A Steady-State Contingency Analysis of the SADC Regional Grid Using the N-1 Criterion

Southern Africa has experienced electric power deficits over the last decade. This has been due in part to the member countries＇ inadequate electrical power supply system, as well as load growth in areas which were not adequately planned for. This has induced the formation of organizations such as SADC （Southern African Development Community） and SAPP （Southern African Power Pool） that have the common goal of achieving development and economic growth in the region which comprises of 15 member countries. This paper presents results from a security analysis of the region＇s electric power supply system using a baseline level of performance. This was carried out by performing a steady-state contingency analysis on a SADC power network model subject to the N-1 criteria which expresses the ability of the power network to experience a contingency without causing an overload or failure in any other part of the network. Simulations were carried out using DigSilent.

Large-scale branch contingency analysis through master/slave parallel computing

Contingency analysis(CA)requires fast execution time for real-time power system operations.Because CA problems can naturally be divided into separate subtasks,parallel computing helps to speed up the computation time.This paper proposes a master/slave parallel computing architecture and studies the computation of CA in a large-scale power system through high performance computing,adopting a message passing interface for implementation.In particular,although the execution time of CA varies,there is a tradeoff between having an imbalanced workload and"paying"a synchronization penalty for parallel computing:either factor blocks the progress of scalability.The proposed layered dynamic scheduling method is effective to tackle the challenge of high synchronization cost and workload imbalance and have the potential to further scale for the N-2 contingency analysis.

Computing for power system operation and planning: Then, now, and the future

With the global trend of pursuing clean energy and decarbonization,power systems have been evolving in a fast pace that we have never seen in the history of electrification.This evolution makes the power system more dynamic and more distributed,with higher uncertainty.These new power system behaviors bring significant challenges in power system modeling and simulation as more data need to be analyzed for larger systems and more complex models to be solved in a shorter time period.The conventional computing approaches will not be sufficient for future power systems.This paper provides a historical review of computing for power system operation and planning,discusses technology advancements in high performance computing(HPC),and describes the drivers for employing HPC techniques.Some high performance computing application examples with different HPC techniques,including the latest quantum computing,are also presented to show how HPC techniques can help us be well prepared to meet the requirements of power system computing in a clean energy future.

Fuzzy Based Intelligent Monitoring of Critical Lines in the Restructured Power Market

Restructured electric market environment allows the power wheeling transactions between the power producers and customers to meet the growing load demand. This will lead to the possible of congestion in the transmission lines. The possible contingencies of power components further worsen the scenario. This paper describes the methodology for the identification of critical transmission line by computing the real power and reactive power performance indices. It also demonstrates the importance of fuzzy logic technique used to rank the transmission lines according to the severity and demonstrated on IEEE-30 bus system.

A novel collapse prediction index for voltage stability analysis and contingency ranking in power systems

Voltage instability is a serious phenomenon that can occur in a power system because of critical or stressed condi-tions.To prevent voltage collapse caused by such instability,accurate voltage collapse prediction is necessary for power system planning and operation.This paper proposes a novel collapse prediction index(NCPI)to assess the volt-age stability conditions of the power system and the critical conditions of lines.The effectiveness and applicability of the proposed index are investigated on the IEEE 30-bus and IEEE 118-bus systems and compared with the well-known existing indices(Lmn,FVSI,LQP,NLSI,and VSLI)under several power system operations to validate its practicability and versatility.The study also presents the sensitivity assumptions of existing indices and analyzes their impact on voltage collapse prediction.The application results under intensive case studies prove that the proposed index NCPI adapts to several operating power conditions.The results show the superiority of the proposed index in accurately estimating the maximum load-ability and predicting the critical lines,weak buses,and weak areas in medium and large networks during various power load operations and contingencies.A line interruption or generation unit outage in a power system can also lead to voltage collapse,and this is a contingency in the power system.Line and generation unit outage contingencies are examined to identify the lines and generators that significantly impact system stability in the event of an outage.The contingencies are also ranked to identify the most severe outages that significantly cause voltage collapse because of the outage of line or generator.

Graph Computing and Its Application in Power Grid Analysis

Approaches to apply graph computing to power grid analysis are systematically explained using real-world application examples.Through exploring the nature of the power grid and the characteristics of power grid analysis,the guidelines for selecting appropriate graph computing techniques for the application to power grid analysis are outlined.A custom graph model for representing the power grid for the analysis and simulation purpose and an in-memory computing(IMC)based graph-centric approach with a shared-everything architecture are introduced.Graph algorithms,including network topology processing and subgraph processing,and graph computing application scenarios,including in-memory computing,contingency analysis,and Common Information Model(CIM)model merge,are presented.

Graph Theory Based N-1 Transmission Contingency Selection and Its Application in Security-constrained Unit Commitment

Contingency analysis is an important building block in the stability and reliability analysis of power grid operations. However, due to the large number of transmission lines,in practice only a limited number of contingencies could be evaluated. This paper proposes a graph theory based N-1 contingency selection method to effectively identify the most critical contingencies, which can be used in security-constrained unit commitment(SCUC) problems to derive secure and economic operation decisions of the power grid. Specifically, the power flow transferring path identification algorithm and the vulnerability index are put forward to rank individual contingencies according to potential transmission line overloads. Effectiveness of the proposed N-1 contingency selection method is quantified by applying the corresponding SCUC solution to the full N-1 security evaluation, i. e., quantifying total post-contingency generation-load imbalance in all N-1 contingencies. Numerical results on several benchmark IEEE systems, including5-bus, 24-bus, and 118-bus systems, show effectiveness of the proposed method. Compared with existing contingency selection methods which usually resort to full power flow calculations,the proposed method relies on power gird topology to effectively identify critical contingencies for facilitating the optimal scheduling of SCUC problems.

MBA Students’Quality Improvement:The Correlation Analysis of Students’Personal Traits and Attitudes towards Teaching Methods at a Chinese University

MBA education has become the fastest growing segment of education in China in recent years and a segment that can now be considered indispensible.However,how best to teach it has long been a source of debate.One of the key issues is how to match student traits with teaching methods.While engaged as teachers of marketing management,the authors collected data by questionnaire,carried out empirical research and data comparison,and undertook contingency analysis.It was found that different personal traits in students lead to different attitudes towards teaching methods.A student’s major in college,gender,and sector of employment has little influence on attitudes towards teaching methods,while age,the most sensitive factor,plays the biggest role,followed by job and class.Therefore,these factors should be taken into consideration when arranging classes,developing the curriculum,and planning teaching methods.

An HPC Based Real-time Path Rating Calculation Tool for Congestion Management with High Penetration of Renewable Energy

Every year, transmission congestion costs billions ofdollars for electricity customers. This clearly identifies the criticalneed for more transmission capacity and also poses big challengesfor power grid reliability in stressed conditions due to heavyloading and in uncertain situations due to variable renewableresources and responsive smart loads. However, it becomesincreasingly difficult to build new transmission lines, whichtypically involve both economic and environmental constraints.In this paper, advanced computing techniques are developedto enable a non-wire solution that realizes unused transfercapabilities of existing transmission facilities. An integratedsoftware prototype powered by high-performance computing(HPC) is developed to calculate ratings of key transmission pathsin real time for relieving transmission congestion and facilitatingrenewable integration, while complying with the North AmericanElectric Reliability Corporation (NERC) standards on assessingtotal transfer capabilities. The innovative algorithms include: (1)massive contingency analysis enabled by dynamic load balancing,(2) parallel transient simulation to speed up single dynamicsimulation, (3) a non-iterative method for calculating voltagesecurity boundary and (4) an integrated package consideringall NERC required limits. This tool has been tested on realisticpower system models in the Western Interconnection of NorthAmerica and demonstrates satisfactory computational speedusing parallel computers. Various benefits of real-time path ratingare investigated at Bonneville Power Administration using realtime EMS snapshots, demonstrating a significant increase in pathlimits. These technologies would change the traditional goals ofpath rating studies, fundamentally transforming how the grid isoperated, and maximizing the utilization of national transmissionassets, as well as facilitating integration of renewable energy andsmart loads.

Cyber-physical Test Case for Distribution Grid Operation and Control

In the CPS-oriented power distribution system,a large number of the existing test cases cannot be accessed and reused.That is not conducive to the continuity of the CPS research of the distribution network.In response to above problem,based on an actual distribution network and considering the mapping relationship between cyber systems and physical systems,a computation test case that covers multiple power sources,and multiple types of load is proposed in this paper,and it is suitable for the simulation of multiple types of information system scenarios.In order to satisfy the specific needs of researchers for system topology and data,how to perform cyber contingency analysis,vulnerability assessment and distributed control are also discussed based on the existing topology and data.Researchers can utilize the test case presented in this paper to test their innovative methods in operational analysis,optimization control,and safety analysis for distribution networks.They can also utilize the published topologies and data to design their own test cases based on the methods in this paper.