U.S. patent application number 15/638086 was filed with the patent office on 2018-05-10 for proactive intelligent load shedding.
The applicant listed for this patent is OPERATION TECHNOLOGY, INC.. Invention is credited to Tanuj Khandelwal, Farrokh Shokooh.
Application Number | 20180131186 15/638086 |
Document ID | / |
Family ID | 49777361 |
Filed Date | 2018-05-10 |
United States Patent
Application |
20180131186 |
Kind Code |
A1 |
Shokooh; Farrokh ; et
al. |
May 10, 2018 |
PROACTIVE INTELLIGENT LOAD SHEDDING
Abstract
A power control system utilizing real-time power system
operating data to effectuate predictive load shedding so as to
accurately predict the need for and the optimal type of responsive
action to a contingency--before the contingency actually
occurs.
Inventors: |
Shokooh; Farrokh; (Laguna
Beach, CA) ; Khandelwal; Tanuj; (Riverside,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
OPERATION TECHNOLOGY, INC. |
Irvine |
CA |
US |
|
|
Family ID: |
49777361 |
Appl. No.: |
15/638086 |
Filed: |
June 29, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13933014 |
Jul 1, 2013 |
9705329 |
|
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15638086 |
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61666716 |
Jun 29, 2012 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H02J 13/00004 20200101;
H02J 2203/20 20200101; H02J 2310/12 20200101; Y04S 20/222 20130101;
H02J 13/00009 20200101; H02J 13/0006 20130101; Y10T 307/25
20150401; H02J 3/14 20130101; Y02B 70/3225 20130101 |
International
Class: |
H02J 3/14 20060101
H02J003/14 |
Claims
1. A power control system comprising: an power system having one or
more subsystems and electrically connected to one or more loads; a
load shedding system operable to receive data regarding the power
system and to selectively disconnect one or more loads and/or
subsystems from the power system, the load shedding system
comprising a controller operable to: receive data regarding the
power system, loads and electrical connections therebetween,
identify whether a contingency has occurred, and if so, it's type
and location, calculate an optimal response to the contingency
based on the received data, selectively disconnecting one or more
loads and/or subsystems according to the optimal response such that
no disconnection occurs where the controller identifies the
contingency as occurring in subsystem that is already disconnected
from the power system.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 13/933,014, filed Jul. 1, 2013, which is based
on U.S. Provisional Application No. 61/666,716, filed on Jun. 29,
2012, the contents and disclosure of which are herein incorporated
by reference.
BACKGROUND OF THE INVENTION
[0002] In electrical power systems, power generation and load
demand must be balanced at all times. In the event load demand is
higher than the current power generation, load shedding must be
initiated in order to correct the imbalance and maintain system
stability and operability. This balance is reflected in the
frequency response of the power system, i.e. how the frequency of
the generated power aligns with a target frequency reflecting a
stable system, e.g. 60 Hz. For example, when load demand becomes
greater than power generation, the frequency of the generated power
will drop, unless and until either the power generation increase
accordingly, or the excess load is removed.
[0003] Load shedding is the removal of excess load from a power
system to keep the system stable and operational. Load shedding is
typically in response to one or more system disturbances, also
known as "triggers" or "contingencies," that result in a power
generation deficiency condition, i.e. a reduction in power
generation. Common contingencies that can cause a deficiency
condition include faults, loss of generation, switching errors,
lightning strikes, and other similar events.
[0004] Sudden and large changes in power generation capacity, e.g.
through the loss of a generator or main inter-tie, may impact the
dynamic response of the prime mover, which can produce severe power
generation and load imbalances, resulting in rapid frequency
decline. For some disturbances, notably those resulting in a loss
of generation or a system islanding effect, the cascading effects
of these sudden and large power generation changes may be of
primary concern. Indeed, if load shedding is not set and timed
correctly these cascading effects may cause more of a risk to
overall system stability than the initial event itself.
[0005] For example, a short circuit at a power station busbar may
initially result in an acceleration of the generator prime movers
(e.g. turbines) due to the decreased load sensed by the power
system because of the fault, i.e. frequency rises above the target.
When this occurs, a speed regulator may act to decelerate the prime
movers in order to correct the imbalance, i.e. lower the frequency
to the target. However, once the fault clears, the prime movers
face are faced with the impact of the actually still connected
load, i.e. frequency is actually below target, except now under
difficult reacceleration conditions.
[0006] This drop in system frequency may instigate a rapid fall of
power output to the auxiliary loads, causing further reductions of
the energy input to the generator prime movers. This sequence of
events may further deteriorate the system frequency, endangering
the entire power system. To halt the drop in system frequency, it
is necessary to intentionally disconnect a portion of the load
equal to or greater than the generation deficiency in order to
achieve balanced power economics while maintaining system
stability. Automated load shedding systems are therefore necessary
for industrial power systems since sudden disturbances can plunge a
power system into a hazardous state much faster than an operator
can react.
[0007] Conventional automated load shedding schemes utilize fixed
frequency settings with fixed frequency relays. For example, an
under-frequency rely load shedding scheme utilizes fixed load
reduction at fixed system frequency levels. If the power system
frequency falls below a frequency set point for a pre-specified
period of time, the frequency relay trips one or more load
breakers, i.e. sheds a pre-determined load or loads. This cycle is
repeated until the power system frequency is recovered, e.g. 10%
load reduction for every 0.5% frequency drop. However, in the time
it takes for the frequency relay to trip the load breakers to shed
the predetermined load(s) for that frequency level, the frequency
may have degenerated past the level where such a response is
sufficient, instigating successive load shedding operations in the
face of a continuingly degenerative frequency level, and risking
total system failure.
[0008] Unfortunately, the amount of load shed under such schemes is
typically quite conservative, often resulting in excessive or
insufficient load shedding. This is because, typically, there is a
complete lack of knowledge about the actual system operating
conditions, as well as the types of disturbances and their
locations within the system. Indeed, these load shedding schemes
rely on pre-programmed load priority tables that are developed in
advance of the power system's actual operation (i.e. during a
"study phase") and that are static (i.e. time invariant). The
result is that the amount of load shed is not tailored to address
actual power system conditions as they occur during operation.
[0009] Indeed, these conventional load shedding schemes have the
inherent limitation that the contingencies, i.e. events resulting
in power generation deficiency, on which these load priority tables
are based are pre-programmed simulations which, at best, are simply
educated guesses about what actual contingencies the power system
may encounter and what the appropriate response would be. Hence,
the associated load priority tables are only as good as the number
of contingencies envisioned by the engineer who sets up the
simulations. These tables will necessarily not include all possible
contingencies, leaving the system vulnerable to contingencies that
may cause system instability and/or failure. Moreover, these
contingencies (and associated responses) while valid for the set of
operating conditions for which they were created, are often
inapplicable to the changing operating conditions of actual system
operation. In short, the actual operating conditions of the power
system are generally not those of the simulation.
[0010] It is therefore desirable to provide a proactive load
shedding system that can predict the need for and the optimal type
of responsive load shedding action to a contingency based on the
actual operating conditions of a power system.
BRIEF SUMMARY OF THE INVENTION
[0011] Briefly, and in general terms, the present invention
provides for a power control system utilizing real-time power
system operating data to effectuate predictive load shedding so as
to accurately predict the need for and the optimal type of
responsive action to a contingency--before the contingency actually
occurs.
[0012] These and other aspects and advantages of the invention will
be apparent from the following detailed description and the
accompanying drawing, which illustrates by way of example the
features of the invention.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)
[0013] Illustrated in the accompanying drawing(s) is at least one
of the best mode embodiments of the present invention. It should be
understood that what is illustrated is set forth only for the
purposes of example and should not be taken as a limitation on the
scope of the invention described herein. In such drawing(s):
[0014] FIG. 1 illustrates a power control system according to at
least one embodiment of the present invention;
[0015] FIG. 2 illustrates a proactive load shedding system
according to at least one embodiment of the present invention;
[0016] FIG. 3 illustrates a power control system according to at
least one embodiment of the present invention;
[0017] FIG. 4 illustrates a proactive load shedding system
according to at least one embodiment of the present invention;
[0018] FIG. 5 illustrates a proactive load shedding system
according to at least one embodiment of the present invention;
[0019] FIG. 6 illustrates a proactive load shedding method
according to at least one embodiment of the present invention;
[0020] FIG. 7 illustrates a proactive load shedding method
according to at least one embodiment of the present invention;
and
[0021] FIG. 8 illustrates a power control system according to at
least one embodiment of the present invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0022] The above described drawing figures illustrate the described
invention in at least one of its preferred, best mode embodiment,
which is further defined in detail in the following description.
Those having ordinary skill in the art may be able to make
alterations and modifications to what is described herein without
departing from its spirit and scope. While this invention is
susceptible of embodiment in many different forms, there is shown
in the drawings and will herein be described in detail a preferred
embodiment of the invention with the understanding that the present
disclosure is to be considered as an exemplification of the
principles of the invention and is not intended to limit the broad
aspect of the invention to the embodiments illustrated and/or
described.
[0023] FIG. 1 illustrates a power control system according to at
least one embodiment of the present invention.
[0024] A power system 1000 comprises at least one power source 200
electrically coupled to at one or more loads 400. The power sources
may be, for example, an on-site power generator but are not
necessary limited thereto. The loads may be, for example, anything
that requires electrical power to operate. The power system may
also comprise one or more power control mechanisms 600 such as, for
example, circuit breakers or relays, operable to selectively
connect/disconnect one or more loads from one or more power sources
in response to a power system control signal from a controller 800
that is communicatively coupled to the power control mechanisms.
The power system may also comprise one or more substantially
analogous power sub-systems.
[0025] The power system is electrically and communicatively coupled
to a proactive load shedding system 2000. The proactive load
shedding system comprises a proactive load shedding system server
which may distributed across or more physical servers, each having
processor, memory, an operating system, and input/output interface,
and a network interface all known in the art.
[0026] In accordance with at least one embodiment, a power system
model is generated from real-time power system operating data.
Predictive contingencies are then run according to the model.
Appropriate responses are generated and stored. When the
contingency occurs, the appropriate response is retrieved and
executed--shedding the appropriate loads (i.e. signal sent to
controller to open switch).
[0027] The predictive contingencies may be according to known user
inputted predictive contingencies. Appropriate responses are
generated and stored. When the actual contingency occurs, the
appropriate response is retrieved and executed--shedding the
appropriate loads (i.e. signal sent to controller to open switch).
When power system operating data changes, the process repeats so as
to update/optimize the responses to the new system data.
[0028] The predictive contingencies may be system-generated
predictive contingencies. The system may take the model and run a
"what if" for every contingency. These contingencies may be ranked
according to the level of threat they would have to system
stability. They would then be ranked according to how fast the
system would fail in the event of the contingency (i.e. how much
time would the system have to initiate responsive action before
failure became imminent). Then appropriate response are generated
and stored according to the ranking. When the actual contingency
occurs, the appropriate response is retrieved and
executed--shedding the appropriate loads (i.e. signal sent to
controller to open switch). When power system operating data
changes, the process repeats so as to update/optimize the responses
to the new system data.
[0029] When power system operating data changes, the process
repeats so as to update/optimize the responses to the new system
data. For every defined trigger, a response is calculated, updated
according to the real-time system operating data, and transmitted
to the controller to be executed in the event of the associated
contingency occurs. In this manner, the power control system
adjusts to the dynamic effects of contingencies according to
changing actual power system operating parameters.
[0030] FIG. 2 illustrates an exemplary proactive load shedding
system according to at least one embodiment of the present
invention.
Real-Time Power System Topology
[0031] As shown, for example, in FIG. 2, an electrical database
2020 retrievably stores data regarding the electrical connectivity
between the components of the power system (e.g. the power sources
and the loads), the data comprising one or more electrical models
of the power system. For example, as shown in FIG. 8, three loads
L1, L2 and L3 may be electrically coupled to two power sources P1
and P2. The electrical database would store data representing each
of these connections, effectively mapping out and/or modeling all
the electrical connections of the power system. In at least one
embodiment, the electrical database retrievably stores data
regarding the electrical connectivity between components of one or
more power sub-systems.
[0032] As shown, for example, in FIG. 4, computer models of
electrical power systems are developed and maintained in a common
database 2022. Users (e.g. engineers) develop these operating
virtual models of electrical power systems via graphical user
interface editors 2024 and engineering libraries of common
components 2026. Separate data editors for Bus, Branch, and Machine
data allow the user to model the system in the common database. The
libraries, which may be user-edited libraries, provide typical data
that can be substituted into the database upon request. When
predictive studies are performed, as described herein according to
at least one embodiment, the power control system automatically
extracts the necessary power system parameters from the common
database.
[0033] Returning to FIGS. 2 and 4, an electrical power system
topology engine 2040 is communicatively coupled to the electrical
database such that the topology engine can retrieve the electrical
models of the power system stored therein. The topology engine
receives real-time system operating data 2060 and generates a
topology model of the power system based off of the electrical
model and the real-time operating data of the power system as it is
operating. For example, as shown in FIG. 8, power control
mechanisms S1-S2 are shown in an "off" position as they would be if
P1 was undergoing an event that required the shedding of loads L1
and L2.
[0034] According to at least one embodiment, the topology engine
determines the connectivity of the electrical network, taking as
input, a complete model of the network--provided by the electrical
database--consisting of nodes and switching devices. The topology
engine reduces the "node breaker" model to a "bus branch" model,
where the concept of bus defines a maximal sub-network
interconnecting nodes and closed switching devices only. In other
words, the topology model is one that eliminates all switching
devices from the network model by instantiating their "open" or
"closed" status. In this manner, subsystems are identified using
real-time system topology and power system electrical database such
that load shedding calculations are handled independently in each
isolated section. By operating according to sub-systems, the power
control system according to at least one embodiment, will be better
able to identify electrical events or triggers and compute the
required load to be shed within each sub-system. The topology
engine is used to determine sub-systems, which are sections of the
system that are electrically isolated from each other.
[0035] Thus, the topology model is a model of the actual operating
conditions of the power system at the time the topology model is
generated, i.e. "snapshot" of the power system. Because it receives
real-time operating data, the electrical power topology engine
keeps track of the status of the power control mechanisms (e.g.
circuit breakers, isolator switches, fuses, transformer tap
positions, etc.). It can therefore generate the topology model for
the entire power system, or for one or more power sub-systems, as
shown, for example, in FIG. 5.
[0036] As shown in, for example, in FIG. 3, the power control
system according to at least one embodiment of the present
invention acquires real-time data of the actual power system and
monitors or calculates the pre-disturbance operating conditions,
such as, for example, total system load demand, total system power
exchange to the grid, generation of each on-site unit, spinning
reserve for each on-site unit, control settings for each running
unit, settings and loading conditions for all major rotating
machines, system configuration and/or topology (e.g. tie-line
numbers, tie-line status and power transferring, bus-tie status and
flow, transformers and feeder status and loading, loading of each
load, etc.). Real-time operating data may be gathered directly, for
example, via sensors such as Intelligent Electronic Devices (LEDs),
Phasor Measurement Units (PMUs) used for Wide Area Measurement
(WAMs), transducers, Dynamic Disturbance Recorders (DDRs).
Real-time operating data may also be gathered indirectly, for
example, via a central data acquisition systems such as Supervisory
Control & Data Acquisition (SCADA) or Distributed Control
Systems (DCS). Real-time data preferably includes the electrical
operating parameters of the system such as, for example, voltage,
electrical power, reactive power, current, etc. Real-time data may,
for example, indicate whether a contingency has occurred.
[0037] As discussed herein, the electrical power system topology
engine generates topology models for power sub-systems in an
analogous manner. By utilizing topology models for
power-subsystems, load shedding activities may be executed
independently according to each isolated power sub-system.
Accordingly, the proactive load shedding system according to at
least one embodiment identifies contingencies and computes the
required load to be shed on a sub-system by sub-system basis. A
result is that an event in one sub-system can be isolated to that
sub-system and any potential system-wide degenerative effects may
be mitigated.
Steady State System Assessment
[0038] As discussed herein, the proactive load shedding system
according to at least one embodiment of the present invention
utilizes both a steady state and dynamic assessment to proactively
identify and evaluate contingencies that may result in load
shedding, and to determine the optimal amount of load to be shed in
response to each identified contingency.
[0039] The steady state assessment will now be discussed with
reference to FIG. 2.
[0040] A predictive simulation engine 2220 is communicatively
coupled to the topology engine and determines the likely effect of
actual contingencies based on one or more predictive contingencies.
The predictive contingencies are preferably pre-programmed into the
system and are events that the engineer believes have a high
likelihood of happening, and if they do, a high potential for
causing system failure. For example, the predictive simulator may
determine the effect of possible outages, such as loss of one or
more branches (e.g. transmission lines, transformers, etc.) and/or
generating units, to the power system.
[0041] According to at least one embodiment the predictive
simulation engine utilizes the topology model to run the analysis.
In this manner, the predictive simulation engine determines the
effect of contingencies to the power system under the operating
conditions as defined by the topology model. Accordingly, the power
control system according to at least one embodiment of the present
invention is able to apply engineer-determined contingencies to the
actual operating conditions of the power system. Such analysis may
be performed online or off-line.
[0042] According to at least one embodiment, the predictive
simulation engine determines the ability of the power system to
remain stable in the presence of slowly varying changes in the
total demand. It accomplishes this by determining the maximum
loadability of the power system, i.e. how much additional load the
power system can carry without power system collapse, if load (and
accordingly, generation and imports) is increased gradually. This
determination is preferably made according to current power system
operating conditions, i.e. according to the topology model.
[0043] The results of the analysis are utilized by the power
control system to generate appropriate responsive actions, such as,
for example, shedding one or more loads. The responsive action is
such that execution of the response by the system would restore
system stability.
[0044] A response generation engine 2600 is communicatively coupled
to the predictive simulation engine and predictive response
database. The response generation engine receives the predictive
scenarios from the predictive simulation engine and generates
predictive responses based thereon. The predictive responses may be
software instructions that when executed cause the controller to
selectively connect/disconnect one or more loads from one or more
power sources, i.e. to shed a load. Preferably, the predictive
response comprises an optimal load shedding operation. Generally,
this process is completed offline, however it may also be completed
online (i.e. during actual system operation).
[0045] A predictive response database 2240 is communicatively
coupled to the predictive simulation engine and retrievably stores
the responsive action associated with a given predictive
contingency. In other words, the predictive response database is a
knowledge base of appropriate system responses for certain system
conditions and contingencies under those conditions. For example,
the predictive response database will store instructions to shed a
certain load combination according to a certain contingency that
occurs while the system is in a certain operating state. In at
least one embodiment, the stored responsive actions may correspond
to predictive contingencies that are pre-programmed into the
system. In at least one embodiment, the stored responsive actions
may correspond to contingencies that are dynamically assessed, as
discussed herein. Generally, this process is completed offline,
however it may also be completed online (i.e. during actual system
operation).
[0046] The system responses are retrievably stored in a memory of
the controller. When an actual contingency is detected, the
controller checks the memory for a corresponding system response to
see how to deal with the actual contingency. If there is a match,
it executes. In this manner, there is an automatic response to a
detected contingency.
[0047] Exemplary static assessment systems are described, for
example, in U.S. Provisional Application No. 61/666,716, filed on
Jun. 29, 2012, the contents and disclosure of which are herein
incorporated by reference.
Dynamic System Assessment
[0048] As discussed herein, the proactive load shedding system
according to at least one embodiment of the present invention
utilizes both a steady state and dynamic assessment to proactively
identify and evaluate contingencies that may result in load
shedding, and to determine the optimal amount of load to be shed in
response to each identified contingency. The dynamic assessment
will now be discussed with reference to FIG. 2.
[0049] A contingency & screening analysis ("CSA") engine 2420
is communicatively coupled to the topology engine and is operable
to identify and rank the most severe disturbances (i.e.
contingencies) that can cause the power system to become unstable.
According to at least one embodiment, the CSA engine receives the
topology model and identifies the full set of possible predictive
contingencies for the current set of system operating parameters.
The CSAengine may further identify those predictive contingencies
whose effect on power system stability exceeds a user-defined
threshold. In other words, the CSAengine identifies predictive
contingencies that, if they were to occur, would constitute
credible threats to the stability of the system. The CSA engine may
also ranks those predictive contingencies that are credible threats
according to their threat level.
[0050] In at least one embodiment, the CSAengine applies a batch
routine to the topology model in order to identify and rank
predictive contingencies. FIG. 6 illustrates an exemplary batch
routine according to at least one embodiment of the present
invention.
[0051] Step 3010: The CSA engine checks whether the predictive
contingency is part of an outage list. The outage list is a list of
pre-identified contingencies that the contingency analysis engine
is going to analyze. It defines the universe of outages and can
range from all possible contingencies, to a select number of
contingencies effecting select portions of the power system. If the
predictive contingency is part of the outage list, the process
continues with Step 3020. If the predictive contingency is not part
of the outage list, i.e. it is not one to be checked (e.g. because
it is already known that it will not have a significant effect),
the process continues with Step 3030.
[0052] Step 3020: The CSA engine ranks the predictive contingency
according to its effect on power system stability. In at least one
embodiment, this is accomplished by the contingency analysis engine
running a preliminary simulation based on the topology model, in
which the predictive contingency is applied and the simulated
effects on the power system are determined. In other words, the
contingency analysis asks the question: if the contingency occurs,
how many violations (i.e. instances of power system instabilities)
are triggered? In at least one embodiment, the predictive
simulation is an interpolation of the effects of the predictive
contingency based on the effects of similar predictive
contingencies whose effects are known. The predictive contingency
is ranked according to the number of violations the predictive
contingency triggers. The ranking process continues for every
predictive contingency on the outage list until the outage list is
fully ranked. The process then continues with Step 3030.
[0053] Step 3030: The CSA engine copies at least a portion of the
outage list to an evaluation list. The predictive contingencies
that are copied to the evaluation list are preferably determined by
the number of associated violations, i.e. the seriousness of the
contingency. For example, the evaluation list may be a list of the
"top-10" contingencies, or it may be a list of those contingencies
that meet a target threshold for threat level. The process then
continues with Step 3040.
[0054] Step 3040: The CSA engine communicates the predictive
contingencies to the security assessment engine on a by-rank
priority. The security assessment engine then conducts a full
analysis of the predictive contingencies according to the system
and processes described herein.
[0055] Step 3050: As an additional step, the CSA engine may also
generate a report according to the evaluation list that may be
uploaded to a graphical user interface (or a database) to be
reviewed by a user in connection with the power system.
[0056] In this manner, the contingency analysis engine
preliminarily determines the systematic effect of all possible
contingencies on the power system, screens out contingencies whose
systematic effects do not meet a user-defined threshold threat
level (i.e. are not credible threats), and ranks those
contingencies that do meet the threshold according to the severity
of the threat. For example, a contingency whose occurrence would
cause a total system failure would have a high ranking.
[0057] A security assessment engine 2440 is communicatively coupled
to the contingency analysis engine and the response generation
engine. The security assessment engine runs a full security
analysis of the predictive contingencies supplied by the CSA. In
other words, for each predictive contingency, the security
assessment engine determines the complete behavior of the power
system and whether that behavior violates any limits such that
system stability is at risk. This is accomplished by running an
in-depth simulation in which the predictive contingency is applied
to the topology model and the simulated effects on the power system
are determined.
[0058] Determining the effects of the predictive contingency is
preferably accomplished by running one or more stability
calculations, including: transient stability (i.e. time domain)
calculations, voltage stability (i.e. model) calculations, small
signal stability (i.e. model) calculations, and electromagnetic
transient calculations. The particulars of these calculations as
applied to various data sets are generally known to those of
ordinary skill in the art.
[0059] Determining whether the effects of the predictive
contingency include security violations includes comparing those
effects to security limits, assessing whether the effects exceed
those limits, and determining whether the effects are dampening
(i.e. returning to normal on their own). Such determination may
include, for example, determining whether there is a rotator angle
stability violation, a voltage and power limit violation, an
available transfer limit violation, and/or a thermal limit
violation.
[0060] According to at least one embodiment the predictive
simulation engine utilizes the topology model to run the security
analysis. In this manner, the predictive simulation engine
determines the effect of contingencies to the power system under
the operating conditions as defined by the topology model.
[0061] According to at least one embodiment, the predictive
simulation engine determines the ability of the power system to
remain stable in the presence of slowly varying changes in the
total demand. It accomplishes this by determining the maximum
loadability of the power system, i.e. how much additional load the
power system can carry without power system collapse, if load (and
accordingly, generation and imports) is increased gradually. This
determination is preferably made according to current power system
operating conditions, i.e. according to the topology model.
[0062] In at least one embodiment, the security assessment engine
receives the ranked predictive contingencies from the contingency
analysis and identifies the immediacy of the associated threat.
Preferably, this is accomplished on highest-rank-first priority. In
other words, the security assessment engine analyzes the most
severe contingencies to determine, if the contingency happened
under the present system operating parameters, how long before the
threat to system stability would be realized. For example, for a
contingency whose occurrence would cause a total power system
failure, the model analysis engine determines how long from the
occurrence of the contingency until the power system failed. In
this manner, the system according to at least one embodiment of the
present invention further prioritizes which predictive
contingencies to develop predictive responses to.
[0063] The predictive response generation engine then determines
the appropriate remedial action according to the predictive
contingency, the topology model, the predictive simulation, and/or
the predictive response database, as discussed herein. In at least
one embodiment, the predictive response engine compares the
topology model and real-time data with similar predictive
contingencies for which predictive remedial actions are known, and
interpolates a predictive remedial action based thereon. In at
least one embodiment, the predictive response generation engine
conducts a trial and error calculation, in which a predictive
remedial action is introduced into the simulation and the
simulation is checked to determine whether the remedial action
returns the simulated power system to stable operating conditions.
If not, another predictive remedial action is tried until one is
found that accomplishes that goal. The predictive responses are
downloaded to respective power system controllers and stored so as
to be automatically retrievable in the event the actual contingency
occurs.
[0064] It is important to note that this analysis is dynamic, based
on the system operating data in real-time. The effect is as the
system changes, the contingencies passed on by the contingency
analysis/modal analysis will be analyzed (and reactions generated)
on a priority basis according to the most critical contingencies of
the current system operating parameters. This means, the system is
not likely to do a full analysis of any given set of operating
parameters at one time. Instead, the system continues to analyze
the most important contingencies for the set of system parameters
the system is currently operating under. As those system parameters
oscillate, lower ranked contingencies will be filled in, leading to
a full and complete predictive response database.
[0065] Once that occurs, the contingency analysis engine will
retrieve the current real-time data and will re-load the
controllers with all the known responses to every possible
contingency--on a priority system according to critical-ness of the
predictive contingency. In this manner, the system can accurately
predict responses for contingencies according to the real-time
system data without the lag time present in prior art systems.
[0066] Importantly, this analysis occurs according to the power
subsystems that are identified using the real-time system topology.
In this manner, load shedding calculations are handled
independently for each isolated section. By operating according to
sub-systems, the power control system according to at least one
embodiment, will be better able to identify electrical events or
triggers and compute the required load to be shed within each
sub-system. Accordingly, the predictive contingencies that, for
example, are limited to isolated subsystems and therefore would
have a limited effect on the power system as a whole, can be
identified and the calculation of an appropriate response thereto
can be postponed in favor of predictive contingencies whose effect
is system wide. In other words, according to at least one
embodiment, contingency prioritization is enabled at least in part
because of the subsystem by subsystem analysis. This is
particularly important during dynamic system assessment, because of
the sheer volume of calculations required to be undertaken to
determine every possible contingency in real-time. Under these
circumstances, prioritization is highly beneficial.
[0067] The predictive response engine continually evaluates the
generated remedial actions associated with the various predictive
contingencies. For each contingency, it compares the event and
corresponding system behavior with the predictive response
database. But utilizing weighing factors, the predictive response
engine is able to identify the appropriate remedial action required
to return the system to a stable condition. These calculations are
preferably performed on a continuous basis, prior to any
disturbance, event or contingency occurring.
[0068] A proactive load shedding method will now be discussed with
reference to FIG. 7.
[0069] Step 10: A topology model is generated based on real-time
power system operating data and an electrical model, as discussed
herein. The electrical model identifies all the electrical
connections of the power system. The real-time operating data is
gathered via sensors. The topology model is a model of the actual
operating conditions of the power system at the time the topology
model is generated, i.e. "snapshot" of the power system. Because it
receives real-time operating data, the electrical power topology
engine keeps track of the status of the power control mechanisms
and is in effect, a reduction of the "node breaker" model to a "bus
branch" model.
[0070] Step 20: The effects of preprogrammed predictive
contingencies to the power system under the operating conditions as
defined by the topology model are determined, as discussed herein.
The pre-programmed predictive contingencies are events that the
engineer believes have a high likelihood of happening, and if they
do, a high potential for causing system failure.
[0071] Step 40: The effects of real-time predictive contingencies
to the power system under the operating conditions as defined by
the topology model are determined and ranked based on the severity
of the effect and the imminence of the effect, as discussed herein.
The full spectrum of predictive contingencies that could occur to
the power system under the operating conditions as reflected in the
topology model are identified. Those predictive contingencies are
ranked according to the severity of their effect on the power
system and the imminence of the effect.
[0072] Step 50: Appropriate responsive actions to the predictive
contingencies (both preprogrammed and real-time) are determined and
retrievably stored, as discussed herein. The appropriate responsive
actions to each real-time predictive contingency are determined in
priority order of the ranking.
[0073] Step 60: If an actual contingency is detected that aligns
with a predictive contingency for which an appropriate responsive
action has been determined, the responsive action is executed in
response to the actual contingency. The predictive responses are
downloaded to respective power system controllers and stored so as
to be automatically retrievable in the event the actual contingency
occurs that matches the predictive contingency. As the system
operating conditions change, the predictive contingencies analyzed
(and reactions generated) will likewise change, continually
analyzing and retrievably storing the most important contingencies
for the current system operating conditions. The set of responses
(e.g. priority tables) to predictive contingencies associated with
the current system operating conditions are continually loaded to
the controllers to be quickly retrieved in the event of an actual
contingency.
[0074] It should be noted, that while the embodiments of the
present invention are herein described primarily with respect to
load shedding in response to transient stability analysis, the
present invention has equal applicability to general security
assessment, as would be understood by one of ordinary skill in the
art.
[0075] Security assessment includes various calculations, such as
transient stability, electromagnetic transient stability, voltage
stability and small signal stability. The power control system
identifies cases that can potentially lead to system violations
(i.e. power system instability) and performs detailed dynamic
calculations from a system stability perspective--both short term
and long term. These cases are run either using offline information
(e.g. planning models) and/or online information (i.e. real-time
topology models). The real-time information may be based on the
power system operating conditions at the moment prior to any
disturbance and may include, for example, information such as,
system load, location, wind speed, solar irradiance, etc.
[0076] The results of the security assessment may then be compared
against system security violations, such as, undervoltage,
overvoltage, power transfer limits, thermal loading, etc., to
filter contingencies or triggers that require corrective action
from a dynamic performance point of view. During an initial
training of the power control system, remedial actions are
evaluated by the engineer that can include, for example, real power
adjustment by means of load shedding, reactive power adjustment by
means of capacitor banks, system islanding by intentionally
isolating healthy sub-systems from unstable behavior, changing
protection schemes or settings to make the system more or less
sensitive to disturbances.
[0077] The present invention may be provided as a computer program
product which may include a machine-readable medium having stored
thereon instructions which may be used to program a computer (or
other electronic devices) to perform a process according to the
present invention. Moreover, the present invention may also be
downloaded as a computer program product, wherein the program may
be transferred from a remote computer to a requesting computer by
way of data signals embodied in a carrier wave or other propagation
medium via a communication link.
[0078] It should be noted that while the embodiments described
herein may be performed under the control of a programmed
processor, in alternative embodiments, the embodiments (and any
steps thereof) may be fully or partially implemented by any
programmable or hard coded logic. Additionally, the present
invention may be performed by any combination of programmed general
purpose computer components or custom hardware components.
Therefore, nothing disclosed herein should be construed as limiting
the present invention to a particular combination of hardware
components.
[0079] The present invention includes various steps. The steps of
the present invention may be performed by hardware components or
may be embodied in machine-executable instructions, which may be
used to cause a general-purpose or special-purpose processor or
logic circuits programmed with the instructions to perform the
steps. Alternatively, the steps may be performed by a combination
of hardware and software.
[0080] The enablements described in detail above are considered
novel over the prior art of record and are considered critical to
the operation of at least one aspect of the invention and to the
achievement of the above described objectives. The words used in
this specification to describe the instant embodiments are to be
understood not only in the sense of their commonly defined
meanings, but to include by special definition in this
specification: structure, material or acts beyond the scope of the
commonly defined meanings. Thus if an element can be understood in
the context of this specification as including more than one
meaning, then its use must be understood as being generic to all
possible meanings supported by the specification and by the word or
words describing the element.
[0081] The definitions of the words or drawing elements described
herein are meant to include not only the combination of elements
which are literally set forth, but all equivalent structure,
material or acts for performing substantially the same function in
substantially the same way to obtain substantially the same result.
In this sense it is therefore contemplated that an equivalent
substitution of two or more elements may be made for any one of the
elements described and its various embodiments or that a single
element may be substituted for two or more elements in a claim.
[0082] Changes from the claimed subject matter as viewed by a
person with ordinary skill in the art, now known or later devised,
are expressly contemplated as being equivalents within the scope
intended and its various embodiments. Therefore, obvious
substitutions now or later known to one with ordinary skill in the
art are defined to be within the scope of the defined elements.
This disclosure is thus meant to be understood to include what is
specifically illustrated and described above, what is conceptually
equivalent, what can be obviously substituted, and also what
incorporates the essential ideas.
[0083] The scope of this description is to be interpreted only in
conjunction with the appended claims and it is made clear, here,
that the named inventor believes that the claimed subject matter is
what is intended to be patented.
* * * * *