(none)
This disclosure relates to calculating energy passing through a point of an electric power system using energy packets. This disclosure further relates to calculating a value of energy passing through a point of an electric power delivery system using energy packets.
Non-limiting and non-exhaustive embodiments of the disclosure are described, including various embodiments of the disclosure with reference to the figures, in which:
Electric power delivery systems have been designed for the safe and reliable generation, transmission, and distribution of electric power to consuming loads. Electric power markets transact electricity, which is the medium that transfers energy from generators to consumers (via the electric power delivery system). Voltage control is important for maintaining power system stability, minimizing losses, and keeping voltage magnitudes within required ranges. In prior systems, voltage control algorithms use complex power as an input and act to control reactive power in combination with other targets. Complex power is a well-defined concept for the single-frequency sinusoidal steady-state operation of linear electric circuits. However, with the addition of renewables and power-electronically coupled devices, the dynamics of electric power systems are changing. Under these conditions, both time-averaged real power and methods to calculate reactive power have limitations. For example, non-sinusoidal waveforms introduce error into these prior methods. This disclosure defines the concept of an energy packet. Energy packets may be computed and communicated at a fixed rate, with a common time reference. Energy packets may precisely measure energy exchanges, independent of system frequency and phase angles. The application of energy packet measurements is used in embodiments herein to improve power system monitoring and control using voltage control and voltage stability assessment.
Described herein are systems and methods that use energy packets to measure energy through select points on the electric power delivery system for voltage control and stability assessment. For the purposes of this document, such a point could be thought of as an infinitely small slice of a conductor at which voltage at, and current though, that slice can be measured. In some embodiments, a point may be considered to be a location at which a piece of power apparatus (e.g., machine, line, transformer) connects to a bus. The point does not store, produce, nor consume energy. The point may include, but does not require, the presence of current (CT) or voltage (PT) measurement apparatus (e.g. current transducers (CTs) potential transducers (PTs) or the like). If measurement apparatus are collocated with a point, it may be alternatively referred to as a measurement point or point of metering. For practical application, CTs and PTs cannot typically be collocated at a point. As such, the measurement point is typically the location of the CT and the voltage is considered collocated as long as minimal impedance exists between the location of the PT and CT. The disclosures herein divide the energy at each point of measurement according to a direction of energy transfer at the point. Energy packets may be used for voltage control and assessment.
The embodiments of this disclosure will be best understood by reference to the drawings, wherein like parts are designated by like numerals throughout. It will be readily understood that the components of the disclosed embodiments, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the systems and methods of the disclosure is not intended to limit the scope of the disclosure, as claimed, but is merely representative of possible embodiments of the disclosure. In addition, the steps of a method do not necessarily need to be executed in any specific order, or even sequentially, nor need the steps be executed only once, unless otherwise specified.
Several aspects of the embodiments described may be implemented as software modules or components or elements. As used herein, a software module or component may include any type of computer instruction or computer executable code located within a memory device and/or transmitted as electronic signals over a system bus or wired or wireless network. A software module or component may, for instance, comprise one or more physical or logical blocks or computer instructions. Software modules or components may comprise disparate instructions stored in different locations of a memory device, which together implement the described functionality of the module. Indeed, a module or component may comprise a single instruction or many instructions, and may be distributed over several different code segments, among different programs, and across several memory devices. Some embodiments may be practiced in a distributed computing environment.
IEDs 110 and 140 may be any device configured to meter electric power. IED 110 may include a stimulus input 122 configured to receive CT and PT secondaries and condition the signals received therefrom for use by the IED 110. Signal conditioning may include various filters, step-down transformers, analog-to-digital converters (A/D) and the like to produce digitized analog signals. In various embodiments, digitized analog signals may be provided by other devices such as merging units. IED 110 may include a processor 112 for executing instructions. The processor 112 may be implemented as a field-programmable gate array (FPGA), microprocessor, application specific integrated circuit, or the like. Storage media 114 may be a repository for computer instructions executed by the processor 112, settings, samples, and the like. Storage media 114 may include a single or multiple physical storage media, one or more of which may be packaged with the processor 112. A monitored equipment interface 116 may be in communication with monitored equipment of the electric power delivery system such as a circuit breaker for sending signals to the equipment and receiving status signals from the equipment. A communication interface 118 may facilitate communications with various other devices either directly or, as illustrated, via a network 180.
As discussed briefly above, electric power systems may be monitored and controlled to increase efficiency using voltage stability and control. To calculate the flow of energy, IED 110 may also include metering 120, which may be embodied as computer instructions on storage media 114 for execution by processor. Metering 120 may include further signal processing 122 to condition obtained currents and voltages. The IED 110 may include an energy packet calculator 124 to calculate energy packets as discussed below. The IED 110 may further include voltage stability and control 126 that may use energy packets to provide voltage stability and control. In various embodiments, calculation and/or communication of energy packets uses a common time signal that may be obtained by the IED using a common time interface 132 in communication with a common time source 134. Common time signal may be any time signal that from a time source 134 that is common to the devices on the electric power delivery system. Common time source 134 may include a global navigation satellite system (GNSS), WWVB, or other similar common time. Common time signal may be delivered via radio or over other communication media using a common protocol such as IRIG. In various embodiments, the common time signal may be received via the communication interface 132. The common time signal may be a common network time.
Although details of only IED 110 are illustrated, IED 140 may include the same or similar elements to perform power system voltage stability and control. IEDs 110 and 140 may be in communication using direct communication, the network 180, or the like.
As described below, the disclosures hereof are fundamentally different than a time-averaged power Pavg and a reactive power Q combination. In the time-averaged methods, Pavg is defined as the power resulting from the component of current in phase with the voltage and Q is the power resulting from the component of current out of phase with the voltage. By this definition, the mathematics attempts to separate power driving loads and power circulating in a lossless manner among passive reactive power devices. However, physical interpretation of reactive power is challenging in all cases except the pure steady-state sinusoidal case. Energy packets provide a simpler approach. The disclosures herein provide a method that divides the energy passing through each point into portions related to the direction of energy transfer at the point. This simplifies accounting for energy exchanges in today's electric power system characterized by fast dynamics, non-sinusoidal signals, and power-electronically coupled devices.
Equation 1 defines the continuous-time energy packet ε(t) from voltages v(σ) and currents i(σ) over each time interval TEP:
The fixed interval TEP does not need to depend on any estimated power system quantity such as fundamental frequency. In this way, an energy packet may be considered a time-domain concept. Energy packets can be calculated independently for each phase of a poly-phase system or as a consolidated value. Equation 2 defines a consolidated three-phase energy packet ε3(t). A basic three-phase continuous-time energy packet may be defined using Equation 2, where the integration interval is over the same time interval for all three phases:
Equation 3 defines the discrete-time energy packet ε[n] that may be useful for digital signal processing implementations where the value TS is the data sample period, and M represents the number of sampled analog values per energy packet:
It should be noted that energy packet computations may down sample the original signal by a factor of M. Equation 3 shows this by Mn in the summation ranges. The notation for a discrete-time quantity is with hard brackets: v[m]≡v(mTs).
Positive and negative direction energy transfer may be calculated over each integration interval.
The separation into positive and negative regions is given mathematically as follows in Equations 4 and 5, for the discrete-time case:
For illustration, it is convenient to show continuous-time waveforms as in
Energy packets may be used for voltage applications such as local voltage control and wide-area voltage stability assessment. Voltage control and stability using energy packets instead of the traditional methods are an improvement in that the power system frequency is not needed. Further, energy packets are a better representation of power transfer during non-sinusoidal operating conditions than the previous power calculations. Voltage control may be performed using a summation of negative energy packets. The negative energy packet set, E−, for a continuous-time case may be defined using Equations 6A-6D:
where frequency is ω and the phase angle by which current lags voltage is ϕ. Computing the integral an applying trigonometric reductions achieves Equation 7 for the negative energy packet set:
Similarly, the positive energy packet set is given in Equation 8:
The positive and negative energy packet sets may be normalized by Enet as illustrated in Equations 9 and 10:
where Enet is a sum of E+ and E−. A relationship between energy packets and traditional real and reactive power from sinusoidal steady-state conditions may be expressed in Equations 11 and 12:
As outlined above and illustrated in Equations 4-10, energy packets, energy packet sets (positive and negative), and normalized energy packet sets (positive and negative) may be calculated independently of power system frequency.
Traditional calculations of complex power for electric power system monitoring and protection have disadvantages, especially as the power system frequency changes. The real power component of complex power is computed according to Equation 13, where Tsys is the period corresponding to the fundamental frequency:
For steady-state sinusoidal systems, an advantage of Equation 11 is that it integrates perfectly over exactly one period. However, in actual systems, the frequency continuously changes, which is particularly true during disturbances. Accordingly, presented herein are improvements that use energy packets as described above, which are calculated independent of power system frequency. Thus, power system frequency deviations from nominal do not affect the energy or power calculations.
For nonstationary, multifrequency, or distorted conditions, the energy packet definition is unchanged and does not depend on frequency estimates or assumptions. The voltage assessment and control applications of energy packets described herein use sets of energy packets, as defined above. The computation of these sets is by summation of the individual energy packets over a specified period, either of fixed duration or as defined by zero-crossing boundaries (ZB).
E−(k)=Σn∈ZB(k)ε−[n] Eq. 14
It should be noted that E+ may be similarly computed numerically by summing the positive energy packets, ε+[n] over a positive region bounded by zero-crossings. Enet may be computed by summing the positive and negative energy packet sets over a desired period. In various embodiments, Enet may be determined by calculating the sum of positive and negative energy packets over a desired period. Similarly, the positive and/or negative energy packet sets may be determined by summing the respective positive and/or negative energy packets over a period. Other methods of calculating the positive and/or negative energy packet sets and Enet are contemplated and may be used.
Energy packet sets and normalized energy packet sets may be used as described in the embodiments below for local voltage control and for voltage stability assessment.
The field of voltage control spans from capacitor bank controllers to wide-area voltage stabilizing and optimal control systems. This section describes the application of energy packets to local voltage control via a switched capacitor, such as the capacitor bank 150 illustrated in
With reference to
The energy packet controller, in the operating zone between VLD 706 and VHD min 704, keeps Ê− within limits Ê0min and Ê0max. These limits can be calculated in multiple ways. In one embodiment, the limits are converted from the limits of an existing power factor control using Eq. 9. In another embodiment, the limits could be set to the values of Ê− present when the voltage of an uncompensated line is pulled down to a value of 0.9 p.u. by a real-power load (0.95 p.u. for the upper limit). The limits for the operating region shown in
It should be noted that the control algorithm may be modified for systems with load that is predominantly capacitive. Determination of the inductive or capacitive nature of the network may be performed using a system identification technique described at the end of this disclosure.
The energy packet controller was simulated to demonstrate the voltage response to a range of real-power load impedance values. The current exhibits harmonic distortion.
The Ê− thresholds may be calculated as follows: given a known complex line impedance, Z, the system is simulated with a driving voltage of 1 p.u. at one end of the line and a resistive load, with resistance R, at the other end. The magnitude of R is calculated such that the voltage at the load is reduced to 0.9 p.u. Ê− is calculated at the source for the operating point where the calculated R is the load and the source voltage is a single-frequency sinusoid at nominal frequency. This value of Ê− is Ê0min. The process is repeated for a value of 0.95 p.u. at the load and the value of Ê− used for Ê0max.
Accordingly, an IED such as IED 140 of
There are many known techniques for assessing voltage stability. These include Thevenin impedance matching, generator reactive reserve monitoring, and decision trees. Additionally, techniques based on measured power system state are possible, including running full simulations to determine voltage trajectories in the presence of uncertainty and contingencies. The purpose of this section is to show a simpler design based on energy packets.
Here is a basic system to demonstrated the algorithm principle. Initially, sinusoidal steady-state conditions are assumed and the load varies with a single state variable, α. For example, control on state a may be attempting constant power or controlling impedance to increase load in response to demand. In Equation 15, the load power angle ϕL is a fixed constant:
However, because increasing α is driving the load impedance to zero while the source voltage stays constant, the power delivered by the source can continuously increase.
Based on these principles, an assessment algorithm with energy packets is possible. The energy packets delivered at the source are monitored, and the assessment algorithm compares the energy packets consumed by the load for the same time stamps. At the maximum capability of the system, the value of energy packets delivered by the source continues to increase while the value of energy packets received by the load begins to decrease. Starting with Equation 14, the source-received energy packet set is defined as ES−[k] and the load-received energy packet set as EL−[k]. Equation 16 defines the resulting energy packet voltage indicator (EVI):
For a local voltage stability application, computing Equation 16 requires two devices measuring and sharing energy packets. Normally, energy at the source and load move in the same direction. At the system maximum, EVI[k] changes sign. For stability assessment, EVI[k] is compared to a suitable threshold (described later).
For the example of
The application of Equation 16 over a wide area requires a slight modification. In this case, based on energy packet exchanges, the total energy delivered by generation and received by loads is computed on a time-synchronized basis at each control location, illustrated in Equation 17. The relative performance of EVIi[k] for location i indicates the area most suitable for voltage controls, either continuous or emergency. Since the indicator measures energy directly in a load-shedding scheme, it indicates the amount of load to shed. The numerator ΔES− is based on the area of interest for voltage stability.
The detection of an impending voltage problem is achieved by taking advantage of the fact that proximity to the maximum power point is associated with voltage problems for typical load-control algorithms. Added security and sensitivity is achieved by including the EVI and its derivative, as shown plots 1200, 1205 of
Control algorithms may be developed for maintaining voltage stability, and may depend on the nature of the power system. Such algorithms may include disconnecting certain loads, connecting capacitor banks, disconnecting capacitor banks, adding power generation, removing power generation, controlling inverters to increase or decrease reactive power, and the like.
As mentioned above, the voltage control algorithm may depend on the nature of the electric power system loads as primarily inductive or capacitive. The following describes identification of the power system network as primarily inductive or primarily capacitive. Energy packets measure the energy sent and received at a given node over an interval of time. Energy packets are symmetric with the angle between current and voltage in steady state. Therefore, when an algorithm requires estimating the net capacitive or inductive nature of a network, a separate system identification algorithm is included. Although the system identification algorithm is not a contribution of this disclosure, this section demonstrates how to adapt two known algorithms for use with controllers based on energy packets. System identification may be performed by the metering module 120 of IED 110 in
Because energy packets measure instantaneously in time, the identification algorithm must not be based on measuring frequency or angles. For example, measuring the angle between current and voltage is not an option. The strategy employed here is to apply an instantaneous power calculation and then consider the sign as an indication of an overall inductive or capacitive network. An instantaneous power expression is shown in Equation 18:
Another option, without the derivatives, that requires polyphase signals is based on the instantaneous reactive power. First, the Clarke transformation is applied to three-phase voltages and currents, resulting in α, β, and γ components, shown in Equation 19:
Preact-1(t)=vαiβ−vβiα Eq. 19
For energy packet algorithms, the sign of Equations 10 or 19 indicates the inductive or capacitive nature of the network. With single-frequency sinusoidal conditions, both Eq. 18 and Eq. 19 calculate a constant value. When harmonics are present, the results of these may not be constant, but the averaged signal shows a strong prevalence to maintain the expected sign corresponding to capacitive and inductive loading. Thus, the parameter of interest (the sign) is used for identification, as shown in Equation 20:
γ=sign(preact) Eq. 20
With the determination of the nature of the power system as inductive or capacitive as shown in Equation 19, the embodiments herein may be tailored for the inductive or capacitive nature of the power system.
While specific embodiments and applications of the disclosure have been illustrated and described, it is to be understood that the disclosure is not limited to the precise configurations and components disclosed herein. Accordingly, many changes may be made to the details of the above-described embodiments without departing from the underlying principles of this disclosure. The scope of the present invention should, therefore, be determined only by the following claims.
Number | Name | Date | Kind |
---|---|---|---|
5271572 | Grandi | Dec 1993 | A |
5315527 | Beckwith | May 1994 | A |
5317472 | Schweitzer, III | May 1994 | A |
5367426 | Schweitzer, III | Nov 1994 | A |
5581173 | Yalla | Dec 1996 | A |
5680324 | Schweitzer | Oct 1997 | A |
5793750 | Schweitzer, III | Aug 1998 | A |
6603298 | Guzman-Casillas | Aug 2003 | B2 |
6662124 | Schweitzer, III et al. | Dec 2003 | B2 |
6845333 | Anderson | Jan 2005 | B2 |
6934654 | Benmouyal | Aug 2005 | B2 |
7027896 | Thompson | Apr 2006 | B2 |
7230809 | Whitehead | Jun 2007 | B2 |
7463467 | Lee | Dec 2008 | B2 |
7504806 | Labuschagne | Mar 2009 | B2 |
7630863 | Zweigle | Dec 2009 | B2 |
7788731 | Morris | Aug 2010 | B2 |
7930117 | Guzman-Casillas | Apr 2011 | B2 |
8068937 | Eaves | Nov 2011 | B2 |
8275485 | Schweitzer | Sep 2012 | B2 |
8275486 | Schweitzer | Sep 2012 | B2 |
8275487 | Schweitzer | Sep 2012 | B2 |
8476874 | Labuschagne | Jul 2013 | B2 |
8575941 | Samineni | Nov 2013 | B2 |
8816652 | Labuschagne | Aug 2014 | B2 |
9184795 | Eaves | Nov 2015 | B2 |
9853689 | Eaves | Dec 2017 | B2 |
20030161345 | Flowers | Aug 2003 | A1 |
20040186669 | Benmouyal | Sep 2004 | A1 |
20050280965 | Lee | Dec 2005 | A1 |
20060193099 | Schweitzer | Aug 2006 | A1 |
20060247874 | Premerlani | Nov 2006 | A1 |
20070086134 | Zweigle | Apr 2007 | A1 |
20070090811 | Labuschagne | Apr 2007 | A1 |
20090254655 | Kidwell | Oct 2009 | A1 |
20100007336 | De Buda | Jan 2010 | A1 |
20100161263 | Benmouyal | Jun 2010 | A1 |
20110084672 | Labuschagne | Apr 2011 | A1 |
20110153246 | Donaldson | Jun 2011 | A1 |
20110251432 | Schweitzer | Oct 2011 | A1 |
20120059532 | Reifenhauser | Mar 2012 | A1 |
20140100702 | Schweitzer | Apr 2014 | A1 |
20140257586 | Pai et al. | Sep 2014 | A1 |
20150070507 | Kagan | Mar 2015 | A1 |
20190260204 | Koval | Aug 2019 | A1 |
Entry |
---|
Samineni, Satish; Labuschagne, Casper; Pope, Jeff: “Principles of Shunt Capacitor Bank Application and Protection” 36th Annual Western Protective Relay Conference, Oct. 2009. |
Elif Uysal-Biyikoglu, et. al “Energy-Efficient Packet Transmission Over a Wireless Link”, IEEE/ACM Transactions on Networking, vol. 10, No. 4, Aug. 2002. |
Erol Gelenbe, et. al “Central or Distributed Energy Storage for Processors with Energy Harvesting”, 2015 Sustainable Internet and ICT for Sustainability (SustainIT), IEEE, Apr. 2015. |
Erol Gelenbe and Elif Tugce Ceran “Energy Packet Networks with Energy Harvesting”, IEEE Access, vol. 4, Mar. 2016. |
A. Monti, et. al “Towards a Real Digital Power System An Energy Packet Approach”, 2017 IEEE Conference on Energy Internet and Energy System Integration (E12), Nov. 2017. |
Roberto Rojas-Cessa, et. al “An Energy Packet Switch for Digital Power Grids”, 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Jul. 2018. |
Ivan Smon, et al “Local Voltage-Stability Index Using Tellegen's Theorem”, IEEE Transactions on Power Systems, vol. 21. No. 3, Aug. 2006. |
Engineering Institute of Technology “Fundamentals of Smart Metering—kWh and kVArh Meters” Article [online]. Jul. 13, 2017 [retrieved Dec. 3, 2019]. Retrieved from <URL:https:www.eit.edu.au/cms/resources/technical-resourses/fundamentals-of-smater-metering-kwh-and-kvarh-meters-2>. |
Schneider Electric “PowerLogic-™ PM5100 Series Power and Energy Meter” User Manual [online]. Mar. 2017 [retrieved Dec. 4, 2019]. Retrieved from <URL: https://download.schneider-electric.com/files?p_enDocType=User+guide&p_File_Name=EAV15105-EN05.pdf&p_Doc_Ref=EAV15105-EN>. |
Yokogawa “How to Measure Electrical Power” Article [online]. 2017 [retrieved Dec. 4, 2019]. Retrieved from <URL:https://tmi.yokogawa.com/us/library/resources/application-notes/how-to-measure-electrical-power/>. |
Schweitzer, Eddie: “Intelligent Capacitor Bank Control” Application Note Jun. 16, 2009. |
PCT/US2021/016794 PCT International Search Report and Written Opinion of the International Searching Authority, dated Apr. 8, 2021. |