IEC 60870-5 standard defines the communication protocol for remote control systems and for monitoring and controlling of geographicaly large processes.
Five documents specify the base IEC 60870-5:

- IEC 60870-5-1 Transmission Frame Formats
- IEC 60870-5-2 Data Link Transmission Services
- IEC 60870-5-3 General Structure of Application Data
- IEC 60870-5-4 Definition and coding of Information Elements
- IEC 60870-5-5 Basic Application Functions

The common standards are based on these documents:
- IEC 60870-5-101 Transmission Protocols, common standards especially for basic remote control tasks
- IEC 60870-5-102 Common standard for the transmission of integrated totals in electric power systems
- IEC 60870-5-103 Transmission protocols, common standard for the informative interface of protection equipment
- IEC 60870-5-104 Transmission Protocols, Network access for IEC 60870-5-101 using standard transport profiles

Numerical protection relays are used in electrical protection for detection of fault condition. The IED analyzes Current Voltage signal in the electrical system, and derives fault condition based on the output obtained by analysing the signals. For analysing the signal we perform FFT on the signal. The output of FFT is used and using various algorithms fault condition will be detected.

This paper describes a method to use numerical protection as power factor controller. A power factor controller provides control output to maintain the power factor in an electrical system to unity. To provide this control output PF controller analyses the current and voltage waveforms of electrical system. Since this is the same voltage and current waveform which are being analysed by numerical protection relay, and since these IED's have higher processing capacity we can built the power factor control algorithm within the IED. This method will help us reduce parallel processing of same data and thereby reducing the cost of the system by simply adding some software features.

INTRODUCTION

This discussion in this paper is based upon how a data processed by numerical protection relay can be effectively used as power factor controller. This paper here discusses power factor control mechanism only for distribution. So we will restrict ourselves only for distribution segment. A numerical protection relay which is used in control system for electrical transmission and distribution has voltage and current as signal inputs. Both these signal are obtained from the transmission or distribution line. These signals are first signal conditioned by an analog circuitry for removal of noise and other unwanted interferences. Now using a DSP (digital signal processor) we have to perform FFT on all the signals. We will get real and imaginary terms as output of FFT. From these terms we can find the magnitude and phase of each of these current and voltage signal. This data can now be used for calculation of power such as KW, KVA, KVAR, KWH and PF. One of these parameters is power factor (PF) which is crucial for our analysis. This power factor is then used for controlling the capacitor bank switching to maintain the PF of the system to unity. Thus we are using the data processed by a numerical protection relay for power factor control.

The complete system is divided into three steps:

Signal conditioning & analog to digital conversion.

Performing FFT on all the signals.

Using the output of FFT for power factor control algorithm.

SIGNAL CONDITIONING

Signal conditioning is hardware module which is built inside the numerical protection relay. This hardware part is responsible for converting incoming current/voltage signal to appropriate voltage levels so that it can be digitized. Also the signal conditioning circuit takes the responsibility of reducing the noise and other interferences which can distort the incoming signal. The signal conditioning circuit should be designed in such a way that it will pass the required harmonic content involved in signal processing and bypass the rest. Usually up to 15th harmonic is passed and above these are attenuated.

PERFORMING FFT

Usually a digital signal processor is used for performing FFT on the incoming signals. Depending upon the requirement of how much harmonic content is to be extracted from the signal the samples are taken. Again here we will consider a distribution electrical system, harmonic content up to 15th is considered. To achieve this we will have to take a 32 point DFT of the signal. The DFT can be calculated using the following formula

DFT Equations

(1)

(2)

Using the above mentioned equation we will real and imaginary terms in frequency domain. It can be graphically represented as follows

Figure 1. Conversion from time domain to frequency domain

So we will have N/2 real & imaginary terms. The magnitude and phase of the corresponding signal can be calculated by the following equation

(3)

(4)

Here frequency domain terms represent the fundamental quantity and the harmonics. The 0th term will represent the DC shift of the signal. The 1st term will represent the magnitude of the signal and remaining terms will represent the harmonic content.

POWER FACTOR

Power factor in an electrical system is defined as ratio of real power flowing to load to apparent power. Power factor has no unit. In any system it is desirable to have power factor of unity. But it is not case practically. For an inductive current lags and for capacitive load current leads. Usually in electrical system such as distribution the load is inductive. So depending on how much inductive load is present, capacitive banks are added in parallel to the load so that power factor can be maintained to unity. By doing so we reduce the losses in the system and hence increasing the efficiency. As discussed earlier we have real & imaginary terms of all current and voltage signals. The power calculation can be done as follows

SÌ… = VÌ…r .IÌ…r* + VÌ…y .IÌ…y* + VÌ…b .IÌ…b* (5)

Here

SÌ… = Three phase power

VÌ… = Respective line voltage

.IÌ…* = Complex conjugate of respective Line current

From the above mentioned formula we will have three phase power of the system. But in order to calculate the power factor we need to calculate real and apparent power. It can be done using the following formula.

P = real (SÌ…) - Real power (6)

Q = Imag (SÌ…) - Apparent power (7)

Now power factor can be calculated as

PF = P/S - three phase power factor.

NUMERICAL PROTECTION RELAY

All the above mentioned formulas and procedure is already being calculated by numerical protection relay in electrical system. As can be seen these are the exact calculation required by the power factor controller. So instead of recalculating the same output in another device we can use calculation for control output. A numerical protection relay has a lot of processing capacity. This processing capacity can be utilized for building control algorithm within itself. Thus we can have the capacitor bank switching output directly from numerical protection relay.

Also there is enough communication capability in the IED (numerical protection relay) such as Ethernet, Fiber optic. These are very high speed communications, which can be utilized to take the real time power data from the device. This data in turn is utilized by control algorithm build in another device directly.

In both the case we can save hardware cost. If the first solution is exploited, we can have use the Ethernet communication of the protection to some other purpose, such as web communication. By doing so we can have all the real time power data and power factor control and switching history available on internet. This capability opens a lot of topics for discussion as how the available data can be used, which is beyond the limit of this paper.

PROCEDURE

The processing capacity of numerical protection relay has to be utilized at the most by using the following procedure

The whole system is has two devices which perform the same calculation on the same signal.

Select a device with communication and processing capacity to perform the calculation in our case numerical protection relay.

Calculate the required data and use the same for other device's operation. In our case for power factor control algorithm.

Build the power factor control algorithm within the numerical protection relay. If not possible transfer the processed data by communication and just build the control algorithm elsewhere.

CONCLUSION

From this we have analyzed that a numerical protection relay with higher processing capability can be used as power factor controller. By constructing a power factor controller algorithm within the numerical protection relay we have utilized the processing capability for maintaining the overall system power factor.

Also we have reduced the system complexity and cost. As complexity has reduced we can some more features from the same system such as providing a web server application within the IED and get all the information on the internet.

Many of today's substation devices like protection relays are IEC 61850 compatible - one way or the other. From a SCADA point-of-view these and other devices can easily interface with such devices using the client/server communication services: •Get a value of single data object (GetDataValues – Client driven)
•Get a list of values of data objects (GetDataValues with list sent in each request – Client driven)
•Get the complete list values of data objects using a dataset object (GetDataSetValues – Client driven)
•Get the complete list of values of data objects (of a dataset) using reporting (reporting, General Interrogation – Client driven)
•Get the complete list of values of data objects (of a dataset) using reporting (reporting, Integrity period – Server driven)
•Get one (BufTm=0) or more (BufTm>0) value(s) of data objects (of a dataset) using reporting on data and quality change and data update – Server driven)
•GOOSE and Sampled Values … exchanges complete list of values of data objects of a dataset (events: application specific – Server driven
•Get sequence of value(s) of data objects (of a dataset) using logging (on data and quality change and data update – Client driven)

These IEC 61850 services (except for GOOSE and SV) are mapped to the MMS protocol.

In IEC 61400-25-4 the IEC 61850 services are mapped to:
•IEC 61950-7-2 ACSI and Information Models (LD, LN, DATA, DA, …) defined as webservices (almost all service in IEC 61850 become a corresponding WS in 61400-25-4)
•(full) Mapping according to IEC 61850-8-1 MMS
•(subset) Mapping to OPC XML DA
•(small subset) Mapping to IEC 60870-5-104
•(small subset) Mapping to DNP3

In the current scenario what should a SCADA vendor support in order to interface with 61850-compatible devices?

In existing installations with DNP3 or IEC 60870-5-101/104 it is recommended to keep these solutions. It is not recommended to just replace one protocol by another! IEC 61850 should be considered if SCADA systems want to benefit from the 3000+ standard information models and the substation configuration language (SCL, IEC 61850-6) to simplify the configuration of Gateways, RTUs, Data Management Systems, and SCADA systems and to simulate easily the Gateways, RTUs, and Data Management Systems!! Direct access from SCADA systems to IEDs may be required. Some utilities get rid of HMIs in Substations and provide IP access directly from the control center to the IEDs (trough routers).

EMS and SCADA systems of the big vendors have already or will have soon direct access to IEC 61850 compliant devices or systems. More to come soon.

DNP3 is an extremely flexible protocol with multiple layers that is ideal for automatic data transmissions in mission-critical environments. Today, DNP3 is commonly found within supervisory control and data acquisition (SCADA) systems commonly used in a wide range of industries including electric power, waste management, traffic control, mass transit, and manufacturing.

The protocol has been modified to address a new generation of technologies and innovations. The proposed ratification from IEEE as P1815 guarantees that DNP3 will continue to be expanded upon.

“DNP3 has proven to be a powerful and effective tool for streamlining and optimizing communications transmissions between central control systems and remote devices, thanks to exceptional, forward-thinking stewardship by the IEC and DNP3 Users Group,” said H. Lee Smith, president of the DNP Users Group, the group that has developed and maintained standards originally developed by the International Electrotechnical Commission (IEC) into what will become IEEE P1815.

“As we build and expand upon the firm foundation already laid, we expect IEEE P1815 to continue its successful trajectory, finding new and deeper relevance across a host of applications and industries,” continued Smith.

Development and expansion of P1815 will continue as a result of a collaboration between IEEE and the DNP Users Group. IEEE will integrate existing communications architectures as well as emerging ones and will evaluate new features and additions as they are proposed while increasing the interoperability between different types of devices and operational networks.

IEEE will also focus on finalizing security protocols that address cyber security issues and designing new frameworks that would allow P1815 to be easily deployed in a smart grid environment. As the frequency of widely-publicized cyber attacks increase the need to shore up communications security is emphasized. Cutting-edge security will be incorporated within P1815 to address these concerns.

The new IEEE standard is expected to play a significant role in smart grid deployment. The IEEE development team will also focus efforts on developing a flexible and adaptable architecture that will standardize the release of smart grid applications. The developing smart grid depends upon an open but secure architecture that is able to communicate with a variety of protocols and functions including power distribution and transmission, advanced communications, and supporting software.

“IEEE has emerged as the premier global resource for smart grid information and technical expertise, therefore, it is appropriate that it undertakes a leadership role in further adapting the IEEE P1815 standard for smart grid use,” said Judy Gorman, managing director at IEEE’s standards association. “Interoperability and security are critical factors in bringing the smart grid online, and IEEE P1815 will ensure these vital requirements are being met.”

Ratification of the new standard is planned for mid-2010 while IEEE continues to develop the standard until then.

The advent of automatic meter reading (AMR) came about in the mid-’80s, and more prominently in the early 1990s as an automated way to collect basic meter-reading data. The term and technology behind advanced metering infrastructure (AMI) began showing itself around 2005, evolving from the foundations of AMR. As not uncommon in this industry, we often hold on to the label that came first or use two terms interchangeably, even if the actual meaning or definition is slightly different. All AMI systems contain AMR functionality (although it’s not the core of its purpose), but all AMR systems are not AMI systems.

Definitions

According to the Demand Response and Advanced Metering Coalition, AMR is defined as a “system where aggregated kWh usage, and in some cases demand, is retrieved via an automatic means such as a drive-by vehicle or walk-by handheld system.” A more expanded definition likely includes all one-way systems, drive-by and walk-by systems, phone-based dial-up systems, handheld reading entry devices and touch-based systems. These systems tend to be collection only, without means for broadcasting command or control messages. In addition, data from AMR systems is typically gathered only monthly or, at most, daily.

AMI is typically more automated and allows real-time, on-demand interrogations with metering endpoints. The Federal Energy Regulatory Committee (FERC) defines AMI as “a metering system that records customer consumption hourly or more frequently and that provides for daily or more frequent transmittal of measurements over a communication network to a central collection point.”

AMI requires requisite bandwidth to supply more than merely metering and power-quality information. AMI systems need to have appropriate bandwidth and broadcast capabilities to allow for demand response/load management as well as distribution automation.

Available Information

Because of the inherent differences in AMR and AMI, the data available from each system differentiates them.

AMR systems can typically provide the kWh reading and possibly peak kW demand for the month. Other limited data may also available, depending on the system deployed.

AMI typically provides a substantial payload of information. The list of detailed information that can be supplied via AMI systems includes: cumulative kWh usage, daily kWh usage, peak kW demand, last interval demand, load profile, voltage, voltage profile, logs of voltage sag and swell events, voltage event flags, phase information, outage counts, outage logs, tamper notification, power factor, and time-of-use kWh and peak kW readings. With high-end AMI systems, nearly all of this information is available in real time and on demand, allowing for improved operations and customer management.

AMI systems can also be used to verify power outages and service restoration, perform remote-service disconnects and reconnects, allow automated net metering, transmit demand-response and load-management messages, interrogate and control distribution-automation equipment and facilitate prepaid metering.

When studying the list of available information, one easily sees the differences. The functionality available in AMI has caused many utilities throughout North America to invest in AMI systems, including utilities that previously invested in AMR systems. Utilities have various reasons for wanting to increase their AMR systems’ functunality.

Benefited Parties

Because of the differences in available information, the number of departments that can benefit from the system is vastly different (see Figure 1).

The beneficiary list from AMR is short, with only the metering and billing departments benefiting. AMI can benefit groups ranging from engineering and operations to asset-management and planning departments. In addition, AMI has the built-in tools to enhance customer service and satisfaction.

The drivers for AMR are typically limited to improved billing accuracy and a reduction in the time and expense to read and bill meters.

While AMR systems were advanced in their day, they just don’t have the capability to deliver most of these goals to electric utilities. This is not a slight on AMR; those systems were designed in a different time for a different purpose. There are options that allow utilities to migrate from existing AMR systems to a more powerful and flexible AMI system.

While AMI systems also read meters, it’s no longer a primary driver for most utilities.

In 2007, the Cooperative Research Network, the research arm of the National Rural Electric Cooperative Association, identified its top two dozen applications for AMI systems. Meter reading didn’t make the list.

As highlighted above, there are numerous drivers for utilities to implement AMI systems. Some are touched on below by utilities that have embarked on AMI system implementations.

Bob Brennan, president and CEO of Manitoba Hydro, remarked at the kickoff of Manitoba Hydro’s implementation, AMI will allow the utility to “ … achieve key objectives set forth in our corporate strategic plan, particularly in the areas of conservation and stewardship, delivering customer value, financial performance and employee safety.”

Southern Pine EPA in Taylorsville, Miss., implemented AMI because it says it will give the company the ability to achieve its mission, “ … to provide reliable, safe and efficient services at a competitive price to all our customers.”

According to Dwight Duncan, Ontario minister of energy, “Smart meters will empower consumers to better manage their electricity costs and respond to pricing incentives that encourage both conservation and load shifting to off-peak periods.”

The U.S. Energy Policy Act of 2005 (also known as EPAct 05) encourages the use of time-based rates to enable consumers to manage their electric energy use and costs through AMI and its associated communications technologies.

Tools for E&O Professionals

AMR’s limited functionality and flexibility offers little in engineering tools. But what can AMI mean for utility-distribution engineers and operations personnel? When used at its fullest potential, there is much to be gained.

Improved system-voltage monitoring can lead to better regulation, improved capacitor and regulator placement and more accurate voltage-drop analysis. Improved load information leads to better load studies and analysis, resulting in improved planning and system design. Improved reliability monitoring can lead to improved outage response, proper system-protection analysis and ultimately, a decrease in outages and outage time, raising reliability indices. Improved monitoring and information flow can also lead to better management of critical assets such as transformers and capacitors. Distribution-automation tools implemented via AMI networks provide for real time interrogation and control of remote intelligent electronic devices (IEDs). The information and reporting tools available within AMI systems can allow for targeted vegetation management and line patrol, prioritizing and controlling maintenance spending. Last, engineers can use the systems to pinpoint system losses, and once identified, reduce them.

Opinions & Conclusions

Uncertainty in power-supply and generation markets is likely to lead to additional costs being passed to distribution utilities. AMI provides the tools and flexibility to pass these charges on to consumers as needed. In addition, the demand response and pricing programs that can be implemented via AMI systems allow the utility and customers a number of options to manage their usage.

AMR systems are good doing what they do: reading meters. Nevertheless, as they prepare for the future, it will likely be harder for most utilities to justify the expense of a system to provide meter reading alone. The benefits of AMI tend to provide a more palatable and sensible return on investment (ROI) for today’s utilities. This also tends to be true for utilities that invested in early AMR technologies, as manageable and cost-effective migration plans can be set into action.

So, what does AMI offer? First, AMI can provide a utility a real-time connection to all its customers, providing actionable information to consumers and utility staff. Second, a utility can have a better understanding of the quality and distribution of its product, allowing for improvements in the utility’s reliability and efficiency. This can lead to improved financial benefits for the utility and improved satisfaction for customers.

Upon completion of Lake Country Power’s AMI rollout, general manager Rick Lemonds said, “Our AMI system has already made positive service impacts by providing the right employees with the right information when requested. This provides our members with data to support answers to their questions.”

Although AMR had its run, the more one looks at AMI, the more it seems its uses are limited only by imagination.