CIM oriented graph database for network topology processing and applications integration

Although the standards-based systems integration of utility software applications using the domain data standard common information model (CIM) exists, many utilities are facing difficulties in managing of data exchanges among software application systems due to lack of standard oriented database management systems. The standard oriented database can be built from the CIM object oriented model using object-relational mapping (ORM). The generic design of ORM can handle object oriented model mapping to any database schema semantics. This paper presents a CIM oriented database (CIMODB) design through the object-relational mapping (ORM). The flexibility of data moving between object-oriented paradigms and relational database paradigms is achieved with the use of ORM concepts. Furthermore, the paper explores the integration of upstream power system applications with the proposed CIMODB, such as, topology processing, load-flow analysis, and more power system studies at the control center level from the legacy vendor software systems. A case study is illustrated to elaborate the CIMODB concept on the 400kV 20-substation Maharashtra network, which is the part of western region in India.

In a power system state estimator (SE), a network topology processor (NTP) determines the circuit breaker (CB) status in real-time to obtain electrical network topology. In a conventional NTP, many substation measurements are simply discarded because their positions in the simplified bus-branch network model are lost. These measurements cannot be used in the network observability analysis and when some of the used measurements are lost, an estimate of system states may not be obtained. This paper proposes an innovative method to utilize these redundant measurements. The new method uses a numerical matrix to represent the physical connectivity of substation devices, and then dynamically searches for solutions to calculate branch and bus injection power flow measurement data using the linear combination of the available substation measurement data. Test cases on IEEE-30 bus system verify that the proposed method is very effective in making the network observable, without the need to install new measurement devices

Modern utilities monitor and control the power system via a vast network of communication-enabled devices. The data generated from power plants to consumers has been treated independently and applications monitoring and controlling the power system have been operated separately. However, operation of the power system is now completely dependent on the exchange of data among the applications to achieve a comprehensive view of end-to-end reliability of the power system. In this paper, the integration of power system operational data and application is described.

Precise evaluation of fault current model parameters is an important issue in protection and automation systems. These parameters play a crucial role in selecting protective relay settings, detecting, and compensating saturated CT waveforms, calculating AC and DC components, estimating the sub-transient and transient time periods for the short-circuit current, determining fault locations, and controlling a fault interruption to avoid very fast transients that arise from switching. A new strategy for calculating the fault parameters using short-circuit current model is presented. The short-circuit current data is used to estimate fault inception angle, decay time constant, power system angle and maximum symmetrical AC fault current. The difference concept can be utilized to obtain precise mathematical formulas for evaluating the parameters of the fault current model. This is for efficient implementation of multiple functions that include digital protective relay, fault locator, digital filter, CT saturation detector and compensator. The strategy can be applied offline or in real-time. To verify the developed methodology, comprehensive numerical studies on a power system with real parameters data are presented. The power system is simulated using the Alternative Transient Program (ATP) tool. The algorithm is processed using MATLAB© software application. It is examined under variable operating and fault conditions for the system. The quantitative findings indicate that the method has high feasibility, and can achieve reliability, accuracy, and speed in estimating fault current parameters. The results also demonstrate the effectiveness of the proposed algorithm, as well as its robustness with respect to changes in system parameters. Its performance is sustainable as the data window moves, and it is immune to different fault and operational conditions. A key highlight of the proposed approach is the ability to perform many tasks of computer applications in power systems using the accurate calculated parameters for the fault current model.

In this study, an effective Web-enabled generalized architectural model is proposed. The proposed model makes the power system analysis to be completely secured, distributed, platform-independent and language-independent. Although significant progress has been made for on-line power system analysis in distributed environment, still efficient distributed environment has not yet been exploited. The Web-enabled architectural models are emerging as basic methodologies to support the integration of different power system applications using open Internet standard. The existing RMI models for solving multi-area power system problems in distributed environment, has its limitations to use in internet-based applets. The main objective of this study is to convert existing RMI model for power system applications into Web based model for on-line monitoring of multi-area power systems in distributed environment. Test bench has been created to carry out the performance analysis of the proposed model. Using the proposed model, load flow analysis is carried out for various bus systems. The results obtained are reported.

Nowadays, the increasing energy demand, development of smart grids, and the combination of different energy systems have led to the complexity of power systems. On the other hand, ever-expanding energy consumption, development of industry and technology systems, and high penetration of solar and wind energies have made electricity networks operate in more complex and uncertain conditions. Therefore, analysis of traditional power and energy systems requires physical modeling and extensive numerical computation. To analyze these systems’ behavior, advanced metering and condition monitoring devices and systems are utilized, which generate huge amounts of data. Assessment of these data is approximately impossible by conventional methods and requires powerful data mining procedures. Machine learning, deep learning, and a variety of regression, classification, and clustering algorithms are powerful tools to use in these issues. These procedures can be utilized for load/demand forecasting, demand response evaluation, defect/fault detection in electrical equipment, power system analysis and control, cybersecurity, and renewable energy generation prediction. Understanding the structure and functioning of each learning method is therefore one of the most important issues in the application of them to solve power system problems. In this chapter, we will introduce and discuss selected methods of data mining based on their learning, structure, formulation, mode of operation, and application in power systems. Literature on machine learning and deep learning procedures, train and test process of networked methods, and, finally, applications of each procedure are presented in this chapter.

Historically, databases in power systems were designed for certain applications and not oriented to information-sharing. The isolation among power system applications' databases hinders the development of a universal information infrastructure in the power system industry. To accommodate the trend of software development, the Electric Power Research Institute (EPRl) Working Group on Control Center Application Interfaces has published a standard data model-common information model (CIM) in IEC standard 61970. An overview of all the models is introduced. A central CIM database is proposed in this standard for large amount of common data-sharing among applications. Accordingly, conventions and procedures used to translate the CIM specification into a workable, real-world relational database are reaching maturity. EPRI also decided to use extensible markup language (XML) in resource descriptive frame (RDF) as the format for exchanging CIM data in power system applications and databases. This paper presents an overview of the CIM data models for power systems, the CIM implementations in database design, and the data exchange format for the applications.

In recent years, fuzzy set theory applications have received increasing attention in various areas of power systems such as operation, planning, and control. A number of research articles appeared which indicate applicability of fuzzy systems to power systems for wider operating conditions under uncertainties. While most of these systems are still under investigation, however, there already exist several practical applications of fuzzy systems. This paper presents a comprehensive set of references on fuzzy set theory applications in power systems.

This paper reviews robust feedback control applications in power system. Robust control concept in power system control area evolves by the way of uncertainty modeling. Uncertainties can be caused by variation of loading, load parameters, network topology and machine parameters. One direct way to take into consideration of uncertainties is to enumerate various system operating conditions and use a set of linear time invariant systems to model the power systems. Enumeration method is used in robust control signal selection and robust controller design. Another way is to model uncertainties as structured or unstructured uncertainties. Controllers are designed based on nominal system condition to tolerate uncertainty as much as possible. The controller synthesis problem is solved by either Algebraic Ricatti Equation (ARE) or Linear Matrix Inequality (LMI). LMI is shown to be more flexible in controller design since it provides a way to specify system dynamic performance. Most recently, linear parameter varying (LPV) concept expands the use of enumeration method to express a set of linear time invariant (LTI) systems with state space dependent on linear parameters. LPV based control methods extend gain scheduling to design linear control for each operating conditions and overall a nonlinear controller for the varying parameter system.

Cooperative revolutionary approach (CCA) is a new architecture of evolutionary computation. CCA simulates the coevolutionary mechanism in nature and adopts the notion of ecosystem. Multiple species in the ecosystem coevolve and interact with each other and result in the continuous evolution of the ecosystem. The application domain problem is mapped into the evolving ecosystem and solved when the coevolutionary process ends. Evolutionary game theory can be used to model CCA and to analyze its dynamical behaviors. CCA has been successfully applied to a wide variety of practical problems. The paper surveys the origin and development of CCA; introduces the basic theories of CCA and discusses the potential applications in power system and power market. CCA is a brand new research direction and has great potentials in solving increasingly complex problems emerging in power system and power market, such as power system optimal planning and operation, power market auction design and bidding strategy optimization etc.

A deep generative model for probabilistic energy forecasting in power systems: normalizing flows

The Flexible AC Transmission Systems (FACTS) control strategies inherits prime importance in power quality improvement with using endless numbers of devices to gain reactive power compensation and maintaining power factor. STATCOM plays a vital role and is highly acceptable and widely used in transmission and distribution networks as a dynamic shunt compensator due to its ultramodern characteristics. It serves several applications in power system, like, reactive power compensation, harmonics reduction, power factor improvement etc. and adds reliability of the system. The wide enhancement in STATCOM controller involves various solid-state converter terminologies, controlling algorithms, self-commuting operations, magnetic configurations etc. has been stated in many research works. This paper deals with a review on state-of-art STATCOM controlling device with meaningful applications in the power system.

Energy storage systems are pivotal for maximising the utilisation of renewable energy sources for smart grid and microgrid systems. Among the ongoing advancements in energy storage systems, the power conditioning systems for energy storage systems represent an area that can be significantly improved by using advanced power electronics converter designs and control techniques. Normally, the battery, flywheel, ultracapacitor and superconducting magnetic energy storage are the types of energy storage systems that typically require power conditioning systems for efficient bidirectional power flows. Compared to the previous review papers, this paper critically reviews the power conditioning system configurations and control techniques from the perspective of energy storage system applications in the power systems. First, the power conditioning systems are categorised into DC bus power conditioning systems and AC bus power conditioning systems based on the output voltage types at the connected point. Next, the topologies and control configurations of popular power electronics are comparatively analysed to highlight their advantages and power system applications. Moreover, the control configurations are discussed in terms of the popular applications of energy storage systems, that is, power backup smoothing, frequency regulation, voltage regulation and power quality applications. In addition, the latest developments in the energy storage system such as multi‐functional energy storage system stacking, artificial intelligence for power conditioning system of energy storage systems and security of control of energy storage systems are critically analysed. Finally, the review is concluded by discussing industrial applications and future research trends for the power conditioning systems of energy storage systems.

This article addresses the use of software tools by engineers, operators, and planners to handle complex issues in less amounts of time. The topics of the article include applications of artificial intelligence (AI) in power system operations applications such as customer restoration and fault testing, voltage and VAR dispatch, dynamic security analysis, voltage collapse, control center load management assistance, optimal power flow, and power system restoration; and applications in power system planning such as training, data verification, stability studies, load forecasting, outage scheduling, ranking of alternatives, power transaction evaluation, and evaluation of third-party generation alternatives.

Geographical Information System (GIS) applications are very helpful tools for displaying and analyzing information for several technological fields. The research group of Electrical Power System Lab (EPSL) of TEIC is developing a GIS software application for displaying the operational conditions of the power system of Crete, presenting also critical information and statistical data for system's characteristics. This tool is intended to help training of engineers in the Electrical Department of TEIC to simulate and visualize power system operation and characteristics. Besides, this tool is very helpful for a power system engineer in observing the whole system operations and system's data. All data used are derived from a database developed by EPSL. Digitalized maps of Crete Island use this database and display them optionally according to user's demand or choice. So, an authorized user can decide which data will be displayed on the map, and with a simple mouse click on a selected element of the map he can b informed about its characteristics. Furthermore, this application is being uploaded on web. This means that this application runs on a server of EPSL, which can serve distant users after authorization procedure. That distance user could be a trainee in his desk, or an engineer, or a researcher in the lab. One of the services that application provides is the load flow calculation on a specific part of the system, or for a specific scenario of system's operation.