Charging Ahead with E-Buses: Benefits, Costs, and Transition Roadmap

This paper reaches a recommendation for the 10-year e-bus transition roadmap for New York City. The lifecycle model of emission reduction demonstrates the ecological and financial impacts of a complete transition from the current diesel bus fleet to an all-electric bus fleet in New York City by 2033. This study focuses on the NOx pollution, which is the highest among all major cities by Environmental Protection Agency (EPA) and greenhouse gases (GHG) with annual emissions of over five million tons. Our model predicts that switching to an all-electric bus fleet will cut GHG emissions by over 390,000 tons and NOx emissions by over 1300 tons annually, in addition to other pollutants such as VOCs and PM 2.5. yielding an annual economic benefit of over 75.94 million USD. This aligns with the city mayor office’s initiative of achieving total carbon neutrality. We further model an optimized transition roadmap that balances ecological and long-term benefits against the costs of the transition, emphasizing feasibility and alignment with the natural replacement cycle of existing buses, ensuring a steady budgeting pattern to minimize interruptions and resistance. Finally, we advocate for collaboration between government agencies, public transportation authorities, and private sectors, including electric buses and charging facility manufacturers, which is essential for fostering innovation and reducing the costs associated with the transition to e-buses.

Electricity Consumption and Economic Growth in the Beijing-Tianjin-Hebei Agglomeration of China

Nowadays, increased attention is being paid to the causal relationship between electricity consumption and economic growth. This paper attempts to examine the causal relationship between electricity consumption and economic growth for China＇s Beijing-Tianjin-Hebei agglomeration, using annual data covering the period 1982- 2008. In this study, unit root tests, the Johansen co-integration test, and the Granger causality test are applied. The empirical results indicate that the two series （electricity consumption and economic growth） of the three locales （Beijing, Tianjin, and Hebei） are non-stationary. But first differences of the two series are stationary. The results of the Johansen co-integration test indicate that electricity consumption and economic growth are co-integrated in Hebei and Tianjin while this is not the case in Beijing. The Granger causality test implies that there is causality running from electricity consumption to economic growth in all of the three locales. Causality running from economic growth to electricity consumption is found in Hebei and Beijing while this is not the case in Tianjin. This means that an increase in electricity consumption directly affects economic growth and that economic growth also stimulates further electricity consumption in Hebei and Beijing. But in Tianjin, an increase in electricity consumption directly affects economic growth while economic growth cannot affect electricity consumption. These findings can provide useful information for local governments of the three locales to formulate sustainable energy and economic policies. The study is of great significance for circular economy and building a resource-conserving society.

一种基于电量聚类分析的居民阶梯电价制定方法

我国居民用电执行阶梯电价政策。针对现有阶梯电价制定方法存在的不足,采用基于电力大数据的分析思想,形成一种新的阶梯电价制定方法。首先介绍用电量数据的结构特点和k-means++算法的基本原理,将聚类结果作为测算,验证了该方法的优越性。

考虑氢能储运特性的配电网集群划分与氢能系统选址定容策略

电-氢能源系统(IEHS)的合理规划对能源结构转型具有重要意义,充分利用氢储能的可移动特性可降低IEHS综合成本,提出一种考虑氢能储运特性的配电网集群划分与氢能系统规划策略。首先,将氢能系统拆分为多个氢能子系统(HES),建立多个HES之间的气氢拖车交通运输及储运成本模型;其次,基于电力-交通网架结构与新能源分布情况提出配电网集群划分方法;最后,根据集群划分结果,建立HES双层选址定容模型,该模型以IEHS年综合成本最低为目标,分层解决单个集群内HES的容量配置问题、各集群内部HES选址定容及气氢拖车配置问题。结果表明:提出的策略可以减小氢能储运压力、降低IEHS综合成本,提升风、光消纳水平,加快系统潮流计算迭代收敛速度。

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。

基于大语言模型绿电预测和绿电交易的园区综合能源系统集群多目标协同运行方法

为实现传统工业园区数字化和智能化升级,助力区域高质量发展,亟需园区智能化调度模型。为此,该文结合智慧园区管理系统和园区综合能源系统物理模型建立园区综合能源系统集群架构,提出了园区综合能源系统集群绿电交易三阶段协同运行方法,以解决多园区综合能源系统绿电交易的问题,实现分布式绿电的精准预测以及就地消纳。首先,基于大语言模型LLAMA-7B实现绿电预测,进一步以绿电功率划分购售电园区。其次,基于绿电价格配额曲线预测模型和动态绿电定价策略,制定园区间绿电交易差异价格。在此基础上,建立了多目标低碳经济优化运行模型,从而解决绿电交易所带来的经济因素和环境因素的矛盾问题。算例分析表明:所提出的模型可以统筹规划园区综合能源系统集群的经济成本、实际碳排放量和新能源利用率,对多园区综合能源系统的智能调度具有积极的推动作用。

基于SHAP-LightGBM的电动集装箱正面吊运起重机能耗分析和异常识别

集装箱正面吊运起重机(以下简称正面吊)在港口的实际作业中发挥着重要作用。随着社会对能源和环境问题的日益关注,正面吊的电动化趋势愈加显著,市场上电动正面吊的数量逐年增加。电耗性能直接影响电动正面吊的续航能力、作业效率和作业成本,是电动正面吊的重要性能之一。驾驶行为、作业工况、设备故障等因素均会对电动正面吊的能耗产生影响。为此,通过收集电动正面吊客户侧的实际运行数据,基于LightGBM(light gradient boosting machine,轻量级梯度提升机)模型,在微观和宏观两个层面分别对电动正面吊的行驶和作业过程进行能耗建模,并运用SHAP(Shapley additive explanations,沙普利加和解释)理论量化分析不同作业工况、作业行为对电动正面吊能耗的影响,同时识别设备故障所引起的能耗异常。结果表明,基于SHAP-LightGBM的能耗模型能够准确预测和分析电动正面吊的行驶和作业能耗,可为电动正面吊的设计、能耗策略优化提供有效的信息输入,同时可建立电动正面吊实际运行过程的理论能耗基准,有效指导驾驶行为和识别故障造成的能耗异常等。

原油管道节能降耗优化技术研究

基于降低原油管道水力消耗和热力消耗的目的,通过核算管输经济成本分析了不同输量对油单耗、电单耗及单位周转量运行能耗等参数的影响,研究了能耗最优和经济成本最优对应的最佳输量,分析了以气代油和用电方式改变对管输经济成本的影响。得到如下结论,单位周转量运行能耗随着输量的增大先增大后减小,在输量为1 050 m^(3)/h时的运行能耗最优;不同年份的燃料价格和电价对经济成本的影响较大,最低经济成本对应的输量也有所不同;将燃油加热炉改为燃气加热炉后,预计全年可节约热力成本1 840万元;将用电方式从一般工商业调整为大工业用电,且计价遵循最大容量时,预计全年可节约水力成本1 610万元。研究结果可为同类原油管道的运行优化提供实际参考。

Design and optimization of equivalent consumption minimization strategy for 4WD hybrid electric vehicles incorporating vehicle connectivity

This paper presents an optimized equivalent consumption minimization strategy(ECMS) for four-wheel-drive(4 WD) hybrid electric vehicles(HEVs) incorporating vehicle connectivity. In order to be applicable to the 4 WD architecture, the ECMS is designed based on a rule-based strategy and used under the condition that a certain propulsion mode is activated. Assuming that a group of 4 WD HEVs are connected and position information can be shared with each other, we formulate a decentralized model predictive control(MPC) framework that compromises fuel efficiency, mobility, and inter-vehicle distance to optimize the velocity profile of each individual vehicle. Based on the optimized velocity profile, an optimization problem considering both fuel economy and battery state of charge(SOC) sustainability is formulated to optimize the equivalent factors(EFs) of the ECMS for HEVs over an appropriate time window. MATLAB User Datagram Protocol(UDP) is used in the codes run on multiple computers to simulate the wireless communication among vehicles, which share position information via UDP-based communication, and dSPACE is used as a software-in-the-loop platform for the simulation of the optimized ECMS. Simulation results validate the control effectiveness of the proposed method.

A Chance Constrained Optimal Reserve Scheduling Approach for Economic Dispatch Considering Wind Penetration

The volatile wind power generation brings a full spectrum of problems to power system operation and management, ranging from transient system frequency fluctuation to steady state supply and demand balancing issue. In this paper, a novel wind integrated power system day-ahead economic dispatch model, with the consideration of generation and reserve cost is modelled and investigated. The proposed problem is first formulated as a chance constrained stochastic nonlinear programming U+0028 CCSNLP U+0029, and then transformed into a deterministic nonlinear programming U+0028 NLP U+0029. To tackle this NLP problem, a three-stage framework consists of particle swarm optimization U+0028 PSO U+0029, sequential quadratic programming U+0028 SQP U+0029 and Monte Carlo simulation U+0028 MCS U+0029 is proposed. The PSO is employed to heuristically search the line power flow limits, which are used by the SQP as constraints to solve the NLP problem. Then the solution from SQP is verified on benchmark system by using MCS. Finally, the verified results are feedback to the PSO as fitness value to update the particles. Simulation study on IEEE 30-bus system with wind power penetration is carried out, and the results demonstrate that the proposed dispatch model could be effectively solved by the proposed three-stage approach. © 2017 Chinese Association of Automation.

A Study of Discrete-Time Optimum Current Controller for the Virtual Synchronous Generator under Constraints

In recent years, power generation using renewable energy sources has been increasing as a solution to the global warning problem. Wind power generation can generate electricity day and night, and it is relatively more efficient among the renewable energy sources. The penetration level of variable-speed wind turbines continues to increase. The interconnected wind turbines, however, have no inertia and no synchronous power. Such devices can have a serious impact on the transient stability of the power grid system. One solution to stabilize such grid with renewable energy sources is to provide emulated inertia and synchronizing power. We have proposed an optimal design method of current control for virtual synchronous generators. This paper proposes an optimal control method that can follow the virtual generator model under constrains. As a result, it is shown that the proposed system can suppress the peak of the output of semiconductor device under instantaneous output voltage drop.

节能减排约束下的行业经济增长路径研究

为了减少全球气候变暖给世界生态环境带来的负面影响,我国政府制定实施了“力争2030年前实现碳达峰,2060年前实现碳中和”的“双碳”战略。在此时代背景之下,探究通过何种路径即能够满足节能减排的要求,又能够满足经济增长的需要,就成为了我国学术界亟待解决的研究课题之一。本文以节能减排与经济增长的协调发展为目标,围绕着经济增长、能源消耗、二氧化碳排放3个关键点,通过构建行业经济增长多目标优化模型,以及设计的3种不同能源消耗强度下的发展情景,运用非支配排序遗传算法来研究降低行业能源消耗强度对我国行业经济增长及其减少全国二氧化碳排放所产生的影响作用。研究结果表明:1)2021—2030年在基准情景下,其他行业的GDP年均增长率最高,交通运输及仓储和邮政业次之。由此可见,其他行业、交通运输及仓储和邮政业在未来的经济增长潜力会相对更大。2021—2030年在3种情景下我国GDP累计总量分别为1263.99万亿元、1264.18万亿元、1264.28万亿元,模拟结果表明通过降低能耗强度不但可以减少了全国的二氧化碳排放,而且还可以促进我国GDP的增长。2)2021—2030年在低碳情景下的我国能源消耗总量比在基准情景下的降低了20%左右,在强化低碳情景下的我国能源消耗总量比在基准情景下的降低了40%左右,2种低碳情景下的全国能源消耗总量下降幅度与行业能耗强度下降幅度基本一致。3)2021—2030年在3种情景下的我国碳强度变化一直呈下降趋势,2030年在3种情景下的我国碳强度值分别为0.834t/万元、0.680t/万元、0.530t/万元,相较于2005年的我国碳强度值,下降幅度均超过了74%,远超我国政府制定的2030年的碳强度要比2005年的碳强度下降65%的减碳目标。

中国电力消费与经济增长及结构调整相关性分析

随着经济发展和电气化程度加深,中国电力消费与经济增长相关关系的量化测度日益重要。基于面板向量自回归模型,构建了经济增长、电力消费和产业结构等方面的变量,检验了全国和江苏省电力消费和经济特征之间的长期均衡关系,并通过脉冲响应函数揭示电力消费和经济增长在受到不同类别的冲击时的长短期变化趋势。全国和江苏的电力消费、经济增长和产业结构升级趋势之间均呈现了跨期均衡关系,全国经济增长对电力消费的脉冲效应短期大,长期则弱化,江苏经济增长对电力消费冲击则更具持续性,反映出江苏经济发展、产业结构调整和电力生产消费之间的协调性。全国各区域的电力消费和生产应根据区域经济发展基础和程度,科学合理制定电力投资规划。

基于NPP-VIIRS数据的我国2012—2020年电力消费量时空动态模拟

夜间灯光数据能够有效探测城市夜间灯光,可用于估算电力消耗(EPC)的空间分布。各地区自然环境及社会发展差异大,夜间灯光与EPC的关系也存在地区差异。以我国为例,构建不同区域EPC长期时空动态最优模型,使用基于NPP-VIIRS数据构建的夜间灯光总量(TNL),采用线性模型、二次多项式模型及幂函数模型对2012—2020年EPC的时空动态进行模拟。结果表明,在国家层面,二次多项式模型为最优,平均绝对相对误差(MARE)最小,为1.94%;在省级层面,最优拟合模型一般为二次多项式模型,平均MARE值为2.78%。31个省份中,二次多项式模型最优的有24个,线性模型最优的有4个,幂函数模型仅有3个。本研究使用精度更高的NPP-VIIRS夜间灯光数据,为准确模拟EPC数据的长期时空动态提供了一种思路,对反映社会经济活动中电力利用效益的提高所取得的成效分析具有重要意义。

Optimal Portfolio and Consumption Rule with a CIR Model Under HARA Utility

In the real-world environments,different individuals have different risk preferences.This paper investigates the optimal portfolio and consumption rule with a Cox–Ingersoll–Ross(CIR)model in a more general utility framework.After consumption,an individual invests his wealth into the financial market with one risk-free asset and multiple risky assets,where the short-term rate is driven by the CIR model and stock price dynamics are simultaneously influenced by random sources from both stochastic interest rate and stock market itself.The individual hopes to optimize their portfolios and consumption rules to maximize expected utility of terminal wealth and intermediate consumption.Risk preference of individual is assumed to satisfy hyperbolic absolute risk aversion(HARA)utility,which contains power utility,logarithm utility,and exponential utility as special cases.By using the principle of stochastic optimality and Legendre transform-dual theory,the explicit expressions of the optimal portfolio and consumption rule are obtained.The sensitivity of the optimal strategies to main parameters is analysed by a numerical example.In addition,economic implications are also presented.Our research results show that Legendre transform-dual theory is an effective methodology in dealing with the portfolio selection problems with HARA utility and interest rate risk can be completely hedged by constructing specific portfolios.

Optimal allocation of solar photovoltaic distributed generation in electrical distribution networks using Archimedes optimization algorithm

This paper proposes to resolve optimal solar photovoltaic(SPV)system locations and sizes in electrical distribution networks using a novel Archimedes optimization algorithm(AOA)inspired by physical principles in order to minimize network dependence and greenhouse gas(GHG)emissions to the greatest extent possible.Loss sensitivity factors are used to predefine the search space for sites,and AOA is used to identify the optimal locations and sizes of SPV systems for reducing grid dependence and GHG emissions from conventional power plants.Experiments with composite agriculture loads on a practical Indian 22-bus agricultural feeder,a 28-bus rural feeder and an IEEE 85-bus feeder demonstrated the critical nature of optimally distributed SPV systems for minimizing grid reliance and reducing GHG emissions from conventional energy sources.Additionally,the voltage profile of the network has been enhanced,resulting in significant reductions in distribution losses.The results of AOA were compared to those of several other nature-inspired heuristic algorithms previously published in the literature,and it was observed that AOA outperformed them in terms of convergence and redundancy when solving complex,non-linear and multivariable optimization problems.

基于CVaR风险计量指标的发电商投标组合策略及模型

电力市场中各类市场具有不同的价格波动特性和收益率随机变化特性。为了保证年度收益最大且风险最低,发电商需在各个市场上合理分配参与竞价的电量。借鉴金融领域风险管理的理论,以条件风险价值(CVaR)为风险计量指标,综合考虑风险和期望收益率,建立了新的发电商均值-CVaR投标组合优化模型。应用该模型,对发电商在年度合约市场、月度合约市场、日前市场和实时市场4个市场总电量的分配比例和有效前沿进行了计算。计算结果表明,所提出的模型能较真实地反映发电商所面临的市场风险的本质特征,可使发电商在保证一定期望收益率的前提下承担最小的CVaR风险,从而为发电商的投标决策与风险评估提供了新的思路。

纯电动汽车经济性换挡规律仿真研究

为提高纯电动汽车的续驶里程,降低能量消耗率,本文中针对其燃油经济性进行了换挡规律的仿真。首先制定出两参数静态经济性换挡规律;然后利用动态规划算法找出在ECE循环工况下的最优挡位,并据此对所制定的静态经济性换挡规律进行修正,得到最终经济性换挡规律曲线;最后,在UDDS行驶工况下,建立了纯电动汽车耗电量模型,对修正前后的换挡规律进行仿真。结果表明,修正后的换挡规律能有效地降低纯电动汽车的能量消耗率。

采用两阶段优化模型的电动汽车充电站内有序充电策略

在满足电动汽车用户充电需求及配电变压器容量限制的前提下,建立了以充电站充电收益最大化为目标的第一阶段优化模型。考虑最大化电网公司对缩小峰谷差所给予的激励,以不低于第一阶段优化所求得的最大充电收益为约束,建立了第二阶段优化模型。根据用户的驾驶习惯,采用蒙特卡洛方法模拟用户的充电需求,对电动汽车在无序充电、第一阶段模型和两阶段模型优化控制充电3种情形下充电站的经济效益及配电变压器下的负载情况进行了仿真和分析。研究结果表明,采用第一阶段模型和两阶段模型均可显著提升充电站的经济效益。但是在现行的分时电价机制下,仅采用第一阶段优化模型进行大量电动汽车的充电控制往往会带来新的负荷尖峰,而两阶段优化模型在进一步增大充电站经济效益、减小峰谷差等方面均有显著作用,并且具有很高的计算效率,适于实际应用。

考虑与电动汽车换电站互动的微电网经济调度

为实现电动汽车换电站(BSS)与微电网所有权不同时微电网运行优化,建立了微电网经济调度双层优化模型。在上层模型中,微电网调度中心是决策机构,其目标函数是微电网供电成本最小;在下层模型中,BSS运营商是决策机构,在考虑换电需求量不确定性的基础上,建立以BSS利润最大为目标函数的盒式集合鲁棒优化模型。上、下层优化模型通过微电网向BSS提供的个性化电价实现互动。采用入侵杂草算法和CPLEX软件分别对上、下层优化问题进行求解,得到微电网内部可控微电源的出力和个性化电价,实现微电网和BSS的共同利益。对某中压微电网进行算例分析,结果验证了所提模型及算法的合理性和有效性。