Complex Variable Multi-phase Distribution System State Estimation Using Vectorized Code

Džafić, Izudin; Jabr, Rabih A.; Hrnjic, Tarik

doi:10.35833/mpce.2020.000033

Cited by 14 publications

(5 citation statements)

References 26 publications

(40 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second method is a classical WLS estimator involving previously retrieved measurements within a time window. Moreover, distribution system three-phase SE in complex variables is investigated in [215]- [216]. Similar to that in TSSE, the real-valued measurement function is expanded via Wirtinger calculus in terms of the nodal voltage phasors and their conjugates.…”

Section: Handling Multiple Reporting Rates and Asynchronizationmentioning

confidence: 99%

“…The complex variable-based estimator is intended to incorporate historical data, SM data, and synchronized phasor measurements. In [216], the measurement set consists of SCADA, > REPLACE THIS LINE WITH YOUR MANUSCRIPT ID NUMBER (DOUBLE-CLICK HERE TO EDIT) < PMU, pseudo, and virtual measurements. The vector of measurement functions includes a vector of complex-valued measurements and their conjugates, along with a vector of real-valued measurement functions.…”

Section: Handling Multiple Reporting Rates and Asynchronizationmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Power System State Estimation Using Multiple Data Sources: PMUs, SCADA, AMI, and Beyond

Lin¹,

Abur²,

Gómez-Expósito³

et al. 2024

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

State estimation (SE) is indispensable for the situational awareness of power systems. Conventional SE is fed by measurements collected from the supervisory control and data acquisition (SCADA) system. In recent years, available data sources have been greatly enriched with the deployment of phasor measurement units (PMUs), advanced metering infrastructure (AMI), intelligent electronic devices (IEDs), etc. The integration of multiple data sources provides unprecedented opportunities for enhancing the performance of SE, but also presents major challenges to resolve, including optimal multi-type-sensor co-placement, multiple reporting rates and asynchronization, diverse types of measured quantities, correlations between measurements, integration of online and historical data sources, and system and measurement uncertainties. This paper outlines the state of the art and research opportunities in this area by providing a comprehensive literature review and extensive discussions. It starts by presenting the motivations and challenges, followed by a summary of existing data sources for SE in power systems. Subsequently, for both transmission system (static and dynamic) and distribution system SE, existing methods are systematically reviewed and categorized based on the addressed challenges. Interesting attempts of using novel measurements in SE are also studied. Finally, the paper concludes by providing a detailed discussion on the remaining research gaps and future research directions to be explored.

show abstract

Section: Handling Multiple Reporting Rates and Asynchronizationmentioning

confidence: 99%

Section: Handling Multiple Reporting Rates and Asynchronizationmentioning

confidence: 99%

A Survey of Power System State Estimation Using Multiple Data Sources: PMUs, SCADA, AMI, and Beyond

Lin¹,

Abur²,

Gómez-Expósito³

et al. 2024

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

show abstract

“…3) Distribution system state estimation (DSSE). DSSE estimates the state vector of distribution networks by applying a weighted least-squares approach on a redundant set of measurements [24], [25]. A current or power balancing method is commonly adopted in industrial implementations to achieve high-performance computation [26], [27].…”

Section: Main Functions Of Dms For Smart Gridmentioning

confidence: 99%

Distribution Management Systems for Smart Grid: Architecture, Work Flows, and Interoperability

Jabr

Džafić

2022

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

The smart grid integrates advanced sensors, a twoway communication infrastructure, and high-performance computation-based control. The distribution management systems for smart grid include several functions for manipulating legacy voltage control devices and distributed energy resources through closed-loop volt/var control, leading to wide-area regulation of voltages in the presence of fluctuating power. The other primary distribution network analysis application is concerned with automatic fault location and service restoration following fault events, aiming to provide the grid with autonomous intelligence for self-healing. Communication technologies are vital to enable the computing applications of distribution networks, whether they work in centralized or distributed modes. This paper presents the state of the art in distribution management system architectures and modern workflows showing data exchange, practical parallel implementations designed to handle large amounts of data, in addition to communication standards that serve as interoperability enablers. It demystifies the relationship between different functions developed independently by power system researchers and shows their operation as a complete system, thus placing them in a better context for future research and development.

show abstract

“…AMI data measure the energy, which cannot be treated as other real-time measurements. AMI is taken as an input to short-term prosumer forecast (STPF) and then delivered as pseudo-measurement with probably higher weighting to distribution system state estimator (DSSE) [5], [6].…”

Section: A Increasing Technology and Automationmentioning

confidence: 99%

Distribution Control Centers in the US and Europe: Commonalities, Differences, and Lessons

Vadari¹,

Džafić

Koch

et al. 2022

Journal of Modern Power Systems and Clean Energy

Self Cite

View full text Add to dashboard Cite

The distribution control center (DCC) has evolved from a sideshow in the traditional distribution service center to a major centerpiece of the utility moving into the decentralized world. Mostly, this is the place where much of the action is happening due to new forms of energy that are coming into the distribution system. This creates the flexibility of operation and increased complexity due to the need for increased coordination between the transmission control center and DCC. However, the US and European utilities have adapted to this change in very different ways. Firstly, we describe the research works done in a DCC and their evolutions from the perspectives of major US utilities, and those enhanced by the European perspective focusing on the coordination of distribution system operator and transmission system operator (DSO-TSO). We present the insights into the systems used in these control centers and the role of vendors in their evolution. Throughout this paper, we present the perspectives of challenges, operational capabilities, and the involvement of various parties who will be responsible to make the transition successful. Key differences are pointed out on how distribution operations are conducted between the US and Europe.

show abstract

Complex Variable Multi-phase Distribution System State Estimation Using Vectorized Code

Cited by 14 publications

References 26 publications

A Survey of Power System State Estimation Using Multiple Data Sources: PMUs, SCADA, AMI, and Beyond

A Survey of Power System State Estimation Using Multiple Data Sources: PMUs, SCADA, AMI, and Beyond

Distribution Management Systems for Smart Grid: Architecture, Work Flows, and Interoperability

Distribution Control Centers in the US and Europe: Commonalities, Differences, and Lessons

Contact Info

Product

Resources

About