Two-Stage Scheduling Model for Flexible Resources in Active Distribution Networks Based on Probabilistic Risk Perception

Aiming at the problems of increasing uncertainty of low-carbon generation energy in active distribution network(ADN)and the difficulty of security assessment of distribution network,this paper proposes a two-phase scheduling model for flexible resources in ADN based on probabilistic risk perception.First,a full-cycle probabilistic trend sequence is constructed based on the source-load historical data,and in the day-ahead scheduling phase,the response interval of the flexibility resources on the load and storage side is optimized based on the probabilistic trend,with the probability of the security boundary as the security constraint,and with the economy as the objective.Then in the intraday phase,the core security and economic operation boundary of theADNis screened in real time.Fromthere,it quantitatively senses the degree of threat to the core security and economic operation boundary under the current source-load prediction information,and identifies the strictly secure and low/high-risk time periods.Flexibility resources within the response interval are dynamically adjusted in real-time by focusing on high-risk periods to cope with future core risks of the distribution grid.Finally,the improved IEEE 33-node distribution system is simulated to obtain the flexibility resource scheduling scheme on the load and storage side.Thescheduling results are evaluated from the perspectives of risk probability and flexible resource utilization efficiency,and the analysis shows that the scheduling model in this paper can promote the consumption of low-carbon energy from wind and photovoltaic sourceswhile reducing the operational risk of the distribution network.

Securing offshore resources development:A mathematical investigation into gas leakage in long-distance flexible pipes

Gas flexible pipes are critical multi-layered equipment for offshore oil and gas development.Under high pressure conditions,small molecular components of natural gas dissolve into the polymer inner liner of the flexible pipes and further diffuse into the annular space,incurring annular pressure build-up and/or production of acidic environment,which poses serious challenges to the structure and integrity of the flexible pipes.Gas permeation in pipes is a complex phenomenon governed by various factors such as internal pressure and temperature,annular structure,external temperature.In a long-distance gas flexible pipe,moreover,gas permeation exhibits non-uniform features,and the gas permeated into the annular space flows along the metal gap.To assess the complex gas transport behavior in long-distance gas flexible pipes,a mathematical model is established in this paper considering the multiphase flow phenomena inside the flexible pipes,the diffusion of gas in the inner liner,and the gas seepage in the annular space under varying permeable properties of the annulus.In addition,the effect of a variable temperature is accounted.A numerical calculation method is accordingly constructed to solve the coupling mathematical equations.The annular permeability was shown to significantly influence the distribution of annular pressure.As permeability increases,the annular pressure tends to become more uniform,and the annular pressure at the wellhead rises more rapidly.After annular pressure relief followed by shut-in,the pressure increase follows a convex function.By simulating the pressure recovery pattern after pressure relief and comparing it with test results,we deduce that the annular permeability lies between 123 and 512 m D.The results help shed light upon assessing the annular pressure in long distance gas flexible pipes and thus ensure the security of gas transport in the emerging development of offshore resources.

Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

Research on Technic Realization of Flexible Enterprise Resource Plan

Based on the theory of dynamic enterprise model （DEM）, this paper focuses on describing the technic realization methods of DEM and its application in flexible enterprise resource plan （ERP） system. The complete and systematical description of various business activities in enterprises, quick response to business changes and the demanding adjustments are achieved with the conformation of the dynamic enterprise model platform and the utilization of the dynamic enterprise system model. Mass customization production is truly used in the implementation and development of ERP software.

Exploiting demand-side heterogeneous flexible resources in risk management of power system frequency

More demand-side flexible resources(DFRs)are participating in the frequency regulation of renewable power systems,whose heterogeneous characteristics have a significant impact on the system frequency response.Consequently,selecting suitable DFRs poses a formidable challenge for independent system operators(ISO).In this paper,a reserve allocation methodology for heterogeneous DFRs is proposed to manage the risk of power system frequency.Firstly,a performance curve is developed to describe the cost,capacity,and response speed of DFRs.Moreover,a clustering method for multiple distributed DFRs is conducted to calculate the aggregated performance curves and uncertainty coefficients.Then,the frequency security criterion considering DFRs’performance is constructed,whose linearity makes it can be easily coupled into the system scheduling model and solved.Furthermore,a risk management model for DFRs considering frequency-chance-constraint is proposed to make a trade-off between cost and frequency security.Finally,the model is transformed into mixed integer second-order cone programming(MISOCP)and solved by the commercial solver.The proposed model is validated by the IEEE 30 and IEEE 118 bus systems.

Optimal flexibility dispatch of demand side resources with high penetration of renewables:a Stackelberg game method

To promote the utilization of renewable energy,such as photovoltaics,this paper proposes an optimal flexibility dispatch method for demand-side resources(DSR)based on the Stackelberg game theory.First,the concept of the generalized DSR is analyzed and flexibility models for various DSR are constructed.Second,owing to the characteristics of small capacity but large-scale,an outer approximation is proposed to describe the aggregate flexibility of DSR.Then,the optimal flexibility dispatch model of DSR based on the Stackelberg game is established and a decentralized solution algorithm is designed to obtain the Stackelberg equilibrium.Finally,the actual data are utilized for the case study and the results show that,compared to the traditional centralized optimization method,the proposed optimal flexibility dispatch method can not only reduce the net load variability of the DSR aggregator but is beneficial for all DSR owners,which is more suitable for practical applications.

A Study on the Architecture of Flexible ERP Based on Multi-Agent Technology

Traditional ERP software system cannot efficiently su pport new management ideas such as BPR, DEM and virtual enterprise which emphasi zes that enterprise should be adjusted to market changes and business process ch ain and value chain should be integrated tightly. To solve these problems, this paper proposed the conception of Flexible ERP system. F-ERP is a self- adapti ve software system based on multi-agent technology. It developed the followin g kind of agents which are useful for F-ERP: business process agent, interf ace agent, data agent and decision and analysis agent. The F-ERP software syste m is an hierarchy system which is composed of data layer, system tools layer, bu siness application layer and business decision layer. It used component based de velopment mythology and complied with CORBA to development F-ERP. The F-ERP sy stem can support the new management ideas such as BPR, DEM and virtual enterpris e etc. By implementation of it, enterprise can improve its management and promot e its competence.

Review of demand-side energy sharing and collective self-consumption schemes in future power systems

The widespread use of distributed energy sources provides exciting potential for demand-side energy sharing and collective self-consumption schemes.Demand-side energy sharing and collective self-consumption systems are committed to coordinating the operation of distributed generation,energy storage,and load demand.Recently,with the development of Internet technology,sharing economy is rapidly penetrating various fields.The application of sharing economy in the energy sector enables more and more end-users to participate in energy transactions.However,the deployment of energy sharing technologies poses many challenges.This paper comprehensively reviews recent developments in demand-side energy sharing and collective self-consumption schemes.The definition and classification of sharing economy are presented,with a focus on the applications in the energy sector:virtual power plants,peer-to-peer energy trading,shared energy storage,and microgrid energy sharing cloud.Challenges and future research directions are thoroughly discussed.

A New Uniform-based Resource Constrained Total Project Float Measure （U-RCTPF）

Resource scheduling has become one of the most important activities in project management research and practice in the last decades. Recently, as part of this development, formal tools and techniques were developed to tackle the more complex problem of resource allocation or scheduling; that is, making sure both time constraints and resource constraints are met. In project scheduling, the concept of float and criticality plays a central role, however, the recent literature does not offer a general and useful measure for criticality （flexibility） in resource constrained projects. The resource constrained project total float measure （RCTPF） is defined as the sum of the total floats of activities, where the total float for an activity is defined as the difference of its latest and earliest start times. The RCTPF calculates the total float of each activity in order to maximize the total float of the project. However, not only the existence of float or its amount is important, but in many cases the distribution of the total amount of the float within the activities is even more significant. The following paper presents an extended measure to the existing RCTPF measure to solve this problem. The new measure, uniform-based resource constrained total project float measure （U-RCTPF）, is geared toward the uniform distribution of the project total float among the various project activities. The scheduling objective is to minimize the variation of the float among the activities. In this approach, a resource-constrained project is characterized by its best schedule, where best means a schedule in which the RCTPF is maximal and the uniformly measure is minimal.

Flexible resource allocation optimization model considering global K-means load clustering and renewable-energy consumption

Vigorously developing flexible resources in power systems will be the key to building a new power system and realizing energy trans-formation.The investment construction cost and operation cost of various flexible resources are different,and the adjustment ability is different in different timescales.Therefore,the optimization of complementary allocation of various resources needs to take into account the economy and adjustment ability of different resources.In this paper,the global K-means load clustering model is pro-posed and the 365-day net load is reduced to eight typical daily net loads by clustering.Secondly,a two-level optimization model of flexible resource complementary allocation considering wind power and photovoltaic consumption is constructed.The flexible resources involved include the flexible transformation of thermal power,hydropower,pumped storage,energy storage,and demand response.The upper-layer model optimizes the capacity allocation of various flexible resources with the minimum investment and construction cost as the goal and the lower layer optimizes the operating output of various units with the minimum operating cost as the goal.The results of the example analysis show that the flexible capacity of thermal power units has nothing to do with the abandonment rate of renewable energy.As the abandonment rate of renewable energy decreases,the optimal capacity of pumped storage,electrochemical energy storage,and hydropower units increases.When the power-abandonment rate of renewable energy is 5%,the optimal allocation capacity of thermal power flexibility transformation,pumped storage,electrochemical energy storage,hydropower unit,and adjustable load in Province A is 5313,17090,5830,72113,and 4250 MW,respectively.Under the condition that the renewable-energy abandonment rate is 0,5%,and 10%respectively,the configured capacity of pumped storage is 20000,17090,and 14847 MW,respectively.

Optimal scheduling of flexible grid-side resources and auxiliary service cost allocation model considering renewable-energy penetration

Renewable energy has penetrated power grid enterprises on a large scale.Due to the intermittency and volatility of renewable energy generation,it is necessary to build new flexible grid-side resources to ensure the safe and stable operation of the power grid,which will cause great pressure on cost allocation for power grid enterprises.This article considers four types of flexible grid-side resources and constructs a dual-level configuration optimization model for flexible grid-side resources under the penetration of renewable energy.Based on the configuration results,the cost scale of flexible grid-side resources is estimated and an improved ancillary service cost allocation model based on the Shapley value method is proposed to smooth the allocation of ancillary service costs in the cost of flexible grid-side resources between the two main bodies of renewable energy and load.The calculation results show that,when the penetration rate of renewable-energy power is 30%and 35%,respectively,the cost of flexible grid-side resources is 9.606 billion yuan and 21.518 billion yuan,respectively.The proportion of ancillary service costs allocated to load is relatively high-about five times that of the ancillary service costs allocated to renewable energy-and the higher the penetration rate of renewable energy,the higher the proportion of ancillary service costs allocated to renewable energy.

Assembly Unit Resource Balancing Strategy based on Discrete Production Mode

Aiming at the characteristics of obvious block division and strong discreteness in the assembly production mode of electronic products,this paper proposes a composite U-shaped flexible assembly line model,and establishes a multi-objective optimization mathematical model on this basis.According to the characteristics of the model,the improved ranked positional weight(RPW)method is used to adjust the generation process of the initial solution of the genetic algorithm,so that the genetic algorithm can be applied to the block task model.At the same time,the adaptive cross mutation factor is used on the premise that tasks between different blocks are not crossed during cross mutation,which effectively improves the probability of excellent individuals retaining.After that,the algorithm is used to iterate to obtain the optimal solution task assignment.Finally,the algorithm results are compared with actual production data,which verifies the validity and feasibility of the assembly line model for discrete production mode proposed in this paper.

面向能源安全的省级平衡主体多资源统一调度框架

针对新形势下省级平衡主体面临的能源安全挑战,提出一种多资源、多时间尺度、多颗粒度的统一调度框架。该框架以日前短期调度为基础,通过预测性调度考虑远期能源预测和市场交易总量,兼顾长周期计划的统筹配置作用与短周期计划的精准调度能力。在模型中考虑天然气、跨省区购电以及本地需求响应等多种资源,充分挖掘多方资源的调节能力,实现多方资源的互济与补充。算例仿真结果表明,所提框架实现了全周期调度的高效日前求解,相较于传统固化的调度机制,所提框架对负荷的随机性具有更高的适应能力。

考虑多元灵活性资源协同的配电网韧性提升策略

在台风灾害频发以及新能源发电渗透率日益攀升的双重背景下,文中提出了包含规模化电动汽车(electric vehicle,EV)在内的多元灵活性资源滚动优化调度策略,以提升台风灾害下配电网韧性。首先,根据典型气象特征,通过蒙特卡洛法模拟所在区域的线路和光伏(photovoltaic,PV)的故障场景,并利用系统信息熵进行典型场景筛选,得到线路和PV的时序故障状态。其次,以最小化加权负荷损失率为目标建立多元灵活性资源优化调度模型。基于EV的时空特征对其进行征用调控,并通过网架重构、协调移动应急发电机(mobile emergency generators,MEG)等手段协同互补以最大化利用网内资源。最后,为适应系统故障状态的演化,实时调整调度方案,提出降低问题求解复杂度的两阶段滚动求解方法。以改进后的江苏某地实际供电单元网络为研究对象进行仿真分析,结果表明所提策略可有效降低负荷损失,提升配电网在极端场景下的韧性。

时空约束下资源受限的多智能体柔性重叠组织建模

在资源受限的多智能体系统中,智能体通常需要与其他智能体协作并获取资源,从而实现增加总体收益或完成复杂任务的目的。而开放系统中资源需求和供应的不确定性导致了信息不对称和竞争加剧,从而增加了资源分配的复杂性和协作成本。因此,构建时空约束下的柔性重叠组织框架。该框架一方面融合时空约束提升信息的时效性及资源分配的合理性,另一方面支持柔性重叠组织使智能体能够同时订阅多个资源,进一步缓解资源受限的问题。此外,提出了时空约束下的资源选择算法解决资源的不均衡使用;同时提出了协作策略生成算法来降低资源竞争。最后,在开放的多智能体系统仿真环境中对所提方法进行评估,在不同资源需求、智能体流动性的情况下对任务完成数量、任务成功率和资源利用率进行分析。实验结果表明,使用时空约束下的柔性重叠组织框架可以有效缓解资源受限问题并提高任务成功率和资源利用率。

考虑转移时间的多目标双资源柔性作业车间节能调度

针对考虑工人和工件在机器间转移时间的多目标双资源柔性作业车间节能调度问题(MO-DFJESP),构建了以最小化最大完工时间、总能耗、总工人成本和最大工人工作量为优化目标的数学模型。该模型同时还考虑了工人的技能、熟练度和单位成本差异。为了求解MO-DFJESP模型,提出一种多目标混合进化算法(MO-HEATS)。根据MO-DFJESP模型特点,设计了一种多维编码和解码方案以表示问题的可行解。基于sigmoid函数设计了自适应机制,以兼顾MO-HEATS算法的开发和探索能力,并结合禁忌搜索(TS)组件提升局部搜索能力。最后,在仿真算例上进行了消融实验和对比实验,实验结果验证了自适应机制和TS组件对MO-HEATS算法性能具有明显提升作用,且MO-HEATS算法对求解MO-DFJESP模型具有显著优势。

多类型灵活资源参与下的主动配电网电化学储能检修优化策略

电化学储能电站作为电力系统应对新能源并网问题、实现功率平衡的有效手段,其运维工作至关重要,亟需制定合理的检修计划。为提高电化学储能电站检修计划的经济性与可靠性,提出一种多类型灵活资源参与下的主动配电网储能电站检修策略。首先,搭建移动式储能、应急电源车以及变频空调集群在内的多类型灵活资源运行模型,为检修工作提供额外的功率支撑;然后,基于主动配电网系统运行约束与储能设备检修计划约束,搭建电化学储能电站检修多目标优化模型,并采用宽容分层序列法求解对应的最优检修方案;最后,基于IEEE 33节点系统进行了仿真分析,结果表明,所提策略可以兼顾设备及时检修需求与电网安全经济运行需求。

基于改进边界收缩算法的灵活性资源聚合模型

在需求侧,调控储能、电动汽车等灵活性资源是提高配电系统灵活性的重要手段。为更准确地刻画灵活性资源集群的聚合灵活性,提出基于改进边界收缩算法的灵活性聚合方法。首先将灵活性资源刻画为等效储能模型,随后采用基于高维多面体的边界收缩算法来求解聚合等效模型的参数;在此基础上,通过调节等效储能模型的自放电系数来调节聚合等效模型外接多面体多个超平面的斜率,从而改变收缩后内近似投影多面体的形状;接着采用蒙特卡洛模拟法对原始聚合可行域进行采样,并计算聚合等效模型可行轨迹的样本覆盖率,将其作为方法近似效果的评估指标;最后,基于粒子群算法寻找模型具有最大内近似投影多面体时的自放电系数,从而获得等效储能的最优参数。算例结果表明,相比原方法,改进后的边界收缩算法能覆盖到更大的可行域空间,近似精度提高了13.54%,结果具有更低的保守性。

Optimal Operation of an Integrated Electricity-heat Energy System Considering Flexible Resources Dispatch for Renewable Integration

Large fluctuations may occur on the energy supply and the load sides when large-scale renewable energies are integrated,leading to great challenges in power systems.The renewable power curtailment is especially numerous in the integrated electricity-heat energy system(IEHES)on account of electricity-heat coupling.The flexible resources(FRs)on both the energy supply and load sides are introduced into the optimal dispatch of the IEHES and further modeled to alleviate the renewable fluctuations in this paper.On the energy supply side,three kinds of FRs based on electricity-heat coordination are modeled and discussed.On the load side,the shiftable electricity demand resource is characterized.On this basis,the solution for FRs participating in IEHES dispatch is given,with goals of maximizing the renewable penetration ratio and lowering operation costs.Two scenarios are performed,and the results indicate that the proposed optimal dispatch strategy can effectively reduce the renewable energy curtailment and improve the flexibility of the IEHES.The contribution degrees of different FRs for renewable integration are also explored.

Stochastic Security-constrained Unit Commitment Considering Electric Vehicles, Energy Storage Systems, and Flexible Loads with Renewable Energy Resources

In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming(MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency.