An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

Modeling Simulation Technology Research for Distribution Network Planning

This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, simulating the abnormal condition of distribution network, and presenting operation program of safe, reliable and having simulation record statements. The modeling simulation results show that the software module has lots of advantages including high accuracy, ideal reliability, powerful practicality in simulation and analysis of distribution network, it only need to create once model, the model can sufficiently satisfy multifarious types of simulation analysis required for the distribution network planning.

The Online Assessment of Electric Distribution Network Load Capability

To improve the security and reliability of a distribution network, several issues, such as influences of operation con-strains, real-time load margin calculation, and online security level evaluation, are with great significance. In this pa-per, a mathematical model for load capability online assessment of a distribution network is established, and a repeti-tive power flow calculation algorithm is proposed to solve the problem as well. With assessment on three levels: the entire distribution network, a sub-area of the network and a load bus, the security level of current operation mode and load transfer capability during outage are thus obtained. The results can provide guidelines for prevention control, as well as restoration control. Simulation results show that the method is simple, fast and can be applied to distribution networks belonged to any voltage level while taking into account all of the operation constraints.

A Method for Distributed Generator Dispatch Strategy in Distribution Network

Since a load of power system changes continuously,the generation also adjusted for supply-demand balance purpose.If there exist more distributed generators in the distribution network,the dispatch strategy becomes more crucial.The possibility of having numerous controllable microgrids,diesel generator(DG)units and loads for microgrids(MGs)system requires an efficient dispatch strategy in order to balance supply demand for reducing the total cost of the integrated system.In this paper,a method for the dispatch of the distributed generator in distributed power systems has been proposed.The dispatch strategy is such that it keeps a flat voltage profile,reduces the network losses,increases the maximum loading and voltage security margin of the system.The procedure is based on the analysis of continuous power flow.The method is executed on a 34-bus test system.The MATLAB based PSAT packages are used for simulation purpose.

Scheme of long distance power supply for electrified railway traction network based on traction cable

Purpose–The traction cable is paralleled with the existing traction network of electrified railway through transverse connecting line to form the scheme of long distance power supply for the traction network.This paper aims to study the scheme composition and power supply distance(PSD)of the scheme.Design/methodology/approach–Based on the structure of parallel traction network(referred to as“cable traction network(CTN)”),the power supply modes(PSMs)are divided into cableþdirect PSM and cableþautotransformer(AT)PSM(including Japanese mode,French mode and new mode).Taking cableþJapanese AT PSM as an example,the scheme of long distance power supply for CTN under the PSMs of co-phase and out-of-phase power supply are designed.On the basis of establishing the equivalent circuit model and the chain circuit model of CTN,taking the train working voltage as the constraint condition,and based on the power flow calculation of multiple train loads,the calculation formula and process for determining the PSD of CTN are given.The impedance and PSD of CTN under the cableþAT PSM are simulated and analyzed,and a certain line is taken as an example to compare the scheme design.Findings–Results show that the equivalent impedance of CTN under the cableþAT PSM is smaller,and the PSD is about 2.5 times of that under the AT PSM,which can effectively increase the PSD and the flexibility of external power supply location.Originality/value–The research content can effectively improve the PSD of traction power supply system and has important reference value for the engineering application of the scheme.

Power Flow Model for Medium-voltage Distribution Systems Considering Measurement and Structure Characteristics

Medium-voltage distribution systems(MVDSs)mainly consist of a feeder head,lines,distribution transformers,and the equivalent load or power supply interfaced with the distribution transformers.The information of such load or power supply can be measured via the three-wattmeter method(THM)and the two-wattmeter method(TWM).The measurements can be used to perform the control of the power supply and simulate the characteristics of the load,so the models of the load and the power supply need to consider the measurement characteristics.Existing research works on three-phase power flow(PF)just consider the measurement characteristics of THM.Hence,the PF equation of the bus measured via TWM is firstly built.Based on conventional measurements,an accurate and general model of the grounded and ungrounded slack bus is proposed.Furthermore,the influence arising from the connection type and angle shift of distribution transformers on the admittance matrix is considered,and thus a general three-phase transformer model is summarized,which is applicable for all the transformers mentioned herein.Finally,Newton's method is adopted to solve the PF calculation,and the performance of the proposed PF model is demonstrated through designed tests.

Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable generation.Due to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their operations.To tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible samples.However,since ADNs are mostly operated in a normal status,only very few historical samples are infeasible.Thus,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network training.To address this issue,we propose an enhanced constraint learning method.First,it leverages constraint learning to train a neural network as surrogate of ADN's model.Then,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical dataset.By incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural network.Furthermore,we establish a trust region to constrain and thereafter enhance reliability of the solution.Simulations confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

Interval optimal power flow applied to distribution networks under uncertainty of loads and renewable resources

Optimal power flow(OPF) has been used for energy dispatching in active distribution networks.To satisfy constraints fully and achieve strict operational bounds under the uncertainties from loads and sources, this paper derives an interval optimal power flow(I-OPF)method employing affine arithmetic and interval Taylor expansion.An enhanced I-OPF method based on successive linear approximation and second-order cone programming is developed to improve solution accuracy.The proposed methods are benchmarked against Monte Carlo simulation(MCS) and stochastic OPF.Tests on a modified IEEE 33-bus system and a real 113-bus distribution network validate the effectiveness and applicability of the proposed methods.

Distributed continuation power flow method for integrated transmission and active distribution network

As the integration of distributed generations(DGs)transforms the traditional distribution network into the active distribution network,voltage stability assessments(VSA)of transmission grid and distribution grid are not suitable to be studied separately.This paper presents a distributed continuation power flow method for VSA of global transmission and distribution grid.Two different parameterization schemes are adopted to guarantee the coherence of load growth in transmission and distribution grids.In the correction step,the boundary bus voltage,load parameter and equivalent power are communicated between the transmission and distribution control centers to realize the distributed computation of load margin.The optimal multiplier technique is used to improve the convergence of the proposed method.The three-phase unbalanced characteristic of distribution networks and the reactive capability limits of DGs are considered.Simulation results on two integrated transmission and distribution test systems show that the proposed method is effective.

Linear Three-Phase Power Flow for Unbalanced Active Distribution Networks with PV Nodes

High penetration of distributed renewable energy promotes the development of an active distribution network(ADN).The power flow calculation is the basis of ADN analysis.This paper proposes an approximate linear three-phase power flow model for an ADN with the consideration of the ZIP model of the loads and PV nodes.The proposed method is not limited to radial topology and can handle high R/X ratio branches.Case studies on the IEEE 37-node distribution network show a high accuracy and the proposed method is applicable to practical uses such as linear or convex optimal power flow of the ADN.

Deep Reinforcement Learning Based Approach for Optimal Power Flow of Distribution Networks Embedded with Renewable Energy and Storage Devices

This study proposes a deep reinforcement learning(DRL)based approach to analyze the optimal power flow(OPF)of distribution networks(DNs)embedded with renewable energy and storage devices.First,the OPF of the DN is formulated as a stochastic nonlinear programming problem.Then,the multi-period nonlinear programming decision problem is formulated as a Markov decision process(MDP),which is composed of multiple single-time-step sub-problems.Subsequently,the state-of-the-art DRL algorithm,i.e.,proximal policy optimization(PPO),is used to solve the MDP sequentially considering the impact on the future.Neural networks are used to extract operation knowledge from historical data offline and provide online decisions according to the real-time state of the DN.The proposed approach fully exploits the historical data and reduces the influence of the prediction error on the optimization results.The proposed real-time control strategy can provide more flexible decisions and achieve better performance than the pre-determined ones.Comparative results demonstrate the effectiveness of the proposed approach.

Coordination Control of Power Flow Controller and Hybrid DC Circuit Breaker in MVDC Distribution Networks

The two main challenges of medium voltage direct current(MVDC)distribution network are the flexible control of power flow(PF)and fault protection.In this paper,the power flow controller(PFC)is introduced to regulate the PF and inhibit the fault current during the DC fault.The coordination strategy of series-parallel PFC(SP-PFC)and hybrid DC circuit breaker(DCCB)is proposed.By regulating the polarity and magnitude of SP-PFC output voltage during the fault,the rising speed of fault current can be suppressed so as to reduce the breaking current of hybrid DCCB.The access mode of SP-PFC to the MVDC distribution network and its topology are analyzed,and the coordination strategy between SP-PFC and hybrid DCCB is investigated.Moreover,the emergency control and bypass control strategies of SP-PFC are developed.On this basis,the mathematical model of SP-PFC in different fault stages is derived.With the equivalent model of SP-PFC,the fault current of the MVDC distribution network can be calculated accurately.A simulation model of the MVDC distribution network containing SP-PFC is established in MATLAB/Simulink.The fault current calculation result is compared with the simulation result,and the effectiveness of the proposed coordination strategy is verified.

Novel Affine Power Flow Method for Improving Accuracy of Interval Power Flow Data in Cyber Physical Systems of Active Distribution Networks

A large number of load power and power output of distributed generation in an active distribution network(ADN)are uncertain,which causes the classical affine power flow method to encounter problems of interval expansion and low efficiency when applied to an AND.This then leads to errors of interval power flow data sources in the cyber physical system(CPS)of an ADN.In order to improve the accuracy of interval power flow data in the CPS of an ADN,an affine power flow method of an ADN for restraining interval expansion is proposed.Aiming at the expansion of interval results caused by the approximation error of non-affine operations in an affine power flow method,the approximation method of the new noise source coefficient is improved,and it is proved that the improved method is superior to the classical method in restraining interval expansion.To overcome the decrease of computational efficiency caused by new noise sources,a novel merging method of new noise sources in an iterative process is designed.Simulation tests are conducted on an IEEE 33-bus,PG&E 69-bus and an actual 1180-bus system,which proves the validity of the proposed affine power flow method and its advantages in terms of computational efficiency and restraining interval expansion.

A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first analyzed.Considering that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is proposed.Compared with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are discussed.Furthermore,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power flow.Numerical experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark methods.Meanwhile,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional methods.Also,in some cases,where conventional methods diverge,these LSI methods can still converge.

Planning Model for Energy Routers Considering Peer-to-Peer Energy Transactions Among Multiple Distribution Networks

A high proportion of renewable energy affects the power quality of distribution networks,and surplus energy will be sold to the upstream grid at a low price.In this paper,considering peer-to-peer energy transactions,the energy router-based multiple distribution networks are analyzed to solve the above problems and realize collaborative consumption of renewable energy.Presently,the investing cost of an energy router is high,and research on the economic operation of energy routers in distribution networks is little.Therefore,this paper establishes a planning model for energy routers considering peer-to-peer energy transactions among distribution networks,and explores the benefits of peer-to-peer energy transactions through energy router based multiple distribution networks.A structure of an energy router suitable for peer-to-peer energy transactions is selected,and a power flow calculation model based on a multilayer structure is established.The energy router’s scheduling model is established,and unique functions of the energy router and revenue of each distribution network are considered.A power flow calculation model based on peer-to-peer interconnection of multiple distribution networks through energy routers is also established.Finally,simulation results verify the effectiveness of the proposed planning model.Results show that peer-topeer energy transaction among distribution networks through energy routers can effectively reduce the comprehensive cost of distribution networks,significantly improve the power quality of the distribution networks,and reduce the impact of power fluctuation on the upstream grid incurred by the distribution network.

Cloud-based parallel power flow calculation using resilient distributed datasets and directed acyclic graph

With the integration of distributed generation and the construction of cross-regional long-distance power grids, power systems become larger and more complex.They require faster computing speed and better scalability for power flow calculations to support unit dispatch.Based on the analysis of a variety of parallelization methods, this paper deploys the large-scale power flow calculation task on a cloud computing platform using resilient distributed datasets(RDDs).It optimizes a directed acyclic graph that is stored in the RDDs to solve the low performance problem of the MapReduce model.This paper constructs and simulates a power flow calculation on a large-scale power system based on standard IEEE test data.Experiments are conducted on Spark cluster which is deployed as a cloud computing platform.They show that the advantages of this method are not obvious at small scale, but the performance is superior to the stand-alone model and the MapReduce model for large-scale calculations.In addition, running time will be reduced when adding cluster nodes.Although not tested under practical conditions, this paper provides a new way of thinking about parallel power flow calculations in large-scale power systems.

基于PSASP和Power Factory的分解协调式输配一体化潮流计算

大量分布式电源的并网改变了配电网单向潮流特性,输电网和配电网之间的耦合更加紧密,电力系统呈现出主配网一体化的特点。文章提出了基于分解协调的主配一体化潮流计算方法,分别采用PSASP和Power Factory进行输电网和配电网的计算,设计了主网和配网潮流的边界协调方程,并采用Jacobian-Free Newton-GMRES(m)方法进行求解。测试结果表明,文章所提方法收敛性较好,计算精度高。

主动配电网潮流的全纯嵌入计算方法

配电网潮流计算是进行配电网规划和运行的重要基础。目前,配电网潮流求解方法主要有牛拉(Newton Raphson,NR)法和前推回代(forward backward substitution,FBS)法两大类,但NR法和FBS法在潮流收敛性和计算效率等方面均存在一定的不足。全纯嵌入法(holomorphic embedding method,HEM)是一种求解非线性潮流方程的新方法,它可以有效避免NR法和FBS法在配电网潮流求解过程中出现的上述问题,但现有HEM未充分考虑配电网中各类型分布式电源(distributed generation,DG)和智能软开关(soft open point,SOP)控制方式的多样性,且未构建计及负荷电压特性和频率特性的潮流模型,难以适用于不同运行模式下配电网潮流计算。针对上述问题,提出一种可求解含多类型DG和SOP且可运行在并网/孤岛模式的主动配电网统一全纯嵌入潮流计算方法。首先,根据负荷静态电压和频率特性,构建计及配电网频率和节点电压影响的负荷节点全纯嵌入潮流模型;其次,根据DG不同的控制方式以及配电网不同的运行模式,将DG所连节点等效为不同节点类型,构建各类DG的全纯嵌入潮流模型;再次,考虑SOP不同控制方式,构建SOP全纯嵌入潮流模型;从次,依据全纯嵌入潮流模型等式左右两侧同次幂级数系数相等原则,推导配电网各全纯函数幂级数系数的求解递推关系式,进而计算各全纯函数的各项幂级数系数,借助解析延拓理论求取电压和频率逼近值,实现配电网潮流的准确求解;最后,通过修改的IEEE-33节点测试系统和IEEE-123节点测试系统验证所提方法准确性和有效性。

MATPOWER平台下配电网潮流算法的应用及比较

提出了配电网潮流算法在MATPOWER平台下应用的解决方案。同时基于MATPOWER平台,针对辐射状配电网,对牛顿拉夫逊法和前推回代法在收敛性、计算速度、稳定性以及网孔处理能力上进行了细致的研究比较。为配电网潮流计算系统的核心算法选取提供了实验理论依据。