Gevork B. Gharehpetian⁎; Mehdi Salay Naderi⁎; Hadi Modaghegh†; Alireza Zakariazadeh‡ ⁎ Amirkabir University of Technology, Tehran, Iran
† Ministry of Energy, Tehran, Iran
‡ University of Science and Technology of Mazandaran, Behshahr, Iran
This chapter is composed of two major sections: Smart Grid Technology Roadmap in Iran and National Smart Metering Program (FAHAM). The first section is develops the Iran smart grid roadmap project, which is one of the subprojects of the Iran Smart Grid National Grand Project. The roadmap focuses on technology development. Also, the smart meter program in, Iran is comprised of state-of-the-art electronic/digital hardware and software that combines interval data measurement with continuously available remote communications. In this chapter, the goals and benefits of FAHAM are described. Regarding the pilot project, the components and interfaces as well as the communication architecture of advanced metering infrastructure is presented. Also, the layer model of the FAHAM project has been analyzed. The wireless cellular network, especially General Packet Radio Service, is seen by FAHAM for communication within smart grids and utilities. The pilot project showed that the installation of a smart meter system brings on a new set of challenges for the organizations that operate and maintain the utility's legacy processes.
Iran smart grid; National Smart Metering System Project (FAHAM); Roadmap; Technology development
Abbreviations
AMI advanced metering infrastructure
CAS central access system
CIS Customer Information System
DA distribution automation
DC data concentrator
DER distributed energy resources
DMS distribution management system
DR demand response
EC European Commission
EMS energy management system
FA feeder automation
FAHAM National Smart Metering Program in Iran
GIS geographic information system
GPRS General Packet Radio Service
HVDC high voltage direct current
IEA International Energy Agency
IEC International Electro Technical Commission
ISGC Iran Smart Grid Company
JRC Joint Research Center (of EU Commission)
MDM meter data management
NOC Network Operation Center
OMS outage management system
PLC power line carrier
SCADA supervisory control and data acquisition
SG smart grid
SOC Security Operation Center
VVC volt-var control
WAMS wide area monitoring systems
UML unified modeling language
Smart grid development in different countries is affected by six major drivers:
In Iran, the mentioned drivers motivate technology development and the implementation of smart grids with different degrees of importance. To develop the technology development roadmap of the Iran smart grid, we first need to recognize the details of smart grid technology and then select a reliable reference among numerous references to maintain the consistency and integrity of the programs and actions in the roadmap.
For this purpose, the European Union (EU) has defined a smart grid platform. Most European countries have used this reference for their smart grid development programs. Also, it is possible for different countries with diverse economies, technology, and social circumstances to use this methodology. Its information is available and provides the ability to compare the countries.
This document is prepared to accomplish the Iran smart grid roadmap project, which is one of the projects of the Iran Smart Grid National Grand Project. This roadmap focuses on the technology development; the deployment roadmap should be written as well.
To prepare the technology development roadmap of the Iran smart grid, two recommended documents of the EU commission have been used:
To prepare the technology development roadmap of the Iran smart grid, the first smart grid and its technologies and areas are investigated. Then, the Iran smart grid vision was outlined according to expert opinions and upstream national documents in the smart grid field as well as comparative studies. Based on this vision, policies, actions, strategies and, finally, the technology development roadmap are extracted.
The technology development roadmap contains three parts: the development approach, prioritizing technologies, and determining the technology acquisition method. Considering the variety of smart grid technologies, the International Energy Agency (IEA) standard has been used to categorize smart grid technologies. Based on this standard, smart grid technologies are categorized into eight groups. Fig. 1 demonstrates the technology groups of smart grids in different domains of the SGAM standard. For each IEA category, the development approach and method of technology acquisition have been extracted separately.
Subgroups of each technology area in the IEA standard in hardware, software, and systems sections are expressed in Table 1 in detail.
Table 1
Technology area | Hardware | Systems and software |
---|---|---|
Wide-area monitoring and control | Sensor equipment, phasor measurement units (PMU) | Supervisory control and data acquisition (SCADA), wide area monitoring systems (WAMS), control and automation (WAAPCA), wide area adaptive protection, wide area situational awareness (WASA) |
Information and communication technology integration | Communication equipment (power line carrier, WIMAX, LTE, RF mesh network, cellular), routers, relays, switches, gateway, computers (servers) | Enterprise resource planning software (ERP), customer information system (CIS) |
Renewable and distributed generation integration | Power conditioning equipment for bulk power and grid support, communication and control hardware for generation and enabling storage technology | SCADA, geographic information system (GIS), energy management system (EMS), distribution management system (DMS) |
Transmission enhancement | Superconductors, FACTS, high-voltage direct current (HVDC) | Network stability analysis, automatic recovery systems |
Distribution grid management | Automated reclosers, switches and capacitors, remote-controlled distributed generation and storage, transformer sensors, wire and cable sensors | Geographic information system (GIS), DMS, outage management system (OMS), workforce management system (WMS) |
Advanced metering infrastructure | Smart meter, in-home displays, servers, relays | Meter data management system (MDMS) |
Electric vehicle charging infrastructure | Charging infrastructure, batteries, inverters | Smart grid-to-vehicle charging (G2V) and discharging vehicle-to-grid (V2G) methodologies, energy billing |
Customer-side systems | Smart appliances, routers, in-home display, building automation systems, thermal accumulators, smart thermostat | Energy dashboards, EMS, energy applications for smart phones and tablets |
Prioritization of technologies for each IEA group has been performed based on an attractiveness-capability matrix as well as the opinions of experts. To obtain the attractiveness-capability matrix for all smart grid technologies, a structured questionnaire form has been prepared with two sections. In the first section, the maturity level of each technology in nine levels was asked; in the second section, the attractiveness of technologies considering seven criteria was investigated. These criteria are employment, number of competitors, new markets, added value, a key technology, application in other industries, and the position in the life cycle of technology. Then the attractiveness-capability matrix was extracted.
In terms of time, the attractiveness-capability matrix is divided into three groups. According to the position of each technology in the attractiveness-capability matrix, the priority of development in short, mid and long-term periods can be determined in Fig. 2 for each technology. Fig. 3 shows the IEA standard groups position in the attractiveness-capability matrix for Iran.
Based on the basic features of the Iran smart grid technologies groups (according to the IEA standard and SGAM method), the appropriate method of technology acquisition for each group has been determined. Among a number of valid traditional methods for technology acquisition, the Chiesa (1998) and Narula (2001) methods have been selected. The accuracy and widespread use of these methods were the reasons of this selection. To apply these methods, expert opinions have been collected and analyzed by using a detailed questionnaire form. Comparing the results of these two methods makes the technology acquisition method reliable for each technology.
To obtain a technology development policy, Technology Innovation System (TIS) and Multilevel Perspective models have been employed. Using event logging, measures in the eight IEA standard groups have been analyzed from the TIS perspective. In order to develop more effective actions and strategies in the smart grid roadmap, it is necessary to investigate and classify the players of the Iran smart grid. Fig. 4 represents Iran smart grid players and their relationships in the smart grid ecosystem.
To prepare the roadmap, all the lessons learned in comparative studies, background or benchmarking studies, frameworks, validated methodologies, and upstream national documents and drivers have been used to compile the Iran smart grid road map. Fig. 5 shows the stages of technology and the business development road map of the Iran smart grid.
Fig. 6 shows the fundamental components of the Iran smart grid technology development roadmap. The methodology and components of the roadmap are based on legislation approved in the 18th Supreme Council for Science Research and Technology meeting in January 2016. In the next sections, details of the Iran smart grid technology development roadmap will be described.
Iran smart grid policy-making values are based on the following principles:
By 2025, the Islamic Republic of Iran aims to develop an electric smart grid as an efficient, secure, flexible and stable grid that delivers required high quality and reliable power to consumers and stakeholders. ICT, smart management systems, new technologies in the area of smart grids, IoT and integration of DGs, CHP systems, renewable energy resources, and energy storage systems cause dynamic interactions between stakeholders of the whole energy system. The smart grid provides optimal management of demand and supply in a competitive electricity market. Iran seeks to elevate and consolidate their position as the first country in the Middle East in technology development and the implementation of a smart grid.
The macro policies of the Iran smart grid technology development are as follows:
According to the vision of the Iran smart grid and its technology development and considering upstream documents, the goals of the Iran smart grid technology development are listed below:
Table 2 presents actions and strategies to achieve expected deliveries and outputs corresponding to the funds allocated to different areas of smart grid technology development. It has two columns representing deliveries and outputs corresponding to the funds supported by Iran's Electric Smart Grid National Grand Project (IESGNGP) and other resources.
Table 2
Total financial resources required for implementing smart grid technology development in a short period (3 years) is $155 million. This budget is allocated to achieve the goals expressed in the national Iranian smart grid roadmap. The budget resources are:
Table 3 presents the various areas of the Iran smart grid technology development road map and the funds allocated to each area. The table lists the allocated funds supplied from each resource mentioned above. In order to meet the goals and vision of the plan in 10 years, the resources for mid- and long-term periods should be revised considering the short-term results.
Table 3
No. | Areas of measure for Iran smart grid technology development | Iran's Electric Smart Grid National Grand Project (IESGNGP) budget ($ million) | Other resources ($ million) |
---|---|---|---|
1 | Smart meter development and related technologies | 0.6 | 6.5 |
2 | Customer side technology development | 1.4 | 12 |
3 | ICT infrastructures technology development | 1.1 | 3.5 |
4 | Smart grid technology development (distribution and transmission systems) | 2.7 | 3.5 |
5 | WAMS development | 1.4 | 5.5 |
6 | Grid monitoring and control technology development | 2.1 | 9.2 |
7 | Grid protection systems development | 1.4 | 2.5 |
8 | DGs and renewable energy resources integration infrastructure development | 1.4 | 6.5 |
9 | Electric vehicle infrastructure and new technology development | 1.4 | 5.3 |
10 | Knowledge-based start-up businesses development support | 5.2 | 17 |
11 | Human resources education and training | 1.4 | 4 |
12 | Obtaining technology development infrastructure and smart grid lab development | 1.4 | 6.5 |
13 | Culture making and promotion of smart grid applications | 0.8 | 6 |
14 | Implementation of pilot projects | 2.7 | 42 |
Total budget | 25 | 130 |
In this section, the updating and evaluation mechanisms for smart grid technology development are presented. To do this, two evaluation methods are used: evaluation indices and evaluation reports, which are described.
In Table 4, evaluation indices of research and development programs have been collected based on similar domestic and international literature and documents. In this table, evaluation indices are divided into several groups considering their domain. The name of the group and the indices of each group are defined in Table 4.
Table 4
No. | Index | Domain |
---|---|---|
1 | Percentage of academic staff working as leaders of the smart grid research project | Human resource |
2 | Percentage of postgraduate students studying in the smart grid field | |
3 | Number of visiting professors participating in conferences and workshops held in Iran or publishing joint papers | |
4 | Number of universities or research centers that are active in at least five smart grid projects | Research centers |
5 | Number of universities and research centers that are ranked among the top 10% best research centers or universities | |
6 | Number of ISI-ranked published papers | Scientific productions |
7 | Mean citation of each ISI-ranked paper | |
8 | Iranian researchers’ share from total published papers worldwide | |
9 | Number of highly cited papers | |
10 | Number of patents registered within Iran | Technology development |
11 | Number of patents registered outside Iran | |
12 | Commercialization of plans | Commercialization and industry |
13 | Percentage of yearly growth of GDP per capita due to smart grid science and technology | |
14 | Share of generation of products and services in GDP obtained from domestic knowledge and technology | |
15 | Share of value added by industrial products from national production value added | |
16 | Amount of domestic technology production | |
17 | Number of businesses with at least 1 product/service | |
18 | Key player interactions (cofinancing, research and development by public and private sectors, cooperation in R&D projects, participating in local and national scientific and technology programs, outsourcing, participation in registration of patents and publications) | Increasing key player interactions |
19 | Signing contracts | |
20 | Share of nongovernmental sector in financing research costs | Financial costs |
21 | Research expenditures share in GDP | |
22 | Education costs share in GDP | |
23 | Income absorption | Financial advantageous |
24 | Organizational incentives (e.g., sharing commercialization income among research groups and universities, a credit and promotion system, industrial incentives for innovative plans) | |
25 | Ability to attract research funds, venture capital, and university capital as well as university-based companies | |
26 | License income, copyright and registration rights, research income, tax income, legal costs | |
27 | Earned value of development projects |
The other evaluation method of smart grid technology development is based on reports that are generated by different committees and organizations. In this section, the subject of the reports and their descriptions are presented.
In the development of the Iran smart grid road map, the JRC methodology has been selected as the analyzing method. Based on the JRC methodology, countries that intend to implement smart grids are required to adopt 10 functionalities in their smart grid. To achieve the stated functionalities, it is necessary to determine the assets of the present electricity grid. To identify the priorities and assets of the Iran power electricity network, experts’ viewpoints from industries and universities have been collected using designed forms. Fig. 7 demonstrates the diagram of the Iran electric network priorities, which have been obtained by analyzing the received forms.
Considering the EU requirements and assets and priorities of the Iran smart grid, the deployment of the smart grid is divided into four pillars: customer empowerment, market development, grid development, and governmental institutions. Table 5 presents the pillars of smart grid development, the baseline of the Iran grid and the measures that will be taken through 2020 and 2025.
Table 5
Pillar | Base line | Up to 2020 | Up to 2025 |
---|---|---|---|
Customer empowerment | AMI Telecommunication CIS DR | AMI CIS Smart grid (pilot) Smart home (pilot) Storage systems | Smart city Smart home |
Market development | Tariff definition Tariff diversification Electricity retailers | Privatization sector Smart operators | |
Grid development | WAMS SCADA (transmission) | WAMS Street lightening OMS GIS Volt-Var control (VVC) Asset management system Distribution automation (DA)/feeder automation (FA) Security Operation Center (SOC)/Network Operation Center (NOC) Microgrid (pilot) Integration of distributed energy resources (DER) | HVDC DMS EMS Development and integration of microgrids EV charging infrastructure |
Governmental institutions | SG Steering Committee Renewable energy feed in tariff SG regulatory body AMI mandate | Standard definition Iran Smart Grid Company (ISGC) Instructions and regulations completion |
Iran is located in the Middle East and, as of 2016, has a total population of more than 80 million. More than 99% of the country's population has access to electricity. The power-generation capacity of the Iran grid is more than 76 GW.
In Fig. 8, the percentage of electricity customers in each section has been illustrated. From the 34 million customers of the Iran grid, 35% and 32% are industrial and residential users, respectively. Also, the remaining 16%, 9%, 6%, and 2% are agricultural, public loads, commercial, and lighting, respectively.
Advanced metering infrastructure (AMI) systems are comprised of state-of-the-art electronic/digital hardware and software that combine interval data measurement with continuously available remote communications. AMI gives the system operator and consumers the information they need to make smart decisions, and also the ability to execute those decisions that they are not currently able to do. Implementation and deployment of the National Smart Metering System project (called FAHAM) in Iran was begun in 2009. The FAHAM project follows promoting energy efficiency and load management, improving system reliability, and reducing operational costs by implementing the smart meter project. Moreover, the FAHAM project plans to replace conventional customer meters with smart meters in order to give consumers greater control over their energy use. Smart meters enable a utility to provide customers with detailed information about their energy usage at different times of the day, which in turn enables customers to manage their energy use more proactively.
In 2009, the Iran Energy Efficiency Organization (IEEO) published the roadmap for smart grid roll-out in Iran, illustrated in Fig. 9. As shown, the first steps were scheduled for implementation and deployment of the AMI.
To rollout the pilot project, five areas were selected as the main priority. Zanjan, Bushehr, Mashhad, Ahwaz, and Tehran + Alborz are the first distribution companies that will execute bulk rollout. Considering FAHAM action plans for Tehran + Alborz, it should be noted that distribution substations, lighting feeders, loss monitoring purposes, and large and demand customers have been included in the plan. For the other areas, the residential customers have also been included in FAHAM.
Moreover, 300,000 m for large customers (demand customers) in all 39 distribution companies (all around the country) will be connected to FAHAM in parallel with the aforementioned rollout plans. More details about the FAHAM pilot action plan are shown in Fig. 10.
At the conclusion of FAHAM, all 34 million customers of the Iran grid, all distribution substations, and all feeders will be included in the metering infrastructure.
The aims of AMI implementation in Iran are given below; they should include a plan for achieving each goal.
Smart grid development in Iran has several advantages, which are summarized in three areas: economic, social, and environmental benefits:
Economic benefits
Social benefits
Environmental benefits
The AMI system in the FAHAM project typically refers to the full measurement and collection system that includes meters at the customer site; communication networks between the customer and a service provider, such as an electric, gas, or water utility; and data reception and management systems that make the information available to the service provider. Fig. 11 shows a typical distribution system including AMI. Data can be provided at the customer level and for other enterprise-level systems either on a scheduled basis or on demand. FAHAM will communicate this data to a central location, sorting and analyzing it for a variety of purposes such as customer billing, outage response, system loading conditions, and demand-side management. FAHAM as a two-way communication network will also send this information to other systems, customers, and third parties as well as send information back through the network and meters to capture additional data, control equipment, and update the configuration and software of equipment. Components and interfaces forming the AMI system in the FAHAM project are illustrated in Fig. 12. The main components are described in the following:
The communications solutions deployed in the FAHAM project have to fulfill a set of requirements in order to confirm the economic viability as well as functional reliability of the whole system. The selected communication systems between AMI components shown in Fig. 12 are described as follows:
This interface is between the electricity meter/communication hub, and the concentrator, located, for example, in an electrical MV/LV substation. The protocol architecture is shown in Fig. 13.
For this interface, two power line carrier (PLC) technologies, both working in the CENELEC A band, have been selected:
MI2-SI2 is the interface directly linking the electricity meter with the CAS. Due to cost constraints, this will usually be cellular. If a large number of nodes are installed using the network of a telecom provider, operation costs may become significant. In this case, data exchange with the meter has to be kept to a minimum.
A large number of nodes to be managed by the CAS imply this interface does not usually have high bandwidths from the electricity meter perspective. GPRS (General Packet Radio Service)/UMTS (Universal Mobile Telecommunications System) wireless technology was considered to be the most suitable technology for this interface. A protocol architecture will be studied for DLMS/COSEM. Fig. 14 illustrates this interface communication architecture.
GPRS is a mobile data service offered in GSM systems, in addition to GSM service (it is integrated into GSM Release 97 and newer releases). It was originally standardized by the European Telecommunications Standards Institute (ETSI) and now by the 3rd Generation Partnership Project (3GPP). It is nowadays globally available in nearly all countries (except South Korea and Japan). In general terms, GPRS coverage is readily available in populated areas in most countries.
GPRS is widely used in IP networks today as a WAN wireless (cellular) technology. Each GPRS subscriber obtains an IP address, which can be public or private and at the same time fixed or dynamic, depending on the contracted service features and operator capabilities. GPRS service is provided in the GSM licensed frequency bands of 800, 900, 1800, and 1900 MHz.
The GPRS Access network is divided into two sections:
An electricity meter would function as an MS (Mobile Station) from a GPRS perspective.
UMTS, also known as 3G or third generation mobile technology, is an evolution of existing 2G/GPRS networks using WCDMA modulation techniques in the air interface. It is specified by 3GPP and is part of the global ITU IMT-2000 standard. There have been different releases of UMTS issued by 3GPP. The UMTS lower layer networks are owned by the mobile operator. This network can be further subdivided into two different sections:
Two protocol profiles are proposed: A new highly scalable solution based on SNMPv3 plus secure file transfer protocol and a web services-based profile.
The interface CI3 is used to connect the concentrator to external devices (e.g., sensors that are located in a relatively short radius around the concentrator, power meters, etc.). PLC is not considered as an optimal solution from both installation and component perspectives. Some studies propose wireless as a good alternative; the preferred data model and application layer (IEC 61850) is currently extensively used over wired ethernet, and this is currently considered a good compromise solution for most applications. Given that the concept of an external device is not fully defined in the scope of AMI projects, the profile proposed here should not be considered as exhaustive.
In Table 6, profiles for the multiutility meter communications interface MI3 are proposed.
Table 6
Short name | Physical medium | Physical layer | Link layer | Application layer |
---|---|---|---|---|
M-bus TP | Twisted pair base band signaling | EN 13757-2 | EN 13757-2 | M-bus dedicated application layer EN13757-3 + IEC 62056-53 DLMS/COSEM |
M-bus TP DLMS/COSEM | Twisted pair | EN 13757-2 | IEC 62056-46 HDLC | IEC 62056-53 DLMS/COSEM |
Wireless M-bus | Radio 886 MHz | EN 13757-4 various modes | EN 13757-4 | M-bus dedicated application layer EN13757-3 + IEC 62056-53 DLMS/COSEM |
IEEE 802.15.4 radio | Radio 886 MHz or 2, 4 GHz | IEEE 802.15.4 | IEEE 802.15.4 | IEC 62056-53 DLMS/COSEM |
ZigBee DLMS/COSEM tunneling | Radio 886 MHz or 2, 4 GHz | IEEE 802.15.4 | IEEE 802.15.4 | IEC 62056-53 DLMS/COSEM |
The twisted pair profiles are proposed additionally to suggest communication assessment because of the following advantages for multiutility meters:
There is a suggestion for the use of IEEE 802.11 (WiFi); this is not considered here. The main reason for this is the fundamental requirement of “low-power” for multiutility meters, which is deemed impossible to fulfill with the current IEEE 802.11.
List of standards that must be taking into account for FAHAM deployment are given in reference [1–31].
In the layer model, five layers are defined within the AMI system, illustrated in Fig. 15. These layers are described as follows:
The first layer is the physical layer related to smart meters that are located in customers’ places.
The second layer is AHE software as communications servers that are charged with the task of communicating with smart meters. These devices are different for different meter manufacturers. The diversity of AHE is dependent on a variety of meter manufacturers.
The third layer, meter data management (MDM), is responsible for collecting and managing data from AHE. The task of the layer is to match information in the same format used for other operational surfaces.
The fourth layer pertains to operational and commercial software that provides required statistical data and information for users by received information from MDM.
The fifth layer is distribution companies, which are responsible for information management in order to service the customers based on the business process.
ICT architecture in FAHAM project is depicted in Fig. 16. The communications and information transactions between different parts are described as follows:
Interoperability can be defined as the ability of systems, components, or equipment to provide services to and accept services from other systems, components, or equipment and to use the services exchanged to enable them to operate effectively together. With respect to software, the term is also used to describe the capability of different programs to exchange data via a common set of exchange formats, to read and write the same file formats, and to use the same protocols.
If two or more systems are capable of communicating and exchanging data, they are exhibiting syntactic interoperability.
Interoperability is the ability to automatically interpret the information exchanged meaningfully and accurately in order to produce useful results as defined by the end users of both systems. To achieve semantic interoperability, both sides must defer to a common information exchange reference model. The content of the information exchange requests is unambiguously defined: what is sent is the same as what is understood.
Interoperability can have important economic consequences. If competitors’ products are not interoperable (due to causes such as patents, trade secrets, or coordination failures), the result may well be monopoly or market failure.
Smart metering communication systems should be based on standard metering protocols to confirm interoperability with changing energy supplier equipment and/or consumer equipment over the life of the meter.
Interoperability in the FAHAM system means that meters from different manufacturers should be able to work with all various types of concentrators made by other manufacturers. Every operation and maintenance device can connect to different types of meters and concentrators and CAS can manage all FAHAM devices regardless of their manufacturers. All these mentioned items shall be fulfilled without any additional devices or protocol convertors and without interfering in system online operation.
When two-way command and control systems are embedded into power systems, several security threats must be addressed:
Security is everywhere in the metering process, from the meter and the DC to the back-office information system, including each network and media used to communicate (home network, public network, and enterprise network). Also, all components are concerned and we need to handle global security. All partners, from manufacturers to suppliers and regulators have to work together to raise awareness and secure future metering systems.
The FAHAM system should prevent:
Identified requirements to complete these needs are:
A use case is a term in software and system engineering that defines how a user uses a system to accomplish a particular goal. Use cases describe interactions among external actors and the system to attain particular goals. Use cases are modeled by means of a unified modeling language (UML) and are represented by ovals containing the names of the use case.
This part provides the business use cases for electricity meters installed at the premises of domestic customers. In this section, “meter” refers to the electricity meter/communication hub. The procedure of each desired application of the AMI system is defined as a use case. These use cases are as follows:
Some of these use cases are described in the following:
This use case describes the process of gathering and providing periodic meter reads. This process is triggered after the installation of the electricity meter. Periodic meter readings are daily and monthly meter readings. Daily meter readings are used in power market issues such as real-time pricing. The trigger description and block diagram are depicted in Fig. 17.
Legacy systems assign the task of obtaining cycle meter readings to the central system. Meter reading requests are linked to a deadline date for acquiring the reading of the meters involved. Deadline dates are fixed by legacy systems according to legal, technical, or business requirements.
In order to acquire the most recent energy values, the central system could request the direct reading of the meters involved via the concentrator (communication via SI2-MI2). For those meters whose reading is not available in time, the last value stored on the system could be provided. Thus, the central system or concentrators should periodically retrieve and store meter readings.
This use case provides the description of the process of making the load profile available to the CAS. The load profile is made available through the electricity meter (both load profiles for electricity and gas). The process of registering the load profile (after sending the activation comment from the application layer) is an uninterrupted process that runs throughout the lifecycle of the metering equipment. This process is hence triggered after the installation of the electricity meter. The trigger description, block diagram, and UML sequence diagram are depicted in Fig. 18.
The load profile provides a measurement of the variation in the electrical load versus time. It represents the pattern of electricity usage of a customer. This information can also be used for billing.
Meters shall have the capability of registering load profiles. The number and length of the load profiles registered by the meter shall accomplish the current legal directives.
The CAS shall be able to order the activation of the load profile storage in the meter (if it is not active by default) as well as the programming of the parameters that define the load profiles (i.e., magnitude and periodicity). These orders shall be remotely managed by the CAS, which communicates with meters directly (communication via SI2-MI2) or through a concentrator communication via SI1-CI2 and CI1-MI2).
In addition, the CAS shall periodically gather and store these load profiles in order to provide this information to the legacy systems when required. The gathering of the load profile data by the CAS can be done directly (communication via SI2-MI2) or aided by a concentrator (communication via SI1-CI1-CI2-MI1).
The CAS shall deliver load profiles at the request of the legacy systems.
This use case describes the process of gathering power quality measurements in the CAS. Some indices are defined to measure the power quality of systems ; for example, the number of occurred over-voltage, dip voltage and harmonics. The trigger description, block diagram, and UML sequence diagram are depicted in the following diagrams. The power quality parameters in addition to the voltage parameters for the CT/PT meter are harmonic and THD.
The grid company should guarantee its customers a user-specified quality electricity supply, based on current legal regulations. Due to the aforementioned requirements, meters should register measurements related to interruption and variation voltage. Subsequently, the CAS periodically retrieves this information by means of an on-demand reading to send it to the legacy systems responsible for managing this information.
This use case describes the process to register and provide the customer with standard information related to the interruptions. In this standard, the duration (T) for short and long interruptions has been defined as 3 min, to differentiate between short and long interruptions. In the future, this definition might change. Therefore, it is required that T is configurable. The meter will be able to detect any interruptions and register the related information to be shown to the customer on the meter display or to be sent to end customer devices. The meter will be able to collect this set of information for different interruption events.
This use case describes the activities associated with tampering. Attempts to violate (parts of) the metering installation or the removal of the meter cover must be detected and registered with a time stamp; this detection applies for both the electricity meter and the gas and water meter. Further, fraud attempts using magnetic fields must be registered in the metering equipment. The metering installation must be able to register at least the last 10 fraud attempts for each tampering. Tamper detection (fraud and violation) is always active on all equipment (even during interruptions).
This use case describes the process for applying a threshold on the supply of electrical power. It must be possible to set two different threshold values simultaneously, one for the normal contractual value of the electricity connection and one to be used in case a shortage of electricity is anticipated. The electricity thresholds can be set remotely.
It should be possible to apply demand management settings locally and remotely. Demand limitation for normal and emergency situations should be adjusted either when energy flows from the grid to the customer or from the customer to the grid. When demand limitation in emergency situations is activated it will have the priority to the demand limitation in normal situations.
The activation of the demanded power control mode in the meter allows legacy systems to control the excesses of consumption of electrical power by customers. Meter disconnection elements shall act as a programmable power control switch complying with the applicable legal requirements established. If the power control mode is active, the meter disconnection element interrupts the power supply when the power demanded is higher that a programmable threshold. To restore the power supply, the customer shall, manually or by means of an external domestic device (if such a device exists), close the disconnection device.
Therefore, the legacy systems shall order the activation or deactivation of the power control mode in meters as well as the programming of the power threshold. Those orders should be remotely managed by the CAS, which communicates with meters directly (communication via SI2-MI2) or through a concentrator (communication via SI1-CI2-CI1-MI1).
The smart management of electric distribution grids is one of the key success factors to reach ambitious smart grid goals. Application systems such as an OMS, customer information system, and demand response management system(DRMS) are software that act as decision support systems to assist the distribution system operator with the monitoring and control of the distribution system. The foundation of an application system is the data that is received from AMI. Fig. 19 illustrates the FAHAM system equipped with application systems.
This chapter has been composed of two major sections: the Smart Grid Technology Roadmap in IRAN and the FAHAM. The roadmap focuses on technology development and has been approved in the 147th meeting of the Supreme Council for Science Research and Technology of Iran. The vision of this roadmap says, the Islamic Republic of Iran, by 2025, aims to develop an electric smart grid as an efficient, secure, flexible, and stable grid that delivers the required high quality and reliable power to consumers and stakeholders. ICT, smart management systems, new technologies in the area of smart grids, IoT and integration of DGs, CHP systems, renewable energy resources, and energy storage systems cause dynamic interactions among stakeholders of the whole energy system. A smart grid should provide optimal management of demand and supply in competitive electricity market. Iran seeks to elevate and consolidate the country's position as a first country in the Middle East region in technology development and implementation of smart grid.
FAHAM is an important foundational step in the modernization of the Iran power system. The program involves replacing existing customer meters, now becoming obsolete, with a comprehensive smart meter system. This system includes the technology and telecommunications infrastructure needed for the Iranian power system to continue to manage the electricity system in a reliable, safe, and cost-effective manner. The following key learnings taken from this project have been summarized as follows: