Observability can be defined as temporal, geospatial, and topological awareness of all grid variables and assets. A more modern times related definition of observability is the ability for any combination of system state and inputs to determine the system state in a finite time using only measurement of system outputs. (DOE: “Sensor Network Issues for Advanced Power Grids” report)
It also can be seen as a set of qualities related to operational visibility of the grid and integrated DER, especially in distribution grids. In a larger sense, observability may be extended to cover electrical, thermal, stress, risk, financial, utilization, and security states.
The electric power distribution grid of 21st century needs to be an observable grid, and the level of awareness should be high enough to cover the requirements of grid stability and reliability in presence of intermittent generations and loads.
Observability may be extended to cover electrical, thermal, stress, risk, financial, utilization, and security states.
Sufficient sensing and data collection can help to assemble an adequate view of system behavior for control and grid management purposes, thus providing snapshots of grid state. The data can also be utilized to validate planning models. Measurement refers to the ability to record and monitor grid parameters such as three-phase voltage, current, phase angle, and power factor as well as DER output and performance. (DOE-OE: “Modern Distribution Grid” report)
Observability is a critical function to grid capabilities like situational awareness, dynamic stability, integrated control, reliability, contingency analysis, self-healing, resiliency and DER management.
Observability for distribution grid is fundamentally a more difficult issue than for transmission grid. Complicating factors include feeder branches and laterals, unbalanced circuits, poorly documented circuits, large numbers of attached loads and devices and, in the case of feeders with inter-ties, time-varying circuit topology.
To attain observability, the first step is to develop an observability strategy based on measurement types and characteristics, classify data by key characteristics, and determine sensor mix and build sensor location plan. The very next step would be implementation of a set of features and elements in grid management system, centrally or at the edge, that enables observability:
State Estimation: The State Estimation is the standard method for determining a consistent and comprehensive network status. The results are used as the basis for all other Network Application functions. It is the process of determining those parameters that can be used to determine power system conditions. The power system states include:
- Node voltage phasor (voltage magnitude, phase angle),
- Transformer turn ratios (turn ratio magnitude, phase shift angle)
- Complex power flow (active power flow, reactive power flow).
Fault Localization Isolation Service Restoration (FLISR): Automatic sectionalizing and restoration, and automatic circuit reconfiguration. accomplished by coordinating operation of field devices, software, and dedicated communication networks to automatically determine the location of a fault, and rapidly reconfigure the flow of electricity so that some or all of the customers can avoid experiencing outages.
Volt-var Control:
Controlling the voltages in a distribution network is an important task for any network management system working on the distribution level. Volt-var control is a process undertaken to maintain an optimal voltage at all points along a distribution feeder under all loading and DER conditions.
- Improve efficiency by reducing technical losses through voltage optimization
- Reduce electrical demand and/or accomplish energy conservation through voltage reduction
- Promote a “self-healing” grid (Volt-var control plays a role in maintaining voltage after “self-healing” has occurred)
Outage Management System: A system service used by operating entities to better manage their response to power outages, integration of multiple sources of data (smart meters, customer calls, etc.) integration with other utility systems to analyze possible fault locations (Geographical Information Systems (GIS) and connectivity databases for common node analysis) and/or integrate fault location from applications such as FLISR, and integrate with computer aided dispatch systems for remedial action.
Simulation: Simulation tools include analytical and software tools that can model the electric power structure as it is designed and operated. This incorporates the proliferation of DER, deployment of smart grid technologies and evolving business models, and other reasons.
Grid Model : In distribution network, the model is a data set, in spatial context that contains grid asset details and configuration information, customer and DER connectivity details, and other relevant information to reflect an accurate depiction of the current state of the distribution system. This model is often visually represented in a GIS as well as used in power flow studies. Distribution operations employs two versions: as-built and as-operated. As-built reflects the model prior to daily operations while as-operated reflects the actual real time model for daily operations.
Tools that can be widely applied in distributed system integration analysis and in studying the impact of DER on distribution circuits. These tools should be capable of performing the following non-exhaustive list of functions:
- Able to model the subtransmission system;
- Model voltage control equipment;
- Model unbalanced systems;
- Handle load and generation profiles;
- Accommodate accurate flexible DG models;
- Load-flow planning;
- Fault current calculation;
- Distribution state estimator.
Power Quality Measurement and Stabilization: Monitoring may be continuous and handled by distributed intelligent devices in the field reporting unsolicited data only when accepted parameters are violated. Waveform data may be stored locally to allow for data requests and post event analysis. Stabilization of voltage (compensation for spikes, sags, etc.) is the automatic correction of system perturbations (i.e., voltage)
Implementation and Integration with Meter Data Management System: MDM is the process and tools for securely storing, organizing, normalizing data from advanced meters integrating data from other meters, and making the data available for multiple applications including customer billing, analysis for grid control, outage management and others.
As grid observability increases, we have the opportunity to implement increasingly powerful methods for detecting, locating, and characterizing all types of grid faults, foresee grid states, load and generation variations, and even asset health management and avoiding equipment failure.
More insights at: https://www.linkedin.com/company/psi-energy-gridoutlook