Transition to a sustainable energy environment results in aggregated generator and load dynamics in the distribution network. State estimation is a key function in building adequate network models for online monitoring and analyzes. The requirements of distribution system state estimation (DSSE) is becoming stringent because of the needs of new system modeling and operation practices associated with integration of distributed energy resources and the adoption of advanced technologies in distribution network. This paper summarizes the state-of-the-art technology, major hurdles, and challenges in DSSE development. The opportunities, paradigm shift, and future research directions that could facilitate the need of DSSE are discussed.

A Review on Distribution System State Estimation

This paper presents a review of the literature on State Estimation (SE) in power systems While covering some works related to SE in transmission systems, the main focus of this paper is Distribution System State Estimation (DSSE) The paper discusses a few critical topics of DSSE, including mathematical problem formulation, application of pseudo-measurements, metering instrument placement, network topology issues, impacts of renewable penetration, and cyber-security Both conventional and modern data-driven and probabilistic techniques have been reviewed This paper can provide researchers and utility engineers with insights into the technical achievements, barriers, and future research directions of DSSE

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

Distribution systems are undergoing many enhancements and developments to enable the future smart grid, and distribution system state estimation (DSSE) provides the control centers with the information necessary for several of its applications and operational functions. However, the quality of DSSE typically suffers from a lack of adequate/accurate measurements. Recently, many electric utilities have started to install fairly accurate smart meters throughout their distribution networks, which create an opportunity to achieve higher quality DSSE. However, the signals provided by smart meters are generally not synchronized and the difference between the measurement times of smart meters can be significant. Therefore, a complete snapshot of the entire distribution system may not be available. This paper proposes a method to deal with the issue of nonsynchronized measurements coming from smart meters based on the credibility of each available measurement and appropriately adjusting the variance of the measurement devices. To illustrate the effectiveness of the proposed method, two IEEE benchmark systems are used. The results show that the proposed method is robust and improves the accuracy of DSSE compared with the traditional DSSE approach.

Distribution System State Estimation Based on Nonsynchronized Smart Meters

This paper presents a review of the literature on state estimation (SE) in power systems. While covering works related to SE in transmission systems, the main focus of this paper is distribution system SE (DSSE). The critical topics of DSSE, including mathematical problem formulation, application of pseudo-measurements, metering instrument placement, network topology issues, impacts of renewable penetration, and cyber-security are discussed. Both conventional and modern data-driven and probabilistic techniques have been reviewed. This paper can provide researchers and utility engineers with insights into the technical achievements, barriers, and future research directions of DSSE.

We describe the real-time monitoring infrastructure of the smart-grid pilot on the EPFL campus. We experimentally validate the concept of a real-time state-estimation for a 20 kV active distribution network. We designed and put into operation the whole infrastructure composed by the following main elements: (1) dedicated PMUs connected on the medium-voltage side of the network secondary substations by means of specific current/voltage transducers; (2) a dedicated communication network engineered to support stringent time limits and (3) an innovative state estimation process for real-time monitoring that incorporates phasor-data concentration and state estimation processes. Special care was taken to make the whole chain resilient to cyber-attacks, equipment failures and power outages. The achieved latency is within 65ms. The refresh rate of the estimated state is 20ms. The real-time visualization of the state estimator output is made publicly available, as well as the historical data (PMU measurements and estimated states). To the best of our knowledge, the work presented here is the first operational system that provides low-latency real-time state-estimation by using PMU measurements of a real active distribution network.

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Real-time state estimation of the EPFL-campus medium-voltage grid by using PMUs

The object of this paper is to share experiences on deployment and tuning of real-time advanced applications for distribution and distribution state estimator at BC Hydro control center. During past 4 years, BC Hydro has been engaged in the project to procure Distribution Management System (DMS) with objective to enable real-time power system monitoring and control of distribution network in an optimal manner. The emphasis was placed on advanced network applications such as Volt-Var Optimization that are expected to improve the performance and reliability of distribution network. However, a key application that provides basic inputs to advanced applications is distribution state estimator that calculates power system state of distribution network in the real-time. Deployment of state estimator is a difficult process that relies on a number of prerequisites that include, establishing of distribution network model, calibrating and mapping real-time telemetry, extensive software testing and application tuning.

Deployment of real-time state estimator and load flow in BC Hydro DMS - challenges and opportunities

The objective of this paper is to present and share experiences and challenges in Voltage VAR optimization (VVO) real time closed loop deployment at BC Hydro control center. VVO deployment at BC Hydro is focused to maximize energy savings and therefore the closed loop execution is required on continuous 24/7 basis. Several characteristic requirements for closed loop operation were integral for successful VVO deployment. This paper presents foundation elements for VVO closed loop real time execution and some deployment challenges from the system first year of operation.

Voltage VAR optimization real time closed loop deployment - BC Hydro challenges and opportunities

Modeling of loads in energy management system (EMS) impacts significantly the robustness and quality of state estimator solution. Loads are traditionally used as pseudo measurements to fill in for unavailable real-time analog telemetry in order to provide required observability for state estimator to solve. The quality of load model also directly impacts the quality of state estimator and power flow solution. There are several important factors to consider when modeling for real-time applications in EMS. Those include (i) the granularity of load model i.e. whether loads are lumped for the entre station bus or each individual feeder in a substation is represented as a separate load, (ii) load voltage sensitivity which describes the variations of real and reactive loads with changes of bus voltage, (iii) load frequency sensitivity which emulates impacts of frequency deviations on loads and (iv) load accuracy model that assigns accuracy class to loads to be used by state estimator. In addition, the aspects of load model such as load allocation in real-time as well as modeling of loads in the external system also need to be addressed. The objective of this paper is to discuss the load model that BC Hydro has implemented in the network model in EMS to support the state estimator and other EMS advanced applications in real-time.

BC Hydro approach to load modeling in state estimation

A method of state estimation is provided, including: (a) acquiring a plurality of positive sequence voltage and current phasor measurements; (b) designating a reference positive sequence voltage phasor measurement from the acquired phasor measurements; (c) correcting the acquired phasor measurements to account for the reference phasor measurement; (d) calculating complex power having a real component and an imaginary component, using the corrected positive sequence voltage and current phasor measurement; (e) using the real component of said complex power as a calculated mega-watt and the imaginary component of the complex power as a calculated mega-volt-ampere; and (f) using the mega-watt and mega volt-ampere calculations in a state estimation algorithm.

Djordje Atanackovic

Papers

Distribution System State Estimation Based on Nonsynchronized Smart Meters

Deployment of real-time state estimator and load flow in BC Hydro DMS - challenges and opportunities

Voltage VAR optimization real time closed loop deployment - BC Hydro challenges and opportunities

BC Hydro approach to load modeling in state estimation

Method and system for using phasor measurements in state estimation of power systems