top of page
  • Writer's pictureAlibek Jakupov

Smart Grids Data Processing Analysis



SmartGrids concept


Smart Grid is a network that uses info-communication technologies to collect information on energy consumption and production, store the data received, interpret it and distribute energy in accordance with the findings.


The development of "smart grids" is a logical consequence of the changes that affect the processes associated with generation, storage, redistribution, utilization and payment of electricity, including that received from renewable sources.


Renewable Energy Sources (RES) are characterized by a certain complexity of connection and utilization due to the dependence on random natural factors. Due to the depletion of fossil fuel resources and environmental problems, the role of RES and more intelligent power distribution systems will increase.


Analysis of specifics of Smart Grid operation, data exchange protocols will allow to develop appropriate data parsers from the distribution system to the RES monitoring system and development of data analysis and system management services.



Key differences in the SmartGrids architecture



Environmental problems as well as the growing needs of the population have led to the need to use renewable energy sources (RES). Advantageous forms of RES, such as wind and solar power, are very flexible in use but require more sophisticated control systems.


Using Smart Grid involves reorganizing the network architecture and redesigning utility services. Implementation of this technology implies consideration of technical infrastructure of the region.


In terms of development, Smart Grid is in the transition phase from basic concept development and development of national and international standards to the creation of pilot projects, including a large number of industrial projects.


The current power supply system is characterized as passive and centralized, i.e. the network is centralized and there are no real-time changes on the part of both users and customers. Smart Grid is designed to improve network principles by offering new tools for active and distributed interaction.


In classic networks, the client (consumer, building) in the context of the role performed in the distribution network (110/10/0.4 kV) can not be an active element, because it can not affect the main parameter - power consumption. First of all, it is determined by the ability to control the amount of generated, consumed and distributed energy. The client is not able to directly control neither the volume of electrical power nor the elements of transformer stations. Moreover, the power distribution networks themselves are not engaged in real time monitoring, and often do not have data on consumption in real time. From a commercial point of view, the system is also unidirectional, i.e. the client is not allowed to regulate the terms of his tariff plan. The networks (in this case, energy sales organizations) learn about customers and their level of activity once a month, during the period of payment for public utilities, i.e. consumers pay for public utilities at unified tariffs that apply to the whole settlements. Any changes in tariff plans take place at the level of regional authorities, and sometimes at the level of the state, and take a long time. It is not possible to interact with the system in real time, as well as to adjust and monitor the volume of consumption by the client.


In terms of energy distribution, the system is also unidirectional. The energy comes only from the supplier to the consumer and cannot be redistributed.


Obviously, when large energy providers distribute resources centrally and without data on actual consumption and, as a result, the real needs of customers at the moment, the relationship between consumers and suppliers is not regulated by the laws of supply and demand. Also important is the fact that in this case the system is technically vulnerable, as suppliers are not able to react to network failures in time and allocate resources optimally during peak hours.


This statement is true not only for individual buildings, but also for entire communities. It is especially important for large cities with a centralized energy distribution system, where uniform tariffs are offered for completely different consumers with different consumption volumes.


Smart Grid is an advanced end-to-end solution that combines the principles of participant-to-device interaction and optimal use and allocation of resources within the network with the power storage systems being developed.


Smart Grid Architecture Components

At a time when population growth, rising prices for utilities and increased requirements for service quality cause additional costs for infrastructure development, the development of smart distribution networks is one of the solutions to the problems that arise.



Innovative features of SmartGrids architecture



A bidirectional active power distribution channel from generators to client devices and a bidirectional communication channel between all network members.


In order to ensure uninterrupted communication between all system participants, Smart Grid uses digital communication networks and data exchange interfaces. One of the key tasks of Smart Grid is the ability to manage the balance between supply and demand within the network. In this regard, all elements of the network exchange in real time as data on energy consumption, modes (tariffs) of consumption, the amount of energy consumed and planned consumption (predictive data based on statistical information), as well as some commercial information.


The Smart Grid provides protection and self-healing for major failures, natural disasters, and external threats (e.g. local AC/DC power module failure detection based on statistical data).


From a commercial point of view, the use of this technology implies the appearance of a new service market.


Thanks to the development of info-communication technologies Smart Grid can be used both on the scale of administrative premises or enterprises, and for home electrical devices. In this context, Smart Grid partially implements the concept of "Internet of Things", respectively, all devices included in a common system (local and global) must be equipped with means of information interaction.


The definition of "Smart" is justified by creating a channel of communication with the central data processing module, which is responsible for making decisions based on the received data. "Smart" architecture implies the integration of digital technologies into the supply network, mainly the power supply network, and the integration of these networks into a common utility system. The power supply networks are divided into three classes according to the level of transformation: deep transformation of the entire infrastructure, such as Strong Grid in China; creation of an additional digital layer, which implies intelligent data analysis; transformation of business processes, for commercialization and monetization of new technologies.


Currently, the main emphasis in the modernization of power supply networks is on the automation of power distribution processes and the process of transition from the main sources to alternative ones. New opportunities should entail changes in the areas of reliability, efficiency, flexibility, commercial attractiveness of distribution and storage networks.



Reliability


By equipping all meters and nodes with special PMU modules (phasor measurement units) for network monitoring, the task of troubleshooting is facilitated. The system calculates a statistical expectation in order to obtain information on the approximate number of generators to be used at a given time. The statistics are used for early fault detection in the local AC/DC power supply module.


There are opportunities to improve power supply reliability, such as control of fire hazardous areas in the circuit, emergency alarm, with the possibility of automatic power-off, automatic calls to technical support and rescue services, etc. At the same time, the amount of data sent via the communication channel is relatively small compared to the amount of information used to provide voice calls, Internet access and television.



Efficiency


Efficiency is achieved by a branching network, i.e. a transition from a centralized topology to a highly distributed one. Alternative energy sources are connected to existing systems, which can provide customers at peak loads.



Flexibility


One of the system's key advantages is load control. The total network load may vary depending on the time of day. Classic networks do not change the number of generators depending on the load of the network, which causes excess power during periods of decline in customer activity. It is possible to adjust during peak activity hours and billing for power consumption when Smart Grid servers start informing clients (both individuals and businesses) about the amount of power consumed and peak activity time. Enterprises are given the opportunity to contact the devices directly to reduce the amount of power they consume. Utilities providers tend to increase the price of energy during peak hours, which encourages customers to use utilities during less busy hours. In this way, consumption will be implicitly regulated by market laws. For example, the system of the Italian company Enel allows customers to regulate the tariff conditions depending on energy consumption.



Commercial attractiveness


Smart Grid allows for systematic communication between manufacturers and consumers (the manufacturer offers a price, and the consumer chooses whether it is profitable or not), as well as allows customers and manufacturers to choose more flexible terms of cooperation. The maximum energy price is set only under critical network load conditions, and therefore customers are encouraged to plan their energy consumption strategy in advance.


In the 1980s, the ability to automatically track the power consumption of large customers in real time became possible, which in turn became the concept of "Smart Meter", which allows to track the power consumption of any customer in almost real time.



"Smart Meters" Functions



The "Smart Meters" are designed to read, store and retrieve information in real time, report energy losses and monitor the quality of utility resources. To implement these functions, the meters are equipped with microcontrollers with autonomous power supply for 5-10 years, the so-called Crystal-to-Chip Systems (CSC). These single-chip systems have the ability to adapt the circuit to a specific task and certain conditions, without using discrete components.


Smart meter operation scheme

Data can be exchanged over power lines, for example, using the G3-PLC protocol. Thus, on the basis of G3-PLC in France is carried out the design of innovative infrastructure for metering and measuring energy, with more than 35 million users. This technology is the basis for the creation of international standards, such as ITU G.hnem/G.9955 and IEEE P1901.2. In addition, there are a number of analogue and mixed (digital-analog) solutions, including power management information systems, real-time clocks and communication facilities.



Consideration of local regulations



In North America, the AMR (Automated Meter Reading) regulatory standards establish frequency regulations for data collection and transmission. Moreover, these regulations define how much data a meter must store at a certain point in time. Since the communication channel is not always reliable and can be hacked, some of the regulations require utility providers to store information about the last two transmission sessions - to verify the data during billing. In this connection, developers are forced to increase the amount of local embedded memory in the smart meter integrated circuit. Accordingly, the regulations of specific regulatory authorities directly determine the development process of smart meters, including at the level of "iron" (chip).



Data protection



In emerging markets, where the amount of energy lost or stolen makes up a significant proportion of the total energy within the network, data protection is of great importance. The ability to detect and prevent malicious activity with a "Smart Meter" can simplify control and reduce costs for utility providers. "Smart Meters" with integrated chip-level functionality are an effective platform for further development, such as providing wireless communication with thermostats to control load during peak hours.



Intellectual meter scheme



Intellectual meters : Architecture and implementation



Early architectures of solid-state meters supposed the use of many information systems. At such architecture the microcontroller controls the whole system and the display, and several analogue-digital converters and signal processing processor perform metrological tasks. Subsequently, to combine the analog-digital conversion and digital signal processing, special information systems were used, made to order by the manufacturers of metrological equipment. It is obvious that such architectures do not possess sufficient flexibility required in the conditions of the modern market, as the execution of the information system to order requires considerable time and own investments for additional research. It should also be noted that custom information systems were suitable only for certain networks with specific architecture, which reduced the effectiveness of the solution.


In classic architecture, where several inverters are used, the following disadvantages can be highlighted: low accuracy due to interchannel crosstalk and high component costs. Interchannel crosstalk, in turn, requires additional protection of the technical components and the embedded software. It should also be noted that to implement a wide range of analogue 2000:1 input signals, organizations have to switch to differential mode, which is an expensive solution.


As one of the optimal solutions can be considered the method Single Converter Technology (developed by Teridian), which belongs to the class of integrated measuring solutions of crystal-based systems. The architecture, which uses this method as a basis, rationally uses metrological functionality by combining a single sigma-delta ADC with multiplexed inputs and a programmable computer (Computation Engine - CE) to process data in real time. With this solution, developers can flexibly customize the calculator to meet the measurement and processing requirements of utility organizations, minimizing changes at the hardware level.


Multiplexed systems are a cheaper alternative to classical systems, where the architecture provides a separate analog-to-digital converter for each channel. Solutions based on multiplexed systems reduce interchannel crosstalk by using switching circuits that allow input channels to be scanned by selecting each channel in a circle for processing with the same analog-to-digital converter.


This approach is particularly effective for applications such as power management with several signals that are similar in nature. When using such solutions, the main condition is to store phase information between channels. This allows the CE calculator in a multiplexed system to perform measurements on different channels simultaneously. Multiplexed crystal-based systems with a single converter allow the matching of gain and compensation offsets, reduction of interchannel crosstalk and design flexibility. Together, these benefits provide a relatively low-cost solution for high accuracy measurements with a wide dynamic range (2000:1).


The crystal-based systems have the ability to quickly reprogram so that the CE calculator's embedded software can be updated on a simplified basis and engineers have the ability to configure metering equipment with various current sensors such as current transformers, Rogowski coils and current shunt. This simplifies the introduction of anti-intruder techniques.


There are two main methods to implement an automatic meter reading system. The choice of method depends on the specific legislation of the particular country or region.


The first method allows extensive metrological functionality in the final point of measurement. Regulatory authorities in certain regions impose strict requirements on utility companies to reduce the risk of data loss and to obtain accurate energy consumption data for billing purposes. According to the regulations, meter reading is carried out at fixed intervals (every 15 minutes), and the received information is sent to the operator every 8 hours. However, to ensure protection against possible failures when sending information via the communication channel, the regulations require that at least two samples of data are always stored at the measuring point. Thus, it is necessary that the metrological chip can store consumption data for 16 hours.


The second method assumes less functionality, but more favorable price conditions. In case regional authorities impose more loyal requirements to the process of collecting and interpreting meter readings, utility companies reduce the cost of implementing metrological functions in the meter (unless a broader meter function is needed to ensure the payback of the system, to prevent unauthorized actions). According to long-term forecasts of experts, by combining the functions of AMR with the metrological system on the crystal, it is possible to achieve even greater savings. At the moment, the main difficulty in implementation is mainly the heterogeneity of AMR communication methods. For example, information can be transmitted via conventional modems (in fixed or cellular networks) or using power lines (PLC). Also note that in this case the price for additional equipment may vary from USD 3 (when using PLC modems) to USD 20 or more (when using cellular modems).


The possibility of system reprogramming in conditions of active network usage gives utility organizations flexibility to change tariff plans depending on changes in the volume of energy consumption within the network. Thus, when the majority of customers change the hours of peak energy consumption, as well as when the value of demand depends on the season, there is a need to change the period of the day for which there are maximum electricity prices. By tracking electricity fluctuations and changes in peak load values, it is possible to change the tariff policy.


The ability to protect the power supply network from unauthorized actions is one of the key advantages of smart grids. Classic actions by intruders include breaking into a meter's structure by opening its case and locking the mechanism, placing magnets near the meters to saturate its magnetic components, adding capacitance, loads with a single-period rectifier or high instantaneous current. It is not uncommon to bypass the meter, resulting in an increase in AC current through the Counter Neutral Pins. Modern solid-state metrology systems allow designers to prevent intruders by obtaining data from the common power consumption network about such characteristics as unbalanced load, current through the neutral wire, direct currents caused by single-period rectifiers, detection of external magnetic fields. Node (substation) meters can also calculate the difference between the total energy generated and the total energy billable and report any deviations over the AMR network. In cases where a forensic investigation is assigned to recover stolen energy, smart meters help to obtain reliable evidence: accurate data on time of theft and amount of stolen energy.


Basic features for smart meters:


  • Multi-port communications with flexible architecture to support AMR channels; ability to interact with local network devices such as thermostats; development of a topology that includes subnet measurements

  • Multi-channel readout of input data with high processing speed, such as on the basis of SCT (Single Converter Technology), discussed above, to reduce the cost of the system I thank the multiplexing of inputs using sigma-delta ADC in combination with a programmable computer CE

  • Real-time processing of various input signals from sensors with minimal use of hardware components; correction for temperature or other environmental parameters to improve efficiency and avoid calculation errors

  • Firmware that can be upgraded during active use to extend the life of the smart metering system and dynamically adjust tariff plans for the best use of resources

  • Multiphase load monitoring and processing tools to manage power consumption, analyze network load and optimize the real-time monitoring process.

  • Visualization of the received data on the general screen, with support of different supply voltages and screen resolutions

  • Different volumes of internal flash memory for storing consumption data, tools to interact with external memory

  • Set of tools and mechanisms to detect the actions of intruders to prevent theft of energy resources; support for current transformers, Rogowski coils and current shunt, as well as combined current sensing mechanisms; circuit break sensor

  • Full-featured operation with unipolar power supply in special safe mode, which provides for detection of actions of intruders, with single and multiphase power readings

  • Real Time Clock (RTC) embedded in the overall topology

A range of analog interface chips for meters contain integrated real-time clocks with an accuracy of 60 minutes per year. In case the meter is connected to an intelligent power supply which synchronizes the real-time clock at certain intervals, this error can be ignored. In the case of classic meters, consumers, at a certain time interval, will start to encounter significant discrepancies between the invoices submitted for payment and the data taken from their own meters, unless the classic meters are equipped with expensive high-precision real-time clocks.


The functionality of the integrated real-time clock includes measuring and tracking the integrated temperature sensor and optimizing the capacitive load of the integrated resonator on the basis of the received data, in order to compensate for the natural temperature loss of the frequency of the reference resonator. Due to the fact that the frequency may vary depending on external conditions, at each operating temperature, the resonator and chip are calibrated in a single module to ensure greater frequency stability. In this case, there is no need for engineers to perform calibration to obtain highly accurate data. Some of the latest integrated real-time watches use MEMS technology to improve the accuracy and stability of the design itself. The all-silicon resonator used in this watch provides the same low frequency and low current as large information systems based on a quartz resonator, while maintaining a compact design. Moreover, solutions based on this technology are highly resistant to high-temperature assembly processes, are able to operate after shocks and vibrations exceeding 20g, and use an offset scheme to compensate for aging.


Some solutions use a temperature-compensated silicon generator as a basis. Using the measurement data from the integrated temperature sensor, the temperature compensation algorithm optimizes the resonance frequency to take into account temperature effects on an automatic basis. With this solution, the system can guarantee high accuracy when measuring temperature. Unlike large information systems based on a quartz resonator, such solutions have a frequency loss of less than ± 0.5 ppm after high-temperature reflow soldering, and also provide stability of frequency characteristics (< ± 5 ppm) at all operating temperatures from -40 to +85°C.


Flexible on-chip measurement systems, both multiphase and single-phase, are used in residential applications (monitoring, saving data from the last few sessions, etc.), which typically contain a 5-MHz 8051-compatible microprocessor core, a 32-bit programmable computer, a real-time clock, integrated flash memory with up to 64KB and RAM up to 5KB.


The characteristics of intelligent systems considered above show that developers, engineers and architects of power supply systems use them to develop a variety of metrological devices - from the cheapest solutions with limited functionality to high-quality devices with a large amount of integrated internal memory, the ability to quickly reprogram and high-precision meter readings. Systems based on smart meters are very flexible. This allows developers and utility companies to adapt to new market conditions and growing customer needs as the smart meter market develops, and to flexibly change their policies to meet the rules and standards of regulatory organizations, while maintaining high cost-effectiveness and efficiency in use.



Electric network monitoring and control



The list of functionality of modern power supply network monitoring systems includes the following: power monitoring on generators, network load balancing and distribution, protection and data collection. The systems provide protection for transformers, fuses and other components, perform diagnostics of the power supply network and detect failure conditions. In order to save energy, the system dynamically aligns the load and monitors power quality. Standardized accuracy is dynamically required to monitor power delivery in real time, detect failures, and balance the network load. Thus, according to IEC 62053 (European Union standard) for equipment of class 0.2 the minimum required accuracy of measurements is 0.2% of the nominal values of current and voltage. In order for the power factor indicators to be sufficiently accurate, a phase coordination factor of at least 0.1% is required at the time of measurement.


Typically, when distributing multiphase power (e.g., three-phase), energy supplier organizations use a star or so-called Y-shaped circuit, due to the peculiarity of connecting windings of three transformers to one point in the form of Latin letter Y. The line voltages are phase shifted by one third of a turn, i.e. by 120°. In the case of an equal load in each of the three phases, the system is considered to be balanced, therefore there is no need for current through the neutral conductor, which is connected to the point of connection of the windings of the three transformers and allows the unbalanced loads on the connection lines to be coordinated.


Voltage and current readings at different phases in power supply monitoring systems are monitored using analogue-to-digital converters. For each phase in the classical scheme, the power readings are measured using current transformers and voltage transformers (4 pairs in total for each phase and the neutral pair).


Multiphase power monitoring system with Y-circuit configuration

The digital signal processor calculates the power factor values based on the measurement results and also evaluates the parameters of the system itself (active, reactive, total energy). The frequency of sampling is regulated by regional and international standards. Minimum requirements include a wide dynamic range (at least 90 dB) and sampling rate of 16 thousand samples per second. These parameters allow analysis of multiple AC network harmonics, and identify short-term failures such as throws or power failures.


To solve the problem, nowadays precision analog-to-digital converters with the function of simultaneous multi-channel sampling are used, which are synchronized within the information system itself, which reduces the volume of system costs.


16-bit analog-to-digital converters with several channels (4, 6 or 8), with a minimum signal-to-noise ratio of 92 dB are used. 24-bit inverters with 4 channels and a minimum signal-to-noise ratio of 117 dB can be used.


If the input impedance of an analog-to-digital converter is sufficiently high, the transformers can be connected directly to the converters themselves. If the input impedance level is low, a precision low-noise amplifier is used.


Due to the fact that environmental factors (temperature, humidity, drift, etc.) exist at the place of operation, the system performs self-test and correction at certain intervals to compensate for them.


The excessive adjustment range in this case is eliminated by randomly setting the upper and lower voltage of the digital-to-analogue converter using calibrated meters and digitally controlled potentiometers. For example, with an upper value of 2 V and a lower value of 1 V, it is sufficient to use an 8-bit device to implement step 0.0039 V in this range. For automatic recovery of the calibration values, digitally controlled calibration transducers and potentiometers are used, which have an internal non-volatile memory from which the data are downloaded.



Smart Grid Communication system



Smart Grids must perform intelligent real-time monitoring, ensure secure power network operation and load balancing. On a two-way communication channel, information with sensor and meter readings collected from all parts of the network is collected and sent to the network manager. Advanced network functionality allows you to manage the entire system in real time. On the scale of the network are divided into 3 types

  • Regional network (Wide area network, WAN) - in this case the coverage area is the most extensive. In this topology, the control center communicates with the local networks.

  • Network Neighborhood area network (NAN) - In this architecture, the network manages the entire communication channel between the regional and home network, and all data sent over the channel on high voltage lines.

  • Home area network (Home area network, HAN) - This topology involves communication with end customers (homes, organizations). Communication between segments is done through gateways (nodes). Data from the meters are accumulated at the hubs and sent to the network operator's control room. Data on power consumption at the end point (residential building, company) are collected by electronic meters. Further on the communication channel, the meter sends the information to the home network gateway. In certain cases an electronic meter can function as a gateway.

The transmission environment and the volume of sent/received data ultimately determine the type of communication technology and network protocols on each segment of the power supply network. As a rule, the most popular solutions are the use of cellular/paging networks, dedicated radio channels and data exchange via Power Transmission Lines (PTL).



Communication protocols in Smart Grids


Protocols are used depending on the size of the network


Wide area network, WAN

Protocol

Wireless (cellular networks 2G/3G/LTE, GPRS)


Advantages

The cellular network infrastructure has a large coverage area and is accessible; allows transmitting large amounts of information over long distances


Drawbacks

In order to have monthly access, the energy supplier has to pay for the cellular operator's infrastructure rent; in this case the energy supplier does not have access to the infrastructure.


Notes

In this case, the most optimal solution is the wireless interface



Neighborhood area network, NAN


1

Protocol

ISM Wireless Protocol


Advantages

Extensive coverage area; transformer bypass provided


Drawbacks

High dependency on the region's infrastructure; the so-called "dead zones" interfere with the installation and maintenance of equipment


Notes

Under certain topologies (e.g. US topology), it is possible to actively use


2

Protocol

IEEE 802.15.4g


Advantages

Extensive coverage area; transformer bypass provided


Drawbacks

Has not yet been approved as standard


Notes

Applicable in certain topologies


3

Protocol

ZigBee


Advantages

Low power consumption allows battery operation; affordable price; is a popular standard


Drawbacks

Information transfer rate is not high enough; small coverage area; when obstacles are encountered, communication quality is reduced


Notes

In the conditions of local networks, it is practically inapplicable


3

Protocol

First generation PLC (FSK, Yitran, Echelon)


Advantages

Affordable price


Drawbacks

The proposed reliability level does not allow for secure data transmission; insufficient bandwidth


Notes

For the implementation of intelligent power supply networks, the protocol has insufficient security and weak bandwidth.


4

Protocol

First generation narrowband OFDM (orthogonal frequency division multiplexing)


Advantages

In terms of range, bandwidth and transmission reliability, this solution is a better alternative to the FSK protocol.


Drawbacks

This protocol does not allow the transfer of information through transformers; low level of flexibility of the protocol: not compatible with the first generation PLC protocols.


Notes

The high cost and low flexibility of the system require significant investment in its implementation.


5

Protocol

PLC Broadband


Advantages

High transmission speed


Drawbacks

This protocol does not allow for the transfer of information through transformers


Notes

In a large-scale architecture, infrastructure costs significantly exceed the cost of alternative solutions


6

Protocol

G3-PLC


Advantages

High level of reliability, long range; ability to transfer information through transformers; low infrastructure costs; frequent transfer of information due to high speed; compatibility with FSK protocol; open standard; IPv6 support


Drawbacks

Not currently approved as a standard (draft IEEE Z1901.2 for data transmission in smart grids).


Notes

In local conditions is the best solution, regardless of the region



Home area network, HAN


1

Protocol

ZigBee


Advantages

A popular solution; this standard provides an affordable price and low power consumption.


Drawbacks

Limited range; when obstacles are encountered, communication quality is reduced


Notes

When using water and gas meters, is the optimal solution for information transfer


2

Protocol

Wi-Fi


Advantages

High transmission speed


Drawbacks

Average coverage area; in the presence of interference in the form of walls and foundations of buildings there are problems with signal passage


Notes

Not able to meet the needs of utility companies, but is an acceptable solution for household applications


3

Protocol

First generation PLC (FSK, Yitran, Echelon)


Advantages

Affordable price


Drawbacks

Low noise immunity


Notes

Not applicable in case of large amounts of interference (home conditions)


4

Protocol

First generation narrowband OFDM (orthogonal frequency division multiplexing)


Advantages

In terms of range, bandwidth and transmission reliability, this solution is a better alternative to the FSK protocol.


Drawbacks

This protocol does not allow the transfer of information through transformers; low level of flexibility of the protocol: not compatible with the first generation PLC protocols


Notes

High price and low flexibility of the system require significant investments in implementation


5

Protocol

PLC Broadband


Advantages

The bandwidth is wide enough to ensure full performance


Drawbacks

In the conditions of local networks has an insufficient level of coverage


Notes

Not able to meet the needs of utility companies, but is an acceptable solution for household applications


6

Protocol

G3-PLC


Advantages

High level of reliability; information transfer rate is sufficient in home network conditions; IPv6 support allows interaction with a large number of devices


Drawbacks

Not currently approved as a standard (draft IEEE Z1901.2 for data transmission in smart grids).


Notes

In a home environment is the best solution, regardless of the region


Among the protocols used to implement dispatching control within a power network, the CPQ working on top of HTTP or HTTPS can also be distinguished. Accordingly, all requests are made using the standard GET and POST methods.


The communication system consists of three levels. The lower level is the collection of information from sensors, the intermediate level is the data transmission server, and the upper level is the server for data storage and processing (polling server). Communication is carried out through the Internet, the local network of the enterprise or radio channels.


Communication between power consumers and the network is possible using common data transfer protocols and a common application layer. CPQ, as one example, is a communication protocol that mainly influences changes in the data transmission system, which makes it possible to exchange data in real time between different communication layers regardless of distance and hardware differences. As a result, the amount of data transmitted, its timeliness and security of transmission are increased.


Communication channel scheme

The communication channel between the power supply network operator and the hub is an example of a regional network. The Ethernet protocol is used to implement the network with the help of fiber-optic communication means, while one of the cellular protocols is used with wireless technologies. Typically, smart power system designers use cellular or WiMAX to communicate between the network operator and hub.


The channel of communication between the meter and the hub is an example of a local network. To implement a network, engineers resort to wireless communication, or communication over dedicated power lines. Usually, one hub communicates with meters within the network (from several to hundreds of meters) using the power supply lines. The IEEE 802.15.4g standard is used for wireless communications; the IEEE P1901, OPEN meter and ITU-T G.hnem standards are used in cases where information is exchanged over power lines.


Utilities organizations use the home network to communicate with devices inside the home. The list of functions of this network includes disconnecting air conditioners during peak loads, displaying information about the volume of power consumption on home displays, and paying for utilities with cards. Communication protocols are being created to send information to charging systems for electric vehicles/hybrid cars, as this class of devices requires a special protocol for home networks.


Architecture of a communication channel in a smart network


Wireless communication networks



In addition to standardized protocols for the implementation of wireless transmission, there are a number of original (not approved as standard) protocols. The frequency range is 200 MHz to 3.9 GHz. Several blocks are used in the implementation. On the receiving side there is an antenna, which receives the signal. A bandpass filter clears the received signal of unnecessary frequencies. After cleaning, several downscalers on the receiving path convert the carrier frequency into an intermediate frequency (IF). Then signal processing blocks (baseband) are created, which are obtained from the in-phase/square (I/Q) stages. There are various ways of separating the system into separate stages. For example, when using ZigBee technology, the block is implemented with the help of crystal based systems. And in cases when developers use original protocols, the radio channel is built on a separate digital information system, made to order.



North America


WAN

Mobile networks, WiMAX


NAN

G3-PLC, HomePlug®, IEEE 802.15.4g, IEEE P1901, ITU-T G.hnem, original wireless, Wi-Fi


HAN

G3-PLC, HomePlug, ITU-T G.hn, Wi-Fi, ZigBee, Z-Wave



Europe


WAN

Mobile networks


NAN

G3-PLC, IEEE P1901, ITU-T G.hnem, PRIME, Wi-Fi


HAN

G3-PLC, HomePlug, ITU-T G.hn, Wi-Fi, Wireless M-Bus, ZigBee



China


WAN

Mobile networks, broadband, WiMAX


NAN

G3-PLC, RS-485, wireless protocols not yet defined


HAN

G3-PLC, RS-485, Wi-Fi, others not yet defined



Other countries


WAN

Mobile networks, WiMAX


NAN

G3-PLC, HomePlug, IEEE 802.15.4g, IEEE P1901, ITU-T G.hnem, PRIME, RS-485, Wi- Fi


HAN

G3-PLC, HomePlug, ITU-T G.hn, RS-485, Wi-Fi, Wireless M-Bus, ZigBee, Z-Wave


Communication on dedicated power lines



Systems on the PLC protocol exchange data on dedicated power lines. It is also possible to communicate via "cold" wire. Data exchange protocols on power lines are based on such basic modulation schemes as FSK (frequency manipulation) and multiplexing with orthogonal frequency division of channels (OFDM).


FSK is a modulation scheme used for purposes such as one-way transmission from the meter to the concentrator. Among the significant disadvantages of the FSK scheme is the loss of the signal from the receiver side when the interference frequency coincides with one of the transmission frequencies.


Thus, the communication speed is reduced, because the frequency manipulation switches between the two frequencies, which causes delays in the bandwidth. In the case where the system architecture involves a bidirectional communication channel (intelligent networks), frequency manipulation is unacceptable.


Often several hundred meters are connected to a single data concentrator over a high voltage network segment. For this reason, data must be exchanged via low/high voltage (LV/MV) transformers.


Typically these transformers can cause a signal attenuation of several tens of decibels (frequency selective attenuation). Modulation schemes such as OFDM are used to compensate for attenuation. Orthogonal frequency division multiplexing is used in communication systems such as digital radio and television, Wi-Fi and WiMAX networks, and in PRIME (one of the narrowband protocols of the first generation).


With OFDM, PLC networks can provide sufficient bandwidth for smart grids without additional equipment costs. The G3-PLC technology uses OFDM modulation to improve quality, as this modulation eliminates interference at a specific frequency and also prevents frequency selective attenuation by increasing the number of carriers. In this way, the reliability and volume of transmitted information is increased.


Solutions based on OFDM modulation use two levels of error-corrected coding - the Reed-Solomon Brief Encoding and the Reed-Solomon Coding.


Since impulse interference and packet errors can occur on the channel, the data are intermittent in the frequency and time areas of the OFDM carriers. Some security solutions on the MAC level use the AES-128 encryption mechanism, and to find the optimal path between network nodes - mesh routing (mesh routing protocol) [108]. Due to the high reliability of G3-PLC, communication on transformers takes place through an inexpensive connector. In this way it is possible to reduce the number of hubs, which makes this solution an affordable alternative to advanced wireless measurement infrastructures (AMI).


The communication channel distance over high and low voltage networks is 6 km, which allows monitoring even over long distances. At high noise levels, e.g. in apartment buildings, the RS-485 bus architecture is used so that it is less susceptible to external interference due to the differential transmission of signals on the channel.


This architecture also supports multi-point configurations, for connecting several meters to the same bus. Thus, based on this architecture, in apartment buildings the readings of apartment meters are transferred to the central unit, where the accumulated information is sent over a wireless channel or PLC lines. When transmitting data over short distances, the RS-232 protocol is used (e.g. when a meter is connected to a computer, modem or remote display at two points). If communication protocols are not known in advance, boards with the same layout are used for data exchange as for different protocols.



Measuring energy consumption



Power management in smart grids involves measuring both total consumption (whole building) and the load point (household appliances). Based on this data, utility companies offer customers discounts and different pricing rates. The term Power Usage Effectiveness - PUE is also used to measure the efficiency of the production infrastructure. This indicator is a ratio of total data center power consumption to equipment power consumption.


For this purpose, measurements are made at multiple points within the data centre. Microcontrollers, discrete circuitry, or crystal-based solutions can be used to measure power consumption.Among the serious disadvantages of general-purpose microcontrollers are low accuracy and narrow dynamic range, so when using microcontrollers are used 10, 12-bit ADC.


The use of discrete circuitry for measurement involves a significant number of additional components, as well as significant time for architecture development. ZigBee-based solutions allow you to capture data from an outlet (which indicates the time of measurement) and send the information over a wireless communication channel for further graphical analysis. When measuring currents from 10 mA to 20 A in the temperature range of -40°C +85°C, the error of the based systems is 0.5%.



Suppliers of intelligent energy metering and control systems


The largest suppliers of smart metering and control systems for electricity consumption are: Siemens AG, Techem GmbH (Germany), Enel SpA (Italy), PG&E (USA), Ontario Energy Board (Canada), ESC (Australia), Elektromed (Turkey), Energomera and Incotex (Russia). In particular, the Automative Smart Metering System from Siemens is designed to collect data from water, heat, gas and electricity meters with the transfer of information from devices via radio channel at 868 MHz to wireless hubs. It is estimated that the system is currently the cheapest and most advanced in the world.


Hubs automatically regulate the reading and transmission of information to the consumer. One hub has a modem in its device, which sends data to the client via GSM/GPRS network to the Internet address in the desired format. Hubs and components have power for 10 years. Gas and electric meters have special intelligent modules IFS data III for sending data via radio channels to the concentrators.


Smart counters from Enel SpA are electronic devices with built-in two-way communication capability, with improved counting and control mechanisms, with built-in software-controlled shutdown and rigid design. These meters send and receive data over a low-voltage electrical line using Echelon Corporation's own technology with Echelon Hubs, which in turn share IP protocol information with Enel's corporate servers.


The system provides extensive functionality, including the ability to turn on/off consumers remotely, read and monitor data collected by the meter over a period of time, emergency notification in case of emergency, detection of unauthorized use of electricity, regulation of the amount of electricity that the client can receive at a certain time, and remote change of tariff plans of the meter: from credit to prepaid, as well as from single to multi-tariff.



SCADA concept and Smart Grid system


Supervisory control and data acquisition (SCADA) is a software package used for supervisory control and data acquisition in real time and solving the following tasks:

  • Information exchange between the server (or computer) and industrial controllers in real time

  • Data Processing

  • Human Machine Interface, visualization of received data.

  • Alarm system

  • Process analysis

  • Connection with external DBMS

When using this system, the dispatcher receives data from the electronic display system and has the ability to manage remote objects through telecommunications systems or controllers.


Channel of communication between key SCADA components

Unlike Smart Grid, where the use of high-end metrology devices with a large amount of integrated internal memory allows for rapid reprogramming, and therefore requires certain skills from system developers, commercial SCADA solutions for creating application systems offer a ready-made set of solutions. If in certain conditions it saves time and resources, then in most cases this feature severely limits the functionality of the system. And in the conditions of rigid standards, (as for example standards of North America), possibility of reprogramming of system is critical, as the municipal organizations can need specific decisions. SCADA, as a rule, is a centralized solution that uses the control and management of a complex of systems, with the participation of a person. Information collection begins at the terminal controller level (RTU) in the form of meter readings. Then the information is formatted and the operator of the dispatching service makes decisions on the basis of the received data - to correct or interrupt the standard control of means.



In the Smart Grid, the voltage and current readings of different phases in power supply monitoring systems are monitored with the help of analog-to-digital converters. Typically, the digital signal processor calculates the power factor values from the measurements and evaluates the parameters of the system itself (active, reactive, total energy). The operator controls the system only for specific tasks.


In many cases, human control is the most reliable solution, as the conditions of the task often require nontrivial solutions. However, in power supply networks, where the control of entire settlements is carried out, the autonomous operation of the system and automatic interaction of components is the most appropriate approach. In this case, the advantages of Smart Grid, where the system architecture allows for data analysis and automatic troubleshooting, increase significantly.


SCADA-based systems are vulnerable to attack by attackers. When transmitting data over dedicated networks, Smart Grid power lines use the AES-128 encryption mechanism for security at the MAC level, and mesh routing (mesh routing protocol) to find the optimal path between network nodes. However, it cannot be claimed that Smart Grid is a more secure alternative to SCADA, as it is possible to secure both types of systems by observing common information security principles.


When creating automated power supply networks, cost is a key factor determining the economic efficiency of the solution. Smart Grid, being a more affordable alternative SCADA, provides metering, consumption monitoring and management via Internet, power line or cellular networks.


In power supply networks where monitoring, data exchange, meter data collection, load balancing, real time resource allocation are required, Smart Grid is the best solution. However, SCADA, as a powerful supervisory control tool, can be a supporting solution in some cases. In an integrated system, the capabilities of both systems will need to be combined.



Conclustion



Our research covered methods of information collection and analysis, communication protocols and features of technical implementation of the Smart Grid system.


The methods of data processing, mechanisms of automatic distribution of power supply network load and protocols of information exchange in Smart Grid, as well as the general scheme of utility services when using this system are considered.


Smart Grid uses data from smart meters that record energy consumption at different times of day and send the data to a server where the system interprets the information and uses it to distribute energy. The transmission environment and the amount of data sent/received define the type of communication technology and network protocols on each segment of the power network. For example, the IEEE 802.15.4g standard is applied in wireless communications; the IEEE P1901, OPEN meter and ITU-T G.hnem standards are applied in cases where information is sent over power lines. One of the protocols used for dispatching control within the power grid is CPQ, a network protocol operating on top of HTTP or HTTPS. The communication system supports three levels of activity: the lower level is for collecting information from sensors, the intermediate level is for data transmission server, and the upper level is for data storage and processing server (polling server).


Communication is carried out through the Internet, the local network of the enterprise or radio channels. Provision of uninterrupted communication between electricity consumers and the network is possible with the use of common data transfer protocols and a common application layer. CPQ, as one example, is a communication protocol that allows for real-time exchange of data between different levels, regardless of distance and differences in hardware.


Smart Grid provides automatic network load balancing. In the case of the same load in each of the three phases, the system is considered balanced, so there is no need for current through the neutral wire.


Voltage and current readings at different phases in the network monitoring systems are monitored by means of analogue-to-digital converters, which measure power, voltage and current parameters simultaneously at all three phases and on the neutral wire. The digital signal processor calculates the power factor values based on the measurement results and also evaluates the parameters of the system itself (active, reactive, total energy).


For data analysis, Smart Grid systems use both proprietary tools and third-party SaaS solutions. Based on the statistical data, the system calculates the minimum number of generators required at certain points in time, in order to eliminate redundancy in major stations. The statistics are used for early fault detection in the local AC/DC power supply module. In addition, the information can be used to obtain data on the nature of the load just connected to the mains.


During peak activity hours, the Smart Grid servers begin to inform customers (both individuals and businesses) about the amount of power consumed and peak activity time. Legal entities can directly control the devices to change consumption, while individuals are encouraged to choose the tariff conditions.


At peak loads as well as in emergency situations, customers can be powered by alternative energy sources. However, it should be noted that the excess energy stored in renewable energy sources cannot be redistributed due to topology peculiarities.


The integration of Smart Grid, SCADA and alternative energy monitoring systems is capable of performing network management, data exchange, energy consumption measurement, device control, monitoring, processing and visualization of RES data. The aggregate data can be used for analysis, distribution of resources of the power supply network, consumption forecasting and planning of the power supply system development.


Communication protocols in Smart Grids

 

References


  1. J. Torriti, Demand Side Management for the European Super grid // Energy Policy. – 2012. – Vol. 44. – P. 199–206.

  2. Smart Grid Working Group. Challenge and Opportunity: Charting a New Energy Future, Appendix A: Working Group Reports // Energy Future Coalition. – Washington, 2003. – P. 42-118.

  3. Smart Grid Working Group. Challenge and Opportunity: Charting a New Energy Future, Appendix A: Working Group Reports // Energy Future Coalition. – Washington, 2003. – P. 42-118.

  4. NETL Modern Grid Initiative — Powering Our 21st-Century Economy. United States Department of Energy Office of Electricity Delivery and Energy Reliability // National Energy Technology Laboratory. – 2007. – Vol. 8. – 17 p.

  5. SMART 2020: Enabling the Low Carbon Economy inthe Information Age // The Climate Group on behalf of the Global Sustainability Initiative. – Brussels, 2008. – 87 p.

  6. Enel // https://www.enel.com/en-gb: 2.04.2015

  7. NETL Modern Grid Initiative — Powering Our 21st-Century Economy. United States Department of Energy Office of Electricity Delivery and Energy Reliability // National Energy Technology Laboratory. – 2007. – Vol. 8. – 17 p.

  8. SMART 2020: Enabling the Low Carbon Economy inthe Information Age // The Climate Group on behalf of the Global Sustainability Initiative. – Brussels, 2008. – 87 p.

  9. Enel // https://www.enel.com/en-gb: 2.04.2015

  10. The History of Electrification: The Birth of our Power Grid // Edison Tech Center. –2013. – 15 p.

  11. Technology Roadmap. Energy Storage. - International Energy Agency, Paris, 2014. – 64 p.

  12. Berger Lars T. and Iniewski Krzysztof, ed. Smart Grid - Applications, Communications and Security. - John Wiley and Sons, 2012. – 488 p.

  13. Mohsen Fadaee Nejad, Amin Mohammad Saberian and Hashim Hizam. Application of smart power grid in developing countries" // 7th International Power Engineering and Optimization Conference (PEOCO). – Langkawi, 2013. – P. 427-431.

  14. Khan, R.H.; Khan, J.Y. A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network // Comput. Netw. – 2013. – Vol. 57. - P. 825–845.

  15. Della Giustina, D.; Andersson, L.; Casirati, C.; Zanini, S.; Cremaschini, L. Testing the Broadband Power Line Communication for the Distribution GridManagement in a Real Operational Environment // Proceedings of the International Symposium on Electronics, Electrical Drives, Automation and Motion. – Sorrento, 2012. – P. 785–789.

  16. 105 Machine-to-Machine communications (M2M); Applicability of M2M architecture to Smart Grid Networks; Impact of Smart Grids on M2M platform. - ETSI TR 102 935 v2.1.1. – 2012. -Vol. 9. – 58 p.

  17. Della Giustina, D.; Andersson, L.; Casirati, C.; Zanini, S.; Cremaschini, L. Testing the Broadband Power Line Communication for the Distribution GridManagement in a Real Operational Environment // Proceedings of the International Symposium on Electronics, Electrical Drives, Automation and Motion. – Sorrento, 2012. – P. 785–789.

  18. 105 Machine-to-Machine communications (M2M); Applicability of M2M architecture to Smart Grid Networks; Impact of Smart Grids on M2M platform. - ETSI TR 102 935 v2.1.1. – 2012. -Vol. 9. – 58 p.

  19. European Technology Platform. Strategic Deployment Document for European Electricity Networks of the Future. - Smart Grids, 2010. – 69 p.

  20. George W. Arnold. NIST Interoperability Framework for the Smart Grid. - National Institute of Standards and Technology, 2015. – 6 p.

  21. J. Torriti, Demand Side Management for the European Super grid // Energy Policy. – 2012. – Vol. 44. – P. 199–206.

  22. Smart Grid Working Group. Challenge and Opportunity: Charting a New Energy Future, Appendix A: Working Group Reports // Energy Future Coalition. – Washington, 2003. – P. 42-118.

  23. NETL Modern Grid Initiative — Powering Our 21st-Century Economy. United States Department of Energy Office of Electricity Delivery and Energy Reliability // National Energy Technology Laboratory. – 2007. – Vol. 8. – 17 p.

  24. SMART 2020: Enabling the Low Carbon Economy inthe Information Age // The Climate Group on behalf of the Global Sustainability Initiative. – Brussels, 2008. – 87 p.

  25. Enel // https://www.enel.com/en-gb: 2.04.2015

  26. The History of Electrification: The Birth of our Power Grid // Edison Tech Center. –2013. – 15 p.

  27. Technology Roadmap. Energy Storage. - International Energy Agency, Paris, 2014. – 64 p.

  28. Standardization Mandate to European Standardisation Organisations to Support European Smart Grid Deployment // European Commission, Directorate-General for Energy, Smart Grid Mandate. – Brussels, 2011. – P.18-38.

  29. Berger Lars T. and Iniewski Krzysztof, ed. Smart Grid - Applications, Communications and Security. - John Wiley and Sons, 2012. – 488 p.

  30. Mohsen Fadaee Nejad, Amin Mohammad Saberian and Hashim Hizam. Application of smart power grid in developing countries" // 7th International Power Engineering and Optimization Conference (PEOCO). – Langkawi, 2013. – P. 427-431.

  31. Khan, R.H.; Khan, J.Y. A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network // Comput. Netw. – 2013. – Vol. 57. - P. 825–845.

  32. Della Giustina, D.; Andersson, L.; Casirati, C.; Zanini, S.; Cremaschini, L. Testing the Broadband Power Line Communication for the Distribution GridManagement in a Real Operational Environment // Proceedings of the International Symposium on Electronics, Electrical Drives, Automation and Motion. – Sorrento, 2012. – P. 785–789.

  33. Machine-to-Machine communications (M2M); Applicability of M2M architecture to Smart Grid Networks; Impact of Smart Grids on M2M platform. - ETSI TR 102 935 v2.1.1. – 2012. -Vol. 9. – 58 p.

  34. European Technology Platform. Strategic Deployment Document for European Electricity Networks of the Future. - Smart Grids, 2010. – 69 p.

  35. George W. Arnold. NIST Interoperability Framework for the Smart Grid. - National Institute of Standards and Technology, 2015. – 6 p.

  36. C. F. Covrig, M. Ardelean, J. Vasiljevska, A. Mengolini, G. Fulli and E. Amoiralis, Smart Grid Projects Outlook 2014 // Technical report. - European Commission. Joint Research Centre, 2014. – P. 11-158.

  37. Vincenzo Giordano, Julija Vasilevska, Silvia Vitello. Evaluation of Smart Grid Projects within the Smart grid Task Force Expert Group 4 // Technical report. - European Commission. Joint Research Centre, 2013. – P. 1-53.

  38. J. Torriti, Demand Side Management for the European Super grid // Energy Policy. – 2012. – Vol. 44. – P. 199–206.

  39. Smart Grid Working Group. Challenge and Opportunity: Charting a New Energy Future, Appendix A: Working Group Reports // Energy Future Coalition. – Washington, 2003. – P. 42-118.

  40. NETL Modern Grid Initiative — Powering Our 21st-Century Economy. United States Department of Energy Office of Electricity Delivery and Energy Reliability // National Energy Technology Laboratory. – 2007. – Vol. 8. – 17 p.

  41. SMART 2020: Enabling the Low Carbon Economy inthe Information Age // The Climate Group on behalf of the Global Sustainability Initiative. – Brussels, 2008. – 87 p.

  42. Enel // https://www.enel.com/en-gb: 2.04.2015

  43. The History of Electrification: The Birth of our Power Grid // Edison Tech Center. –2013. – 15 p.

  44. Technology Roadmap. Energy Storage. - International Energy Agency, Paris, 2014. – 64 p.

  45. Standardization Mandate to European Standardisation Organisations to Support European Smart Grid Deployment // European Commission, Directorate-General for Energy, Smart Grid Mandate. – Brussels, 2011. – P.18-38.

  46. Berger Lars T. and Iniewski Krzysztof, ed. Smart Grid - Applications, Communications and Security. - John Wiley and Sons, 2012. – 488 p.

  47. Mohsen Fadaee Nejad, Amin Mohammad Saberian and Hashim Hizam. Application of smart power grid in developing countries" // 7th International Power Engineering and Optimization Conference (PEOCO). – Langkawi, 2013. – P. 427-431.

  48. Khan, R.H.; Khan, J.Y. A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network // Comput. Netw. – 2013. – Vol. 57. - P. 825–845.

  49. Della Giustina, D.; Andersson, L.; Casirati, C.; Zanini, S.; Cremaschini, L. Testing the Broadband Power Line Communication for the Distribution GridManagement in a Real Operational Environment // Proceedings of the International Symposium on Electronics, Electrical Drives, Automation and Motion. – Sorrento, 2012. – P. 785–789.

  50. Machine-to-Machine communications (M2M); Applicability of M2M architecture to Smart Grid Networks; Impact of Smart Grids on M2M platform. - ETSI TR 102 935 v2.1.1. – 2012. -Vol. 9. – 58 p.

  51. European Technology Platform. Strategic Deployment Document for European Electricity Networks of the Future. - Smart Grids, 2010. – 69 p.

  52. George W. Arnold. NIST Interoperability Framework for the Smart Grid. - National Institute of Standards and Technology, 2015. – 6 p.

  53. C. F. Covrig, M. Ardelean, J. Vasiljevska, A. Mengolini, G. Fulli and E. Amoiralis, Smart Grid Projects Outlook 2014 // Technical report. - European Commission. Joint Research Centre, 2014. – P. 11-158.

  54. Vincenzo Giordano, Julija Vasilevska, Silvia Vitello. Evaluation of Smart Grid Projects within the Smart grid Task Force Expert Group 4 // Technical report. - European Commission. Joint Research Centre, 2013. – P. 1-53.

  55. Advanced Energy Technologies for Greenhouse Gas Reduction // Report. - Advanced Energy Economy. – 2014. – P. 1-48.

  56. Stuart A. Boyer,. SCADA Supervisory Control and Data Acquisition. 3nd Edition. – ISA, 1999. – 204 p.

  57. Guide to Supervisory Control and Data Acquisition (SCADA) and Industrial Control Systems Security. - National Institute of Standards and Technology, 2003. – 164 p.


135 views1 comment
bottom of page