERC) pricing framework for determining the Nigerian Electricity Supply Industry (NESI) pricing model. One of the objectives of the NERC’s MYTO pricing model is to ensure regulated electricity end user tariff without compromising return on investment. Achieving this objective is imperative to attract investors in the growing Nigerian electricity market. However, NESI has hitherto been faced with challenges ranging from its inability to provide sufficient power to its customers to not being viable enough to provide return on capital invested. In this paper, sensitivity analysis of power plant operation and performance parameters on the cost of electricity (CoE) generation using MYTO (power generation) pricing model were evaluated. Thermodynamic modeling and simulation of an open cycle gas turbine (OCGT) was carried out to augment scarce data on power plant performance and operation in Nigeria. Sensitivity analysis was carried out using probabilistic method based on Monte Carlo simulation (MCS) implemented in commercial software (@ Risk®). The result highlighted sensitivity of the model input parameters to cost of electricity generation based on technical and financial assumptions of MYTO model. Seven most influential parameters affecting generation cost were identified. These parameters and their correlation coefficients are given as: 1) foreign exchange rate, 0.76;2) cost of fuel, 0.51;3) thermal efficiency, -0.23;4) variable operation and maintenance cost, 0.22;5) fixed operating and maintenance cost, -0.03;6) capacity factor, -0.02;and 7) average capacity degradation, 0.01. Based on the gas turbine engine and input parameter distributions statistics for this study, the generation cost lies between 9.84 to 15.45 N/kWh and the probabilities of CoE within these values were established.

Online Fuzzy Logic Base Algorithm for Electricity Price Prediction

This paper presents a web-based system to predict the electricity prices.The proposed system captures the geographical location,weather forecast,and oil price for one week ahead.The captured parameters are fed to a fuzzy-logic-based algorithm to calculate electric energy prices.Based on predicted electricity prices,consumers can turn ON/OFF or reschedule operations of their home appliances to reduce their electricity bill.The proposed algorithm was developed and hosted in a utility server(U-server).On the consumer side,a home gateway(H-gateway),and a monitoring and control system was designed,built,and tested by using a single chip microcontroller.

Factors Affecting Electricity Demand in Jordan

1) The paper examines the relationship between electricity demand and climate/non-climate related factors using statistical regression analysis. 2) It focuses on the environmental, demographic, policy (energy pricing) and technological factors as the main factors affecting the consumption pattern in Jordan. 3) The paper also presents the variations occurred in the electricity demand over the period 1994-2008. The variations that are observed during the period of study are: Shifting of the peak load occurrence from evening to morning period, Modification in the annual daily load curve especially in winter season, Variation in relationship between space temperature and demand especially in winter, and dramatic increase in electric generation after year 2003. The shift in peak load from evening to morning period is mainly due to technological factor as a result of wide use of the air conditions in houses, services and government offices for cooling in summer instead of ordinary air fans. The variations in consumption pattern between 2000 and 2007 are mainly associated with economic, social and demographic factors. The high demand at lower space temperature is governed by introducing new appliances for heating in winter as a result of low electricity pricing comparing with gasoline price. The dramatic increase in electric generation after 2003 is probably due to demographic factors as a result of high growth of population after the Gulf war II. 4) The correlation between the daily maximum loads in morning and evening periods with the differential temperature (ΔT) above 20?C threshold in summer and below 15?C threshold in winter, shows pronounced changes in 2007 compared with year 2000. The regression tests show that a decrease of 1?C below 15?C threshold in winter 1) increases the morning demand by only 2 MW/?C in 2000 and 16.7 MW/?C in 2007, 2) decreases the evening peak by ?2.6 MW/1?C in 2000 and increases the evening peak by 22.9 MW/1?C in 2007. Results show that the demographic, technological, environmental and national energy pricing factors play a vital rule in consumption pattern in Jordan. Moreover, the paper reveals that planners and decision makers should be careful when applying new tariff in the developing countries such as Jordan.

A Review of the Characteristics and Challenges of Electricity Distribution in Ghana: Case Study of the Northern Electricity Distribution Company

This paper presents a review of the characteristics and challenges of electricity distribution in Ghana with an emphasis on the Northern Electricity Distribution Company (NEDCo) in the northern half of Ghana. NEDCo is used as a case study due to the peculiarity of its geographical area of operation and customer characteristics which better highlights the challenges of electricity distribution in Ghana. NEDCo’s electricity distribution operations cover approximately 64% of the total landmass of Ghana and contain the most deprived communities and consumers, who are extensively dispersed. In addition to the scattered settlements, NEDCo has a predominantly lifeline customer base that pay tariffs below the average cost of service. These peculiarities, together with regulatory complexities, have contributed to many challenges, such as high system losses, high cost of service and poor network reliability, in the electricity distribution sector in Ghana.

Sustainability on Energy Governance: Recent Trends of the Electricity Sector in Azerbaijan

Our aim is to analyze sustainability on energy governance,recent trends of the electricity sector in Azerbaijan,in particular,the degree of efficiency of the electricity system and the tariff structure to give recommendations for future development and perspectives of energy sector development in Azerbaijan.We argue that government policy should be oriented towards identification of those factors that seek energy efficiency for sustainable development,uncover several laws,ensuring energy security,and encourage electricity market.Besides that by comparing electricity tariffs in Azerbaijan with some other European countries,we find advantages in the Azerbaijan-EU partnership on the energy field,thus we propose appropriate forms of cooperation regarding to European Neighborhood Policy.

Challenges of Renewable Forest Fuels for Green Electricity Market

In this study, strategic electricity market scenarios are considered in a grid of Scandinavia. This multiple-objective decision environment includes the allocation of a number of renewable forest fuel procurement chains to a combined heat and power plant in Finland. The decision environment includes also electricity procurement from Sweden and Russia. The environment is further complicated by sequence-dependent operations of the local procurement chains during different periods. Due to the complex nature of the environment, multiple-objective methods cannot be directly used to solve the electricity production problem in a manner that is techno-economically relevant to the forest energy industry. Therefore, local and time-varying parameters were measured in local wood procurement conditions to improve the solution method. Using these measurements the smart decision-support system automatically adjusted the multiple-objective methodology to better describe the combinatorial complexity of the production sector. The properties of this methodology are discussed and three scenarios of how the system works based on local real-world data and optional feed-in tariff of green electricity are presented. The Finnish electricity market is subject to policy decisions regarding green energy production regulations. These decisions should be made on the basis of local techno-economic analysis presented in this study accounting for the effects of forest operations on the electricity production and import.

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.

Power Optimization Strategy Considering Electric Vehicle in Home Energy Management System

With the development of smart grid, residents have the opportunity to schedule their household appliances （HA） for the purpose of reducing electricity expenses and alleviating the pressure of the smart grid. In this paper, we introduce the structure of home energy management system （EMS） and then propose a power optimization strategy based on household load model and electric vehicle （EV） model for home power usage. In this strategy, the electric vehicles are charged when the price is low, and otherwise, are discharged. By adopting this combined system model under the time-of-use electricity price （TOUP）, the proposed scheduling strategy would effectively minimize the electricity cost and reduce the pressure of the smart grid at the same time. Finally, simulation experiments are carried out to show the feasibility of the proposed strategy. The results show that crossover genetic particle swarm optimization algorithm has better convergence properties than traditional particle swarm algorithm and better adaptability than genetic algorithm.

On-Grid Tariff in China——History, Current Situation, and Proposed Reform

This article introduces the history of the reform of on-grid tariff in China, the current status of and currently adopted mechanisms related to on-grid tariffs of coal-fired and renewable energy power generation facilities. The article further discusses the proposed and on-going reform and restructure in the electricity price sector, and the trial reforms in regional electricity markets.

Estimating the Impacts of Nuclear Phase-out and FIT on Tokyo Electric Power Company Jurisdiction

This study examines the effects of nuclear phase-out and newly implemented FIT （feed-in tariff） at the TEPCO （Tokyo Electric Power Company） jurisdiction. A power generation mix linear programming model is developed for the TEPCO jurisdiction up to 2030. Three results are found from this analysis. First, coal-fired power plants compensate for an abolishment of nuclear power generation when power mix is analyzed to maximum profits. Second, it is clarified that FIT provides competitiveness to wind power for potential and photovoltaics at the location where 15% of efficiency is expected at the TEPCO jurisdiction. Third, implementing FIT can decrease fossil-fuel dependency and CO2 emissions as much as planned nuclear power generation. However, system costs increase 4.61 trillion.

RCEP框架下关税减让对中国机电产品出口的影响研究——基于GTAP模拟分析

机电产品是中国与RCEP成员国贸易往来中的重要出口产品,运用显示性比较优势指数、贸易竞争优势指数和贸易互补性指数,探讨2012—2022年中国与其他RCEP成员国机电产品的贸易竞争性和互补性。在此基础上,运用GTAP软件分析关税减让对中国机电产品出口的影响。研究发现:RCEP框架下关税减让有利于中国机电产品出口规模的扩大,且长期带来的效果比短期更显著;关税减让产生的贸易创造效应和贸易转移效应十分明显,具体表现为从RCEP域外国家转移至域内;关税减让对中国不同种类机电产品出口的影响有所不同,提出了加强汽车领域交流与合作,加快机电产业结构优化升级,制定差异化出口战略等对策建议。

欧盟对中国电动汽车实施反补贴调查的影响及对策

中国逐步掌握了全球汽车产业电气化和智能化转型话语权,对以美日欧为主的传统汽车产业格局产生了冲击,难免会遭遇各种形式的贸易保护主义。欧盟作为我国主要电动汽车企业出口目的地,已于2023年9月13日宣布对中国电动汽车展开反补贴调查。虽然此举无法从根本上阻止我国电动汽车产业全球化进程,但可能在短期内会破坏市场预期,干扰我国电动汽车企业的经营决策和业务布局并提高未来进入欧盟市场门槛和成本,需要警惕并在窗口期内做好应对准备。

多能源混合车队生鲜品配送车辆路径问题研究

针对同时考虑取送货和分时电价的电动车与燃油车混合车队车辆路径问题,以车辆固定成本、行驶成本、制冷成本、货损成本、时间窗成本、碳排放成本和充电成本之和最小为目标,构建生鲜品配送车辆路径优化模型,设计融合邻域搜索的遗传模拟退火混合算法并求解。结果表明:相比于取送分离,同时取送货模式能够显著提升配送效率,提高车辆装载率;通过技术升级适当增加电动车的电池容量,能够弱化车辆路径方案对充电设施的依赖程度,有效降低配送成本;通过与遗传算法、遗传变邻域混合算法运行结果对比,验证本文算法的有效性,为冷链物流企业在配送环节实现节能减排、降本增效提供借鉴和参考。

省间电力现货交易优化设计与定价机制

在“碳达峰·碳中和”的目标驱动下,受新能源地理分布与随机性影响,以跨区域交易为媒介的区域间电能与灵活性互济重要性凸显。目前,中国正处于构建全国统一电力市场体系的关键阶段,需要有效的市场机制来管理省间电力现货交易。基于上述背景,设计了一种不依赖于跨区域投标者的省间电力现货交易方法。首先,提出了基于报价区的市场出清模型,采用分区边际定价的方法计算每个报价区的结算价格;然后,基于等效双边配对方法,按潮流贡献计算得到各区域间交易所需承担的输电费用;最后,采用算例验证了所提方法的有效性。与已有方法相比,所提方法在不依赖于跨区域投标者的前提下完成了跨区跨省电力交易,充分利用了输电线路容量,且市场出清过程中保护了各区域内部网架信息隐私。

基于风电分时电价的虚拟电厂参与清洁供暖运营优化方法

随着“碳达峰、碳中和”目标的提出,迅速发展的风电由于其随机性与波动性,面临突出的风电消纳问题。蓄热式电采暖作为中国北方地区主要供暖设备,虚拟电厂作为需求侧资源的主要聚合技术手段,聚合蓄热式电采暖的虚拟电厂可为消纳风电、提高风电利用率提供解决途径。对此,提出一种基于风电功率的分时电价划分方法,实现虚拟电厂聚合蓄热式电采暖参与基于分时电价的清洁供暖交易优化运营。首先,阐述虚拟电厂聚合蓄热式电采暖用户参与风电供暖的交易模式;其次,考虑热惯性对蓄热式电采暖和房屋进行精细化建模,提出基于层次凝聚聚类算法的分时电价方法,建立基于Weber-Fechner定律的负荷模糊响应模型,并构建多方主体综合收益最大、弃风量最小和负荷波动最小的虚拟电厂多目标运营优化模型;最后,通过算例分析风电消纳效果和虚拟电厂收益,验证该方法能够有效促进风电消纳、提高多方主体积极性,并具有一定的规模经济性,以期为缓解弃风问题提供参考。

输配电价改革背景下两部制电价的应用现状与发展前景

在输配电价机制改革的背景下,现有两部制电价无法合理反映电力用户真实用电成本的弊端逐渐显露.两部制电价机制承担着分配电力发电、输送、配电、出售电价空间和调节电力系统的资源等重要功能,亟需对现有两部制电价做出改进与完善.本文围绕两部制电价机制展开分析和讨论.首先,介绍两部制电价的基本理论和计费比例,研究基于不同负荷率和电压等级分摊输配电成本的方法.然后,针对两部制电价的收取方式,分别对负荷率套餐、分时电价等电量电价机制以及电费和负荷调整、改进计价比例等基本电价机制进行总结归纳.在此基础上,结合美国、法国、日本等国外两部制实践经验,分析两部制电价机制理论的执行方式.最后,提出我国两部制电价机制的未来发展方向和建议.

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.