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.

Effects of iron electrovalence and species on growth and astaxanthin production of Haematococcus pluvialis

To increase the cell concentration and the accumulation of astaxanthin in the cultivation of Haematococcus pluvialis, effects of different iron electrovalencies （Fe^2＋-EDTA and Fe^3＋-EDTA） and species （Fe-EDTA, Fe（OH）x^32x and FeC6H5O7） addition on cell growth and accumulation of astaxanthin were studied. Results show that different iron electrovalencies have various effects on cell growth and astaxanthin accumulation of H. pluvialis. Compared with Fe^3＋-EDTA, Fe^2＋-EDTA stimulate more effectively the formation of astaxanthin. The maximum astaxanthin content （30.70 mg/g biomass cell） was obtained under conditions of 18 μmol/L Fe^2＋-EDTA, despite the lower cell density （2.3×10^5 cell/ml） in such condition. Fe^3＋-EDTA is more effective than Fe^2＋-EDTA in improving the cell growth. Especially, the maximal steady-state cell density, 2.9×10^5 cell/ml was obtained at 18 μmol/L Fe^3＋-EDTA addition. On the other hand, all the various species of iron （EDTA-Fe, Fe（OH）x^32x, FeC6H5O7） are capable to improve the growth of the algae and astaxanthin production. Among the three iron species, FeC6H5O7 performed the best. Under the condition of a higher concentration （36 μmol/L） of FeC6H5O7, the cell density and astaxanthin production is 2 and 7 times higher than those of iron-limited group, respectively. The present study demonstrates that the effects of the stimulation with different iron species increased in the order of FeC6H5O7, Fe（OH）x^32x and EDTA-Fe.

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.

Hybrid Deep Learning Architecture to Forecast Maximum Load Duration Using Time-of-Use Pricing Plans

Load forecasting has received crucial research attention to reduce peak load and contribute to the stability of power grid using machine learning or deep learning models.Especially,we need the adequate model to forecast the maximum load duration based on time-of-use,which is the electricity usage fare policy in order to achieve the goals such as peak load reduction in a power grid.However,the existing single machine learning or deep learning forecasting cannot easily avoid overfitting.Moreover,a majority of the ensemble or hybrid models do not achieve optimal results for forecasting the maximum load duration based on time-of-use.To overcome these limitations,we propose a hybrid deep learning architecture to forecast maximum load duration based on time-of-use.Experimental results indicate that this architecture could achieve the highest average of recall and accuracy(83.43%)compared to benchmark models.To verify the effectiveness of the architecture,another experimental result shows that energy storage system(ESS)scheme in accordance with the forecast results of the proposed model(LSTM-MATO)in the architecture could provide peak load cost savings of 17,535,700 KRW each year comparing with original peak load costs without the method.Therefore,the proposed architecture could be utilized for practical applications such as peak load reduction in the grid.

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.

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.

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.

变价元素在找矿评价工作中的意义和指示作用

自然界中的变价元素广泛存在,不同价态的元素具有不同的地球化学性状,反映了不同的氧化还原环境,在成矿过程中形成各具特征的元素组合和矿物组合。利用Eh—pH图解和部分变价元素不同价态地化特征,分析自然界中矿物的稳定性和不同价态元素的共存关系及迁移能力,从中提炼找矿信息,有利于提高野外找矿评价工作成果质量。

钾、钠交代作用与铀、金、铁等内生金属矿产的关系

本文详细论述了钾、钠交代作用的矿物特征和地球化学特征，指出钾、钠交代作用的主要方式是渗透交代和液固相交代。主要表现特征是以钾长石或钠长石矿物假象交代原岩中的其它矿物；钾、钠交代作用与Ｕ，Ａｎ，Ｆｅ，Ｗ，Ｃｕ，Ｎｂ，Ｔａ等内生矿产成矿的密切关系，是由钾、钠元素本身的地球化学特征决定的。

电力体制改革和电力市场对南方电网影响分析

电力体制改革和电力市场对电力系统的影响是当前电力系统的研究热点。对电力市场环境下南方电网有限责任公司(以下简称南方电网)的定位、体制、经营等方面带来的影响进行了分析与讨论。电力市场环境下,南方电网应由输配售一体化向输配一体化转变。为适应这个角色转变,需要进一步厂网分离和输配分离。由此对南方电网的运营产生了深刻影响,需要在输配电价的构成分析和制定方法方面争取自身利益的最大化,最后对南方电网应对市场化改革提出了相关建议。

光储联合系统中储能电站的能量管理

为提高储能设备利用率,实现储能电站能量的合理管理,以浙江地区某光伏电站配置的MW级储能电站示范工程为背景,针对现有单应用模式下储能装置容量和功率存在富余的特点,文章提出了一种平抑波动和分时电价相结合的储能装置控制方案。根据光伏出力特点,在光伏波动较强时进行光伏波动平抑,在光伏出力较弱时,根据储能装置剩余容量(state of charge,SOC)的实际情况,结合当地负荷变化曲线,实施分时电价策略。仿真实验表明,该控制方案维持储能设备SOC在合理范围的前提下,能及时平抑白天光伏的波动。同时在一定程度上实现了对负荷的削峰填谷,提高了储能设备利用率,实现了储能电站能量的合理管理,为项目后续示范应用提供了理论依据与技术支撑。

从江水北调的实践看南水北调江苏境内工程实行优待电价的必要性和可行性

45年来,江苏对江水北调工程实行了由省级财政负担工程建设、运行、维修和改造费用和泵站用电享受优待电价的政策。这些政策对于维持工程的正常运用,从而为供水区提供水资源保障起到了关键的作用。针对南水北调东线江苏境内工程省内供水功能的性质和特点,分析了对江苏境内工程省内供水运行实行优待电价的必要性和可行性,指出实行优待电价是南水北调江苏境内工程效益发挥的基础性条件之一。

直接空冷系统优化及参数敏感性分析

按热力学和热经济学原理,给出了直接空冷系统的优化参数和优化目标函数,并对某600MW直接空冷机组进行优化设计分析,参考运行机组的数据计算出了优化结果。对相关变量进行了敏感性分析,所得曲线表明了选取的设计变量和所得优化结果的合理性,而两个经济性参数的敏感性分析表明电价Pe对优化结果影响较大,因此,电价Pe的定值必须合理。

电力企业改革与政府管制

从电力企业自然垄断的客观规律性及所产生的问题分析入手 ,对我国电力企业的产业化分割和政府管制进行研究。研究认为 ,建立有序的市场和充满活力的经济 ,就必须对“电力生产企业”实施电价规制 。

对售电价格管制模型的理论思考

由于电网经营企业的自然垄断,政府必须对其进行管制以提高其效率和社会福利水平。本文从效率和福利两方面通过对四种定价模式进行比较分析,指出拉姆齐定价能在满足企业收支平衡下使社会福利达到最大,分析了拉姆齐定价原则在售电价格管制中的理论研究和应用,结合算例说明拉姆齐定价对于不同用户群之间的差别定价的优越性,并用拉姆齐定价模型对高峰负荷定价和两部制定价进行分析。

国外分时电价政策简介及探究

介绍了法国、美国、日本等国家实行季节、峰谷分时电价以及实时电价的情况,结合江苏南京市的负荷特性给出了实施分时电价的建议,如将峰谷、季节性电价结合起来,合理划分峰谷电价的时段等。

肯尼亚地热发电快速发展之路及对中国地热发电的启示

肯尼亚处于东非大裂谷东支,在现代火山作用下富集了丰富的地热资源。奥卡瑞地热田是当前肯尼亚开发的主要火山型高温地热系统,热储以凝灰岩和粗面岩为主,平均温度235℃,储层厚度大于500m。近20年来,肯尼亚政府大力支持地热发电产业发展,专门成立了地热勘探开发公司承担前期勘探开发工作,鼓励开发商办理矿权,从资金、立法和电价补贴等方面出台促进地热产业发展的政策,同时积极开展国际合作,获取国际支持。至2020年底,肯尼亚地热发电装机达到865MW,并计划到2030年达到5000MW。中国以中低温地热资源为主,高温地热资源则主要集中在藏南-川西-滇西地区和中国台湾地区。中国地热发电虽然起步较早,但由于资源与需求不匹配以及缺少扶持政策等因素限制,近30年发展基本停滞,至2020年底在运装机容量仅44.56MW,远未达到"十三五"规划发展目标。针对中国地热发电产业存在的问题,建议政府下力气摸清资源家底,成立地热勘探资金;支持矿权办理,理顺管理流程;出台积极的地热发电政策,明确发电标杆电价;同时进一步攻关地热发电核心技术和关键装备。

基于共赢策略下的居民阶梯电价设置的定量评估

针对阶梯电价收费标准的制定问题和节水设备能否降低居民水电费的判别问题,以双收益双赢策略和费用较小化原则为切入点,通过最佳双向满意度的方法,建立了最佳收费标准模型;运用Matlab和Excel软件,得出了适合A、B两小区最佳的收费标准,并利用差值法建立费用较小化模型,得到节水设备可降低居民水电费的判别方法。

抽水蓄能电站的作用及两部制上网电价测算方法探讨

介绍了抽水蓄能电站在电力系统中的作用，分析了抽水蓄能电站现行上网电价测算方法存在的问题。

电熔刚玉和锆刚玉中变价态氧化物存在价态的ESR分析

对影响刚玉、电熔锆刚玉 (FCAZS)中变价态氧化物存在价态的因素之一的熔炼气氛 ,以及变价态氧化物存在价态的测定方法进行了研究。研究结果证实 ,致密电熔刚玉和还原法生产的FCAZS制品中 ,变价态氧化物确实是以低价态存在的 ,而电子自旋共振法 (ESR)是定性或半定量分析变价态氧化物杂质存在价态的有效手段。