Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Reliability Assessment of Integrated Electricity and Natural Gas Transmission Systems in Presence of Power-to-gas and Combined Heat and Power Technologies

Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.

Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded

As power to gas(P2 G) technology gradually matures, the coupling between electricity networks and natural gas networks should ideally evolve synergistically.With the intent of characterizing market behaviors of integrated electric power and natural gas networks(IPGNs)with P2 G facilities, this paper establishes a steady-state model of P2 G and constructs optimal dispatch models of an electricity network and a natural gas network separately. In addition, a concept of slack energy flow(SEF) is proposed as a tool for coordinated optimal dispatch between the two networks. To study how the market pricing mechanism affects coordinated optimal dispatch in an IPGN, a market equilibrium-solving model for an IPGN is constructed according to game theory, with a solution based on the Nikaido-Isoda function. Case studies are conducted on a joint model that combines the modified IEEE 118-node electricity network and the Belgian 20-node gas network.The results show that if the game between an electric power company and a natural gas company reaches market equilibrium, not only can both companies maximize their profits, but also the coordinated operation of the coupling units, i.e., gas turbines and P2 G facilities, will contribute more to renewable energy utilization and carbon emission reduction.

Reliability evaluation of integrated electricity–gas system utilizing network equivalent and integrated optimal power flow techniques

The wide utilization of gas-fired generation and the rapid development of power-to-gas technologies have led to the intensified integration of electricity and gas systems.The random failures of components in either electricity or gas system may have a considerable impact on the reliabilities of both systems.Therefore,it is necessary to evaluate the reliabilities of electricity and gas systems considering their integration.In this paper,a novel reliability evaluation method for integrated electricity-gas systems(IEGSs)is proposed.First,reliability network equivalents are utilized to represent reliability models of gas-fired generating units,gas sources(GSs),power-to-gas facilities,and other conventional generating units in IEGS.A contingency management schema is then developed considering the coupling between electricity and gas systems based on an optimal power flow technique.Finally,the time-sequential Monte Carlo simulation approach is used to model the chronological characteristics of the corresponding reliability network equivalents.The proposed method is capable to evaluate customers’reliabilities in IEGS,which is illustrated on an integrated IEEE Reliability Test System and Belgium gas transmission system.

考虑电力-交通耦合网动态协调的EV集群灵活性挖掘与优化调度

电动汽车(EV)作为兼具交通与能量双重属性的跨域主体,发挥其时空灵活性将助力电力-交通耦合网的协调运行。为此,文中考虑电力-交通耦合网综合效益,提出了EV集群调控策略。首先,基于弧阻抗函数构建了动态交通网络加载模型。其次,考虑EV用户的各特征参数存在的差异性与耦合性,构建了单体EV灵活运行域模型,并采用基于zonotope线性近似的闵可夫斯基和算法对其聚合,得到EV集群的时变灵活运行域。在此基础上,提出了动态交通流最优分配下EV集群灵活性调控的双层模型,迭代求解得到上下两层耦合变量构成的瞬时单位流量出行成本,从而引导EV的出行与充放电行为。最后,通过与最短路径引导策略进行比较,验证了所提EV集群调控策略的有效性。

交通网络和电力网络融合承载力的研究综述

电动汽车作为交通电气化的核心,对减少温室气体排放和提高能源效率起到了积极的作用。显著增长的电动汽车保有量和市场占比对充电基础设施产生了一定的影响,如充电设施不足和电网负荷波动等问题凸显。本文深入梳理了交通网络承载力和电力网络承载力的基本概念、计算方法和评估指标,分析了交通与能源网络两网评估方法与两网融合韧性,并探讨了交通-电力融合系统潜在的挑战与策略;揭示出目前亟待开展的研究领域并指出了未来的研究方向,以期提高充电设施效率,缓解交通拥堵,保障电网稳定运行。

电力北斗应用体系设计与应用研究

随着北斗卫星导航系统(BeiDou Satellite Navigation System, BDS)的成熟,电力北斗应用不断拓展和深入,并构建起较为完整的应用体系.本文对电力BDS应用体系架构进行了研究设计,重点介绍了电力北斗在规划建设、设施设备管理、营销、调度控制及物资后勤管理等五方面的应用,并对电力北斗应用未来发展趋势进行了分析,提出了相应的发展建议.

浅谈电力系统中10kV智能配网的设计与应用

电力需求激增的过程中,为提高电力系统的供配电能力,必须转变原有的系统架构。10kV配网作为电力系统中的关键构成,为适应智能电网建设需求,设计人员需采用人工智能等新型技术,建成10kV智能配网,增强配网的运行可靠性,以高效、安全、稳定供电、配电。10kV智能配网建设取得了一定成效,未来需继续加大在这一方面的技术创新,以提高建设水平。基于此,本文重点分析了10kV智能配网的设计要点及应用策略,以期为实际工作提供参考与借鉴。

Electric Vehicle Charging Simulation Framework Considering Traffic,User,and Power Grid

The traffic and user have significant impacts on the electric vehicle(EV)charging load but are not considered in the existing research.We propose a novel integrated simulation framework considering the traffic,the user,and power grid as well as the EV traveling,parking and charging based on cellular automaton(CA).The traffic is modeled by the traffic module of the proposed framework based on CA,while the power grid and user are modeled in the EV charging module.The traffic flow,user’s charging preference,user’s charging satisfaction,and the total supply capability(TSC)in the surveyed region are considered in the proposed framework.Two cases are carried out to show the interactions between the user and power grid.It is shown that the proposed framework can accurately simulate the interactions among traffic situation,user's behavior and TSC,which are significantly lacking in the existing research.The proposed framework is scalable in considering additional interrelated elements.

基于图神经网络多智能体强化学习的电力-交通融合网协同优化运行

针对多重不确定性因素下配电系统、交通系统和电动汽车动态交互的电力−交通融合网序贯协同优化问题,提出一种基于图神经网络多智能体强化学习的电力−交通融合网协同优化方法。首先,基于图理论方法将电动汽车间的相互影响关系转换为一种动态网络图模型,采用一种基于注意力机制的图神经网络多智能体强化学习算法求解电动汽车充电引导策略,探讨电动汽车多智能体间的相互影响作用。然后,在含可再生能源出力的主动配电网中采用二阶锥优化及对偶优化理论对配电网最优潮流进行求解,得到配电网节点边际电价,研究电力和交通系统的动态交互特性。最后,在某区域108节点交通网络和IEEE 33节点电力系统上验证所提方法有效性。

基于气网动态精细化建模的区域电-气综合能源系统机会约束最优能流计算

随着国家能源转型和“双碳”目标的逐步实施,燃气发电在我国电力系统装机中占比不断提高,日益密切的电、气耦合关系使电-气综合能源系统受到更多关注。为此,研究了考虑气网动态精细化建模对含出力不确定的分布式新能源发电的区域电-气综合能源系统运行策略的影响。提出考虑管道气流方向灵活可变的气网动态复频域建模方法,提升了电-气最优能流的计算精度;采用机会约束建立分布式新能源发电不确定性对电网和气网运行影响的模型;算例测试结果表明气网动态精细化模型可有效提升区域电-气综合能源系统对运行不确定性的应对能力。

高速公路与电网耦合背景下的充电站布局规划

为适应大量电动汽车接入而增加的充电需求,需同时考虑高速公路和电网相关约束进行合理的充电站布局规划。首先,基于路段传输模型和排队论动态地计算交通流量信息和充电排队等待时间;其次,构建考虑充电设施和电力设备扩容投资与运维成本之和、用户排队等待时间的多目标规划数学模型;然后,采用快速非支配排序遗传算法和证据推理方法得到最优充电站布局规划方案;最后,以G15沈海高速的实际车流量数据和电力系统数据为例进行仿真分析。仿真结果表明,所提模型和方法能够有效地兼顾投资经济性和用户满意度获得最优的充电站布局规划方案。

计及热网灵活性恢复过程的电热综合能源系统鲁棒超前调度

热网的动态特性使其能够为电力系统提供可观的灵活调节能力,促进新能源并网消纳。然而,如何充分挖掘、准确评估热网的灵活性潜力而尽可能维持热能供需的长期平衡,减少灵活性潜力挖掘对热网运行的影响是当前亟待解决的问题。为此,提出了计及热网灵活性恢复过程的电热综合能源鲁棒超前调度方法。首先,设计了热网灵活性恢复策略,进而构建了兼顾灵活性供给与恢复过程的热网灵活性量化模型。其次,引入风电接纳风险指标,兼顾系统运行成本与风险,构建电热综合能源系统鲁棒超前调度模型。而后,融合分段线性近似、大M法等,设计了兼顾计算精度与效率的求解方法。最后,基于小型规模测试系统,验证了所提方法的有效性。算例分析结果表明:相较于传统的电-热系统协同调度策略,采用所提方法,风电可接纳范围提升10.72%,综合成本降低0.87%,有效提升了系统的安全性及经济性。同时,基于大型规模测试系统,验证了所提模型求解方法具有良好的计算效率。

考虑多评估指标的电-气综合能源系统可靠性评估

燃气轮机的广泛应用使得电力网与天然气网愈加耦合,同时对电-气综合能源系统的可靠性提出了较高的要求,建立全面、合理的可靠性评估指标对于系统可靠性评估具有重要意义。建立电-气综合能源系统的最优负荷削减模型,在传统可靠性评估指标的基础上进一步根据电-气耦合程度、供气系统延时特性建立电-气综合能源系统可靠性评估指标体系;基于蒙特卡洛法从多角度全面分析联合系统的可靠性;以14节点电力系统和10节点天然气系统组成的电-气综合能源系统为例进行可靠性评估。算例结果表明:考虑天然气延时后,联合系统整体可靠性有所提升;燃气轮机容量的提升使得电力系统可靠性有所提升,但提升作用有限。

电力物联网立体异构通信网络协同编排技术研究

采用空-天-地协同的立体通信架构可满足电力物联网广覆盖、大连接的通信需求,但多层异构的通信网络存在结构复杂、节点分散、运维困难等问题。基于SDN(软件定义网络)控制逻辑集中的理念,提出了基于协同编排系统的电力物联网立体异构通信网络协同控制方案。开展了协同编排系统的设计需求分析并完成其功能设计。针对协同编排系统的核心功能需求,提出了改进的基于Q学习的流量调度方法。仿真结果表明,所提方法可提升异构通信网络的流量吞吐能力和负载均衡能力。

海底光缆传输网及其关键技术研究

论文介绍了国内外海底光缆传输网络的发展现状,提出了具有网格拓扑结构的海底光缆传输网的总体架构,研究信息接入与传输、远程供电、海底节点、光电综合网络监测等关键技术,实现各类海洋信息大容量、高速、可靠接入和传输至岸基中心,提高海底区域的抗毁生存、信息综合传输和远程供电等能力,为我国海底光缆传输网络的设计和建设提供参考。

电力企业信息通信网络一体化思考研究

随着电网规模的逐渐扩大和变电站数量的增加,传统人工巡检的方式已经无法满足电网稳定运行的需求。电力企业的信息通信网络一体化在电力企业的策略与发展规划中具有非常重要的意义和作用。基于此背景,开展电力企业的信息通信网络一体化研究,可以为电力企业信息化和数字化转型提供有力的支撑与指导,促进电力企业的可持续发展。

基于数字化变电站的集中式保护

新型的PCS集中式保护采用嵌入式的硬件设计和分布式的软件设计。每个间隔的保护测控集成到一个DSP板卡中,并可灵活扩展,已经成功应用于220 kV变电站。变电站220 kV配置2台集中式线路保护装置完成所有线路和母联的保护测控功能,配置1台集中式元件保护装置完成母线、主变保护测控功能。66 kV配置4台集中式低压保护完成所有66 kV出线、电抗器、电容器保护。变电站在过程层采用IEC61850-9-2/GOOSE的冗余双网方案,间隔层采用点对点同步技术。

一种基于熵的电力通信网络业务资源均匀分配算法

为了均匀电力通信网络业务流量的分布并提高网络吞吐量和传输可靠性,提出了一种基于熵的业务均匀分配算法。根据电力通信网具有的业务特点进行业务流量分析,业务流量的分布情况体现了网络业务运行状态,将业务信息熵作为衡量网络业务分布均匀化的指标,进而引用信息熵作为目标函数得出优化全局业务路由的算法。首先将业务的时延作为约束条件,求得满足业务需求的可用路径集,再将业务信息熵作为优化函数,最后利用量子遗传算法解决多约束路由问题,在适应度评价的过程中添加带宽约束,控制每条业务流量路径走向,求取使得当前网络业务信息熵值最大的业务路径集。仿真结果显示,在基于熵的业务均匀算法下的网络业务分布相对均匀,并有效地控制了流量,实现了优化网络资源和均衡网络负载的目的。

考虑配电网重构的区域综合能源系统最优混合潮流计算

随着热电联产系统、中央空调及燃气锅炉等单元的广泛使用,区域综合能源系统(ICES)中电力、天然气和热力系统的耦合和联系日益紧密。从"源—网—荷"全环节出发,提出了融合配电网重构的ICES最优混合潮流算法来对ICES进行优化调度。首先,基于能源集线器理论,构建了ICES中能量中心(EC)的数学模型。然后,考虑ICES中三相不平衡配电系统、燃气管网及EC的相关约束,以运行成本最小为目标,提出了融合配电网重构能力的ICES最优混合潮流模型及求解方法。最后,利用典型ICES算例系统测试结果表明,所述方法通过将配电网可重构网络拓扑这一灵活可控元素作为控制变量有效集成到ICES"源—网—荷"最优混合潮流算法中,进一步降低了ICES的运行成本。