Nonparametric statistical analysis of system resilience migration and application for electric distribution structures

This paper proposes a set of nonparametric statistical tools for analyzing the system resilience of civil structures and infrastructure and its migration upon changes in critical system parameters.The work is founded on the classic theoretic framework that system resilience is defined in multiple dimensions for a constructed system.Consequentially,system resilience can lose its parametric form as a random variable,falling into the realm of nonparametric statistics.With this nonparametric shift,traditional distribution-based statistics are ineffective in characterizing the migration of system resilience due to the variation of system parameters.Three statistical tools are proposed under the nonparametric statistical resilience analysis(npSRA)framework,including nonparametric copula-based sensitivity analysis,two-sample resilience test analysis,and a novel tool for resilience attenuation analysis.To demonstrate the use of this framework,we focus on electric distribution systems,commonly found in many urban,suburban,and rural areas and vulnerable to tropical storms.A novel procedure for considering resourcefulness parameters in the socioeconomic space is proposed.Numerical results reveal the complex sta-tistical relations between the distributions of system resilience,physical aging,and socioeconomic parameters for the power distribution system.The proposed resilience distance computing and resilience attenuation anal-ysis further suggests two proper nonparametric distance metrics,the Earth Moving Distance(EMD)metric and the Cramévon Mises(CVM)metric,for characterizing the migration of system resilience for electric distribution systems.

Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties

This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.

Design and Analysis of a 24 Vdc to 48 Vdc Bidirectional DC-DC Converter Specifically for a Distributed Energy Application

The design of a bidirectional dc-dc power converter specifically for a distributed energy application is presented. The existing two different DC voltage battery bank of the distributed generation needs to interlink each other using a bi-directional dc-dc converter in order to minimize the unbalance of the output load currents of the three inverters connected to electric grid system. Through this connection, a current can flow from one system to another or vice versa depending on which systems need the current most. Thus, unbalanced currents of the grid line have been minimized and the reliability and performance of the DER grid connected system has been increased. A detailed mathematical analysis of the converter under steady state and transient condition are presented. Mathematical models for boost and buck modes are being derived and the simulink model is constructed in order to simulate the system. Moreover, the model has been validated on the actual operation of the converter, showing that the simulated results in Matlab Simulink are consistent with the experimental ones.

Quantifying Contribution of DER-Integrated EV Parking Lots to Reliability of Power Distribution Systems

In the future smart cities,parking lots(PLs)can accommodate hundreds of electric vehicles(EVs)at the same time.This trend creates an opportunity for PLs to serve as a potential flexibility resource,considering growing penetration of EVs and integration of distributed energy resources DER(such as photovoltaic and energy storages).Given this background,this paper proposes a comprehensive evaluation framework to investigate the potential role of DER-integrated PLs(DPL)with the capability of vehicle-to-grid(V2G)in improving the reliability of the distribution network.For this aim,first,an overview for the distribution system with DPLs is provided.Then,a generic model for the available generation capacity(AGC)of DPLs with consideration of EV scheduling strategy is developed.On the above basis,an iterative-based algorithm leveraging sequential Monte Carlo simulation is presented to quantify the contribution of DPLs to the reliability of the system.In order to verify the effectiveness of the proposed method,a series of numerical studies are carried out.The simulation results show that the integration of DPLs with the V2G capability could help to improve the reliability performance of distribution grid to a great extent and reduce the adverse impact incurred by EV accommodation,if utilized properly.

Reinforcement Learning with Enhanced Safety for Optimal Dispatch of Distributed Energy Resources in Active Distribution Networks

As numerous distributed energy resources(DERs)are integrated into the distribution networks,the optimal dispatch of DERs is more and more imperative to achieve transition to active distribution networks(ADNs).Since accurate models are usually unavailable in ADNs,an increasing number of reinforcement learning(RL)based methods have been proposed for the optimal dispatch problem.However,these RL based methods are typically formulated without safety guarantees,which hinders their application in real world.In this paper,we propose an RL based method called supervisor-projector-enhanced safe soft actor-critic(S3AC)for the optimal dispatch of DERs in ADNs,which not only minimizes the operational cost but also satisfies safety constraints during online execution.In the proposed S3AC,the data-driven supervisor and projector are pre-trained based on the historical data from supervisory control and data acquisition(SCADA)system,effectively providing enhanced safety for executed actions.Numerical studies on several IEEE test systems demonstrate the effectiveness and safety of the proposed S3AC.

分布式能源资源整合与新能源电力市场化营销研究

综合分析了分布式能源资源的特性及挑战,并介绍了微网、虚拟电厂和智能电网等关键技术,探讨了它们在能源领域中的作用与意义;同时,提出了新能源电力市场化运作的核心机制,包括市场化机制与平台的设计、市场化技术工具的应用以及电力交易与结算的运作。通过企业实证案例的分析,验证了分布式能源资源与新能源电力市场化整合在企业电力销售方面的实际意义与效果,对于推动能源领域的可持续发展具有重要的理论与实践价值。

Incentive mechanism for sharing distributed energy resources

To improve the controllability and utilization of distributed energy resources(DERs),distribution-level electricity markets based on consumers’bidding and offers have been proposed.However,the transaction costs will dramatically increase with the rapid development of DERs.Therefore,in this paper,we develop an energy sharing scheme that allows users to share DERs with neighbors,and design a novel incentive mechanism for benefit allocation without users’bidding on electricity prices.In the energy sharing scheme,an aggregator organizes a number of electricity users,and trades with the connected power grid.The aggregator is aimed at minimizing the total costs by matching the surplus energy from DERs and electrical loads.A novel index,termed as sharing contribution rate(SCR),is presented to evaluate different users’contributions to the energy sharing.Then,based on users’SCRs,an efficient benefit allocation mechanism is implemented to determine the aggregator’s payment to users that incentivize their participation in energy sharing.To avoid users’bidding,we propose a decentralized framework for the energy sharing and incentive mechanism.Case studies based on real-world datasets demonstrate that the aggregator and users can benefit from the energy sharing scheme,and the incentive mechanism allocates the benefits according to users’contributions.

Coalition Formation of Microgrids with Distributed Energy Resources and Energy Storage in Energy Market

Power grids include entities such as home-microgrids(H-MGs),consumers,and retailers,each of which has a unique and sometimes contradictory objective compared with others while exchanging electricity and heat with other H-MGs.Therefore,there is the need for a smart structure to handle the new situation.This paper proposes a bilevel hierarchical structure for designing and planning distributed energy resources(DERs)and energy storage in H-MGs by considering the demand response(DR).In general,the upper-level structure is based on H-MG generation competition to maximize their individual and/or group income in the process of forming a coalition with other H-MGs.The upper-level problem is decomposed into a set of low-level market clearing problems.Both electricity and heat markets are simultaneously modeled in this paper.DERs,including wind turbines(WTs),combined heat and power(CHP)systems,electric boilers(EBs),electric heat pumps(EHPs),and electric energy storage systems,participate in the electricity markets.In addition,CHP systems,gas boilers(GBs),EBs,EHPs,solar thermal panels,and thermal energy storage systems participate in the heat market.Results show that the formation of a coalition among H-MGs present in one grid will not only have a significant effect on programming and regulating the value of the power generated by the generation resources,but also impact the demand consumption and behavior of consumers participating in the DR program with a cheaper market clearing price.

Reactive power operability of distributed energy resources for voltage stability of distribution networks

The penetration level of distributed energy resources(DERs)is increasing and has significant impact on the voltage stability of distribution networks.Based on the various types of DERs with distinct reactive power characteristics(RPC),their different contributions to the system voltage stability require classification.Firstly,the features of DERs are reviewed and classified based on their RPC,to investigate different distributed generation technologies for reactive power support in distribution networks.Then,the concept of a relative available transmission capacity index(RATCI),which is based on power transfer margin of the power-voltage curve considering the non-negligible distribution network resistance,is proposed to quantify and evaluate the voltage stability by integrating DERs with the defined reactive power types.Case studies have been conducted for an IEEE 33-bus distribution network to calculate the system RATCI for the mixed integration of DERs.Results show that the multitype and multi-locational integration of DERs can improve the voltage stability of a distribution network.

Impact of Cascade Disconnection of Distributed Energy Resources on Bulk Power System Stability:Modeling and Mitigation Requirements

This work presents a new approach to establishing the minimum requirements for anti-islanding protection of distributed energy resources(DERs)with focus on bulk power system stability.The proposed approach aims to avoid cascade disconnection of DERs during major disturbances in the transmission network and to compromise as little as possible the detection of real islanding situations.The proposed approach concentrates on the rate-of-change of frequency(RoCoF)protection function and it is based on the assessment of dynamic security regions with the incorporation of a new and straightforward approach to represent the disconnection of DERs when analyzing the bulk power system stability.Initially,the impact of disconnection of DERs on the Brazilian Interconnected Power System(BIPS)stability is analyzed,highlighting the importance of modeling such disconnection in electromechanical stability studies,even considering low penetration levels of DERs.Then,the proposed approach is applied to the BIPS,evidencing its benefits when specifying the minimum requirements of anti-islanding protection,without overestimating them.

Reinforcement learning-driven local transactive energy market fordistributed energy resources

Local energy markets are emerging as a tool for coordinating generation, storage, and consumption of energyfrom distributed resources. In combination with automation, they promise to provide an effective energymanagement framework that is fair and brings system-level savings. The cooperative–competitive natureof energy markets calls for multi-agent based automation with learning energy trading agents. However,depending on the dynamics of the agent–environment interaction, this approach may yield unintended behaviorof market participants. Thus, the design of market mechanisms suitable for reinforcement learning agentsmust take into account this interplay. This article introduces autonomous local energy exchange (ALEX) asan experimental framework that combines multi-agent learning and double auction mechanism. Participantsdetermine their internal price signals and make energy management decisions through market interactions,rather than relying on predetermined external price signals. The main contribution of this article is examinationof compatibility between specific market elements and independent learning agents. Effects of different marketproperties are evaluated through simulation experiments, and the results are used for determine a suitablemarket design. The results show that market truthfulness maintains demand-response functionality, while weakbudget balancing provides a strong reinforcement signal for the learning agents. The resulting agent behavioris compared with two baselines: net billing and time-of-use rates. The ALEX-based pricing is more responsiveto fluctuations in the community net load compared to the time-of-use. The more accurate accounting ofrenewable energy usage reduced bills by a median 38.8% compared to net billing, confirming the ability tobetter facilitate demand response.

考虑电动汽车充放电的输配协同能量-灵活性市场出清机制

为应对输电网对灵活性资源的迫切需求,挖掘配电网分布式资源的灵活性支撑潜力,首先,构建市场环境下电动汽车的车-网互动响应模型,分析不同充放电方式下电动汽车的需求响应能力,为电动汽车参与市场环境下电网调度控制提供模型基础;然后,计及配电网运营商对需求侧灵活性资源的聚合作用,以购买电力和灵活性资源总成本最低为目标,构建考虑电动汽车充放电方式的输配协同能量-灵活性市场出清模型,通过协调控制输配电网中各类灵活性资源来满足输电网的灵活性需求;最后,通过修改的IEEE 33节点输电网与2个IEEE 33节点配电网耦合的测试系统对所提输配协同能量-灵活性市场出清方法的有效性进行分析与验证。结果表明,所提方法可提升电力系统的运行经济性和灵活性。

Application of Bifurcation Analysis on Active Distribution Systems

This paper presents the application of bifurcation method on the steady state three-phase load-flow Jacobian method to study the voltage stability of unbalanced distribution systems. The eigenvalue analysis is used to study distribution system behavior under different operating conditions. Two-bus connected by asymmetrical line is used as the study system. The effects of both unbalance and extreme loading conditions are investigated. Also, the impact of distributed energy resources is studied. Different case studies and loading scenarios are presented to trace the eigenvalues of the Jacobian matrix. The results exhibit the existence of a new bifurcation point which may not be related to the voltage stability.

配合防孤岛保护的配电网时限自适应重合闸方法

有源配电网重合闸之前分布式能源必须脱网,但实际中很多变电站内未安装线路侧电压互感器,导致检无压重合闸方案无法实施。文中提出一种与分布式电源防孤岛保护相配合的时限自适应重合闸方法,通过保护跳闸前的系统侧母线电压来推断线路接入的分布式电源防孤岛保护动作时间,自动调整配电线路重合闸的动作时间,实现重合闸与防孤岛保护的时序配合。所提方法不需要安装线路侧电压互感器,不依赖于通信网络,考虑分布式电源低电压穿越要求的同时实现配电线路的快速重合闸,为电力系统运行的稳定性与供电可靠性提供支撑。仿真及实验结果均验证了该方法的有效性。

基于V2G与应急通信的配电网信息物理协同快速恢复方法

随着新型配电系统的快速发展,配电网与通信网络的相互依赖程度逐渐加深。在极端灾害发生后,一方面,配电网失电后的恢复控制需要依靠通信网络的有效支撑,灾后使用电动汽车与电网互动(V2G)恢复负荷电力供应的过程,同样离不开通信网络的引导作用;另一方面,通信网络的正常运行依靠配电网的电力供应。因此,为解决配电网灾害后电力网络与通信网络交互影响下的负荷恢复问题,提出了一种基于V2G和应急通信的配电网信息物理协同快速恢复方法:在灾害发生后,通过调配搭载无线通信基站的无人机前往通信故障区域构建应急通信网络,从而迅速恢复对区域线路开关的控制能力与对电动汽车的引导能力,进而引导电动汽车前往车辆并网站形成分布式电源并控制配电网拓扑重构,以恢复负荷的电力供应。该方法基于灾后无人机与电动汽车的调度约束以及配电网的运行约束,建立了配电网信息物理协同恢复模型,并通过配电网和交通网耦合算例验证了所提方法的有效性。

考虑风险偏好的多主体虚拟电厂经济调度与收益分配策略

虚拟电厂(VPP)在新型电力系统中的地位日益凸显,而可聚合分布式能源(DER)的VPP内部风电机组、光伏发电机组的随机性和波动性负荷等不确定因素给VPP的运营决策和收益带来风险。如何建立公平、合理、透明的利益分配机制是成功维护VPP内DER合作关系的关键。为了激励VPP内部各主体参与市场的积极性,各主体可根据自身特点与贡献度协商分配收益,构建计及风险偏好的包含风电机组、光伏发电、可控分布式电源、储能及柔性负荷的多主体VPP内部优化调度决策模型,参与电力市场,并建立Nash-Harsanyi讨价还价解的VPP利益分配模型。算例分析以VPP最大化运行效益为目标,指导系统运营策略和降低VPP运行风险水平,验证了所提利益分配法能有效平衡各方利益,量化各DER对VPP利润的实际贡献度,提高各成员参与市场竞争的积极性。采用Nash-Harsanyi解的分配方案在VPP收益分配合理性和适用性方面优于Shapley值法方案。

基于模糊层次分析法–熵权法–逼近理想解排序法的虚拟电厂综合贡献度评估方法

为科学全面评估虚拟电厂内部资源的贡献度,深度挖掘虚拟电厂内部资源潜力,激发虚拟电厂内部聚合资源,积极提升安全、可靠和经济性,助力源、网、荷、储一体化的发展,首先,充分考虑虚拟电厂内部资源在电网安全运行、电力电量平衡以及新能源消纳等方面的贡献,建立虚拟电厂内部资源“安全-可靠-经济”的综合贡献度指标评估体系;其次,构建基于模糊层次分析法–熵权法–逼近理想解排序法的虚拟电厂综合贡献度评估方法,分析虚拟电厂内部分布式能源资源贡献度最优选择策略,并将该方案进行灵敏度检验;最后,通过算例分析不同类型的分布式能源资源对虚拟电厂的综合贡献度及其灵敏度,确定虚拟电厂内部资源最优选择策略,为虚拟电厂内部资源配置提出参考性建议。

市场环境下灵活性资源虚拟电厂聚合调控关键技术综述

灵活性资源技术快速发展、数量与日俱增,为提升电力系统灵活性和经济效益提供了巨大潜力。虚拟电厂通过对海量异构灵活性资源协调管理和聚合调控,为支撑海量异构分散式资源参与电力市场交易提供了有效手段。针对电力市场环境下虚拟电厂中多元海量异构灵活性资源的难以高效管控、不同运营主体之间存在效益冲突、能量和辅助服务之间具有耦合关系等问题,对电力市场环境下灵活性资源虚拟电厂全链路运营过程中面临的技术挑战、当前研究进展和未来攻关方向进行了分析和总结。从灵活性资源虚拟电厂的聚合建模、竞标报价、运行控制3方面展开分析,对相关主流技术方法的模型特征、关联关系和适用场景进行了系统性归纳,以此全面认识电力市场环境下灵活性资源虚拟电厂涉及的关键科学问题、核心理论方法和主流技术方案等,为灵活性资源虚拟电厂的未来研究方向和技术发展提供建议。

考虑分布式资源交易的气电综合能源配网系统出清模型

随着分布式能源设备大量接入配电网并逐步参与分布式交易,配电网运行向着分布式、互动化的方向发展而呈现出更灵活多变的趋势。近年来,综合能源系统快速发展,配网层面电力系统和天然气系统耦合程度日益加深,独立运行模式已无法满足边界匹配要求。文中设计了考虑分布式资源参与的配电网集中交易市场模式,对分布式光伏、分布式储能、电动汽车等建立了交易模型。进而,构建了考虑分布式资源交易的气电综合能源配网系统联合出清模型,采用二阶锥松弛法及泰勒级数展开对配电网潮流约束和配气网潮流约束进行线性化处理,通过配电网节点电价和配气网分时气价反映气电联合系统价格信号。最后,基于改进的气电联合系统对文中所提市场机制模型的有效性进行了验证。

大数据联盟下一种分布式光伏资源共享算法设计

为了提升分布式光伏资源利用率,提高时均用电效率,提出大数据联盟下分布式光伏资源共享算法。依据光伏发电储电用电价值链建立资源共享目标,并在约束条件下利用线性电力系统网络模型建立主导节点选择矩阵,划分资源共享集群。针对集成的分布式光伏资源,依据大数据联盟理论,将资源共享分为两种资源共享模式,建立资源共享动态模型,实现资源共享。结果表明,所提方法的资源共享效果较好,能够有效提升资源利用率,具有一定的应用价值。