Abstract
This chapter aims at familiarizing the reader with the state-of-the-art in real-time and study-mode network analysis as currently implemented in SCADA/EMS installations worldwide. The basic components of this paradigm were born in the aftermath of the Northeast blackout of 1965. At that time, the control centers had already replaced the analog computers of earlier generation with the emergent digital machines and key applications, such as economic dispatch, were quickly being adopted. However, due to its compute-intensive nature, security assessment was still performed off-line both for short-term operations scheduling and in long-range system planning. The famous, or, rather, infamous system-wide failure that shut down the lights on the US East Coast for more than 24 h in some places changed everything. State estimation was born, load-flow and contingency evaluation started to be processed online with data collected in real-time, and the rest is history. Today, the ubiquitous real-time and study-mode network analysis functionality is quite sophisticated and offers superb integration opportunities both for advanced applications, such as power system stability assessment, and for quickly expanding new technologies, such as WAMS.
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Notes
- 1.
At the outset, let us note that the techniques addressed in this chapter aim at the static, or steady-state, analysis of power system conditions that are reached long after the sub-transient and transient phenomena have subsided. In this context: “long after” is actually never longer than a couple of seconds; the after-contingency steady-states are determined with load-flow computations; and dynamics, system oscillations, relay settings, and other stability aspects are not taken into account. Originally, this approach was called “static security assessment” as opposed to “dynamic security assessment,” which entailed primarily transient stability calculations. Since a thorough assessment of the power system operating reliability would not be complete unless dynamics would also be considered, a few stability concepts are briefly introduced in Sect. 1.2.3 and Sect. 1.4.2—and then, the main voltage and transient stability tools will be addressed extensively throughout the remaining chapters of this book
- 2.
HIPO (Hierarchy + Input-Process-Output) is a tool developed by IBM in the 1970s [5], which facilitates the planning, documentation, and specification of computer programs and complex systems that encompass both hardware and software
- 3.
At that time: “system security” referred to the power system ability to withstand the impact of generation and/or transmission outages; “generation reliability,” or just “reliability,” designated the capability of the utility’s generating units to cover the load duration curve within a specified Loss of Load Probability (LOLP); and “transmission reliability” belonged in long-range transmission studies and consisted of evaluating line and transformer contingencies in the context of planned network topologies. Nowadays, the term “system security” is normally used as a synonym of “cyber security” whereas the meaning of the early concept of “system security” is conveyed by the term “operating reliability”
- 4.
In the SCADA/EMS context, “online” implies that the calculation results are available to the operator in the SCADA/EMS system itself, as opposed to being available on some other separate system, which would be designated as “off-line.” However, there is no guarantee that the online computational process will be fast enough to produce results that can be labeled “real-time.” A detailed discussion of the “real-time” and “study-mode” paradigms is provided in reference [9]
- 5.
In the old times, power system stability was classified as transient, or dynamic, and steady-state. Today, one of the earlier steady-state stability concepts known as system loadability was relegated to the field of voltage stability whereas the remaining ones are categorized as small signal stability
- 6.
- 7.
- 8.
In the realm of Wide Area Measurement Systems (WAMS), phasor data are collected by PMUs at 2 up to 5 cycle intervals, whereas the status and analog data handled by SCADA systems are gathered at much lower rates. The Sect. 2.4.1 provides a cursory review of using PMU data in SCADA environments
- 9.
The ability to run State Estimation in study-mode may be needed for a variety of reasons, e.g., to assess the system observability when building or upgrading the network analysis database
- 10.
Past system conditions are usually stored in savecases but can also be retrieved from the HIS as snapshots of the real-time database, in which case the capability to run Network Topology and State Estimation in study-mode is required
- 11.
Here is what Dr. Roland Eichler and his colleagues from Siemens say about contingency screening in the Sect. 9.1.1.4 of [4]: “Historically screening was utilized as a means of improving performance for contingency analysis. With modern CPU performance there is minimal time difference between screening and then fully simulating a subset of contingencies versus performing a full simulation without screening. While screening capability is available, there is a limited motivation to perform screening with the associated risk of missing contingency violations as a result of heuristic screening indexes. Full simulation without screening also eliminates maintenance effort spent tuning the screening algorithms. Evaluation of time savings with and without screening should be performed to determine the value of screening and its appropriate use to address certain cases.”
- 12.
The DSA functionality offered by Siemens is known commercially as SIGUARD®
- 13.
The Kuhn-Tucker Theorem, which sits at the foundation of nonlinear programming states that, when formulating a minimization problem, both the objective function and the domain of constraints have to be continuous, convex and twice differentiable. In reality, the domain of constraints in the optimum power flow problem is: non-convex, because of the nonlinearity of the complex voltage variables; and non-continuous, since many potential solution vectors are either unstable or physically unfeasible. This explains why, regardless of the technique deployed to solve the optimum power flow problem, there is no guarantee that a global optimum can be reached, assuming of course that a valid solution could be identified
- 14.
Let us mention en passant the ill-advised, yet relatively widespread, practice of “assessing stability” by running load-flows at successively increased load levels and stopping when the load-flow diverged. While it is true that Newton-Raphson load-flows diverge near instability, they may diverge for many other reasons and the state of maximum power transfer has probably been reached before the load-flow diverged. Sauer and Pai [33] demonstrated conclusively that “for voltage collapse and voltage instability analysis, any conclusions based on the singularity of the load-flow Jacobian would apply only to the voltage behavior near maximum power transfer. Such analysis would not detect any voltage instabilities associated with synchronous machines characteristics and their controls.”
- 15.
Conceptually, the “stability limit” is a function of the system state vector: for each new system state, there is a new stability limit. But not even the stability limit associated with the current or post-contingency operating state is unique, for it depends upon the trajectory followed throughout the computational search. Simply stated, “stability limits” exist; are not fixed; change with the system’s loading, topology, and voltage profile; and depend upon the procedure used to stress the system conditions until instability has been reached. It is precisely this dynamic nature of the “stability limits” that makes it necessary to recompute and track them online. An extensive theoretical discussion of this topic is provided in [10] and related references
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Savulescu, S.C. (2021). Overview of Security Assessment for Grid Operations. In: Nuthalapati, S.(. (eds) Use of Voltage Stability Assessment and Transient Stability Assessment Tools in Grid Operations. Power Electronics and Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-67482-3_1
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