Communication Requirements and Challenges in the Smart Grid
In countries with mature economies, power distribution networks play a critical role in supporting the industrialized society. These power grids were designed decades ago, with the main aim of delivering electricity from large power stations to households and businesses. The last few years, however, have witnessed the introduction of novel technologies and concepts that promise to change the way we produce, manage, and consume electricity. Technologies such as distributed generation and plug-in hybrid electric vehicles (PHEVs) will help to reduce CO2 emissions and offer more sustainable options to consumers of energy, while applications such as the advanced metering infrastructure (AMI) and home energy management system (HEMS) will enable consumers to manage their energy usage more efficiently. The smart grid initiative aims at modernizing the current electricity grid by introducing a new set of technologies and services that will make the electricity networks more reliable, efficient, secure, and environmentally friendly.
The smart grid will be characterized by a two-way flow of electricity and information, creating an automated, widely distributed energy delivery network. It will incorporate into the power grid the benefits of distributed computing and communications to deliver real-time information that will help balance power supply and demand. To be successful, the smart grid initiative will require collaboration, integration, and interoperability among an array of technologies and disciplines. Various forms of information and communication technology (ICT) will therefore play a major role in facilitating the realization of the modern power grid and its services.
There is an increasing consensus that the communication infrastructure that supports the operation of the power grid today needs fundamental changes. This communication infrastructure was designed to meet the needs of a regulated power industry that dates from several decades ago. The communication networks in these power grids were designed to support control operations and interactions between control centers and individual substations. These legacy control systems, often referred to as supervisory control and data acquisition (SCADA) systems, were typically built using a star topology in which data are exchanged between the control center and substations; the main aims were to detect faults and manage generation and demand in the power grid. The messages exchanged through the communication networks consist of either information about the health of the power grid (voltages, the temperatures of the cables, the status of circuit breakers, and so on) or commands that enable changes in the configuration of the network, such as those used to open and close circuit breakers. Such communication infrastructures therefore have a limited ability to cope with the new requirements of the smart grid in terms of penetration, scalability, and performance.
To design a new communication infrastructure able to support the modern power grid, it is important to understand its requirements. In this article, we aim to identify the communication requirements that need to be fulfilled in order to realize the smart grid. These requirements will be identified through the study of the applications and services being promoted by the movement toward smart grid technologies. The remainder of the article is organized as follows. The second section will discuss distributed generation, how it can be integrated within the power grid, and what the communication needs are to make such integration possible. The third section will study the benefits of AMI and identify the communication network that should be built to support its operations. The fourth section will give an overview of the HEMS, its main components, and how home area networks (HANs) will play a major role in realizing these systems. The fifth section will present PHEV technology and emphasize the importance of control and communication networks if this solution is to be adopted on a large scale. The next two sections will offer an overview of the main communication challenges that need to be tackled in order to facilitate the implementation of the smart grid. Our conclusions will follow in the final section.
Distributed Energy Generation
One of the main benefits of the smart grid will be the introduction of distributed energy resources (DERs) into the electricity grid on a large scale. These DERs will be able to supply particular areas with electricity when they are isolated from the main power grid due to failure conditions or system and equipment failures.
Currently, supplying isolated locations with electricity comes with an increased cost to the distribution network operators (DNOs), as the majority of the energy that is destined for customers is wasted in the form of heat before any useful energy reaches the consumer. In this case, DERs represent a cheaper and more efficient solution that can deliver energy from points closer to the consumer than the DNO’s centralized power grid.
Figure 1 shows an area isolated and cut off from the power supply due to a fault that occurred on a feeder and resulted in the opening of breaker B1. The isolated area can be resupplied with electricity from generator G1, however, once breaker B2 is closed.
Although the integration of DER into the power grid makes the energy supply more reliable and reduces its cost, it creates new issues for DNOs. While in a traditional power grid the electricity usually flows from the central power stations to the consumers, in a modern power grid incremented with DER, the electricity flows in two directions, as these new sources of energy are introduced at a lower voltage. To introduce DER technology, DNOs will be faced with the challenge of making their power distribution networks more flexible and dynamic. Whereas in the past distribution networks were considered to be static, with no major control operation or reconfiguration requirements, in the smart grid, distribution networks will be in constant flux depending on the direction and amount of power flow. DNO control systems will therefore need to move from passive control to a more active approach in which the distribution network can be modified and reconfigured according to changes in power flow.
An active control system, however, must have access to control information related to the status of the distribution network. Sensors need to be deployed in large numbers in order to efficiently monitor power network conditions such as faults at the transformers, the status of the breakers, power flow magnitude, and flow directions in distribution lines, as depicted in Figure 2. The telecommunication systems that support grid control operations such as SCADA therefore need to be extended and enhanced to help track all the data collected by the -sensors and enable the system to perform its functions.
Moreover, many studies in the area of active control reflect a shift from the centralized control model toward a more distributed control paradigm. In this model, distribution networks are divided into microgrids, where each microgrid is formed by the interconnection of distributed generators. Autonomous intelligent controllers are deployed to manage these microgrids, as illustrated in Figure 3. These intelligent controllers perform control operations locally, and they, rather than the control room, become the destination for the sensor data. For better management, these intelligent controllers are expected to run in a collaborative manner and exchange control information regularly. Although such a sophisticated control system will remove a certain amount of communication stress from the control room, it will also add new communication requirements, as implementation requires horizontal communication links and more transmission bandwidth.
Advanced Metering Infrastructure
AMI technology will be a vital component of the smart grid as it will provide utilities with a wealth of new information that could help to optimize business operations. AMI could be used by utilities as a way to collect monthly consumption data used for billing and provide load profile, demand, time-of-use, voltage profile, and power quality data.
The use of AMI technology for these operations will eliminate the need for many labor-intensive business processes, such as manual meter reading, field trips for service connects and disconnects, on-demand reads, power outage and restoration management, and other metering support functions. Moreover, AMI systems with two-way communications will let utilities send pricing signals to alert customers to critical periods of peak pricing. This direct communication to customers will encourage conservation during peak periods and will let utilities implement direct control of demand-side management.
Through near real-time price signals, AMI will also enable consumers to manage their energy usage more efficiently. Energy prices could be relayed directly to appliances or through a home energy management gateway, as depicted in Figure 4. The appliances, in turn, would process the information based on consumers’ learned wishes and adjust power consumption accordingly. To realize such a sophisticated control system, a communication network must be deployed to facilitate the exchange of information and -control operations between utilities and consumers.
Typically, an AMI network is composed of networks connecting a number of hardware components and pieces of software. Smart meters in households within the same neighborhood, equipped with communication interfaces, will be connected to a central unit, called a data collector, forming a neighborhood area network (NAN). Each data collector will also be connected to the AMI wide area network (WAN), also called the backhaul, via a collection point on the edge of the WAN that provides connections and/or consolidation for metering data access, as shown in Figure 5. All data sent by smart meters and other control devices will be relayed to a central server running a management application located at the utility control center.
Home Energy Management System
HEMSs will let households effectively centralize the management of services, provide customers with comprehensive functions for internal information exchange, and help keep household members in continuous contact with the outside world. They will also help households optimize their lifestyles, rearranging the day-to-day energy consumption schedule so as to secure a high quality of life while reducing energy bills. In addition to the home’s appliances (indoor electrical devices), an HEMS is typically composed of three main elements:
- An energy management gateway (EMG) that ensures a secure connection between the home’s appliances and other electrical devices and the utility: This gateway will serve mainly as an interface between the utility’s AMI and the home electricity infrastructure (appliances, generation, storage, and so on) and will ensure secure communication between the utility’s AMI and the HEMS.
- An energy management unit (EMU) that collects information about the status of appliances and other electrical devices: This unit controls energy consumption, generation, and storage in the home and communicates with the EMG to deliver control commands or information from the utility to the home appliances. This energy control function includes the calculation of energy consumption, cost, billing, status, and so on as well as the issuing of control commands to appliances.
- A group of sensors and microcontrollers that feed the EMU: These devices supply the EMU with information about the status of the home’s appliances, their mode of operation, and their operational environment.
To realize such a control system, a HAN is required to permit the integration of all targeted electrical devices (home appliances, energy sources, and energy storage entities), microcontrollers (intelligent sensors, RFID units, thermostats, and so on), and other HEMS control components, as depicted in Figure 6. The HAN will carry control data generated by intelligent sensors, microcontrollers, and home appliances to the EMU. It will also carry the control commands from the EMU to the appliances and energy generation and storage devices and from the utility to the appliances registered in the gateway.
Plug-In Hybrid Electric Vehicle
Vehicles are part of our daily lives and represent a major player in world energy consumption and
environmental pollution. Until recently, research was only focused on ways to optimize the design of vehicles and improve their subsystems. With the emergence of advanced vehicular technologies, however, research efforts have been directed toward advanced batteries and storage systems, engine and power train control, and hybrid electric vehicle (HEV) optimization. PHEV technology shows great promise, as it has the potential to both curb emissions and reduce the cost of transportation.
Although plug-in vehicles have not yet been adopted on a large scale, governments, utilities, and auto companies are enthusiastically anticipating the opportunities that may arise from reduced emissions and gasoline consumption, new services and increased revenues, and new markets that would create new jobs.
Currently, research on PHEVs has only focused on developing analyses and demonstrations of vehicle charging behavior, but the long-term infrastructure and information architectures required for a massive market infiltration of PHEVs are less well defined, and there has been little research effort to investigate how the power grid infrastructure could be accommodated to enable a large number of plug-in vehicles.
Despite the accompanying environmental and economic benefits, the adoption of PHEV technology on a large scale will present a serious challenge to utilities, as the penetration of a large number of PHEVs will add stress on the power grid, which might cause voltage instabilities and blackouts. To avoid the worst scenarios, the charging of PHEVs should be monitored by an energy management system (EMS) to help prevent the overloading of the electricity grid. This process is summarized in Figure 7.
Although such an EMS could reside within the utility control room, researchers have also proposed integrating it within intelligent controllers as part of a wider active control system. This EMS will play a major role in issuing decisions about the vehicle-charging process. For instance, when a PHEV tries to charge its battery, the EMS could delay or even refuse the charging operation if there is too much demand on the grid. To make such real-time decisions, however, it is vital to have an underlying communication platform that can support these kinds of control operations.
Whether the intelligent management system is located within the utility control room or installed separately, building it will require a communication network that can effectively communicate details about the charging process of the PHEV to the EMS. Since these decisions will be made in real time, the communication network will play a crucial role in determining overall system performance.
The smart grid will be the carrier for a range of novel applications and services that will help utilities deliver energy more efficiently and enable consumers to manage their energy usage more effectively. These applications and services will have certain communication requirements that cannot be fulfilled by the current communication infrastructure, however. In this section we present the main challenges that need to be tackled and the changes that need to be made in order to satisfy these requirements and facilitate the realization of the smart grid.
From Centralized to Distributed Communication
Legacy control systems in the power grid are composed of control devices, generally called remote terminal units (RTUs). These traditional control systems grew up with the notion of a master RTU and slave RTUs. Slave RTUs are field devices, located within remote sections of the power grid and hard-wired to a master RTU. They are programmed to report their measurements periodically, to act as a data concentrator.
The centralized hierarchical organization of these systems is also reflected in the way the underlying communication protocols operate. Since these devices are connected to a master RTU, the main communication procedure is to allow these control devices to send their measurements to the master RTU and enable the master RTU to send commands to slave RTUs. This vertical communication approach, shown in Figure 8, does not match up well with the requirements of a future distributed control system for the smart grid.
In the future smart grid, control systems will shift from a centralized and passive model to a more distributed and active one. The implementation of control operations in the smart grid will therefore require underlying communication protocols that are more flexible and enable horizontal data exchange between controllers and RTUs in addition to vertical communication—and without necessarily being hard-wired. Communication protocols in the smart grid should also enable control of RTUs in groups, not individually. To make the smart grid a reality, new communication protocols should be designed to provide functionalities that do not exist in the current communication infrastructure, such as data routing, broadcasting, multicasting, and so on.
Data Integration and Network Management
The smart grid will generate billions of data points from thousands of system devices and hundreds of thousands of customers. This wealth of raw data, although not directly useful, could be converted and exploited into information through a knowledge-management life cycle. The data collected from meters, appliances, substations, and other sources will help utilities better understand load factors, energy usage patterns, equipment condition, voltage levels, and many other aspects of the power system.
To achieve this, data must be transported efficiently from these control devices and applications to the servers in the utility control room or power grid substation. This requires a robust, large-bandwidth communication infrastructure that can cope with the enormous volume of data that will be constantly exchanged. Current communication infrastructures, however, have been designed to restrict traditional control systems to the acquisition of limited amounts of data. These communication networks are usually built with old technologies such as telephone lines that have a low bandwidth ratio. The current communication infrastructure therefore cannot meet the demands of smart grid applications and control operations.
The most obvious solution would be to upgrade the communication network, either by replacing the network equipment that limits the transmission and reception rates (modems, routers, and so on) or by introducing new communication technologies that offer wider bandwidth (such as optical fiber and microwave radio links). For many utilities with communication infrastructures that span hundreds of miles, however, the cost of this modernization process could easily be prohibitive.
A less costly alternative is to store measurements in a local substation and exchange the relevant data among the substations to enable sophisticated real-time -applications. Given that substations are usually connected through high-bandwidth links, it becomes possible to aggregate and exchange data at higher rates and thus to reduce stress on the more bandwidth-constrained segments of the communication network.
The Last Mile
Interaction with the customer is at the heart of many smart grid applications, and this requires the deployment of spur or “last-mile” communications, typically from a backbone node right up to the customer’s premises. Utilities may find it difficult, however, to justify the extra cost of incorporating communication links from millions of customers, mostly in residential areas, to the core communication network of the power grid, as the balance between the cost of such a process and the economic benefit brought by home applications requiring this connectivity is not yet clear.
In reality, residential smart grid applications such as AMI have low reliability and connectivity requirements from the communication network. If a small group of customers is disconnected from the smart grid communication network for a relatively short period of time, the reliability and safety of power grid operations would not be threatened. Moreover, these applications do not require a great deal of communication bandwidth, as is the case in the backbone. Low-speed communication technologies with marginal transmission bandwidth that may require multiple retransmissions to complete a message can be tolerated. These relaxed performance and reliability communication requirements in the last mile increase the number of technology candidates. Technologies such as meshed Wi-Fi and power line carrier that are not considered reliable or robust enough for the mission-critical infrastructure backbone become viable options for the last mile. Public networks such as digital subscriber line (DSL) and cellular-based wireless data networks could also be considered as last-mile solutions if utilities could negotiate bulk service rates with the public network operators.
HANs for Appliance Energy Management
A number of networking technologies will be used to form the core of the sophisticated communication network that will support the various control operations of the HEMS. These networking technologies vary from high-speed links to wired and wireless low-power and rate-limited links, such as Wi-Fi, power-line carrier, IEEE 802.15.4, and many others.
While the level of penetration of each technology will vary from one deployment scenario to another, integrating them in the network will present certain challenges. First, these communication technologies have different data rates and transmission, reception, and control functionalities. The HAN cannot provide the end-to-end performance required, however, without an efficient architecture that ensures the proper interworking of the various technologies. Second, as the number of appliances, controllers, and intelligent sensors in the HAN using the radio frequency spectrum increases, some regions of the radio frequency space will quickly become congested. The challenge will be to use interference-aware routing strategies that exploit knowledge of the physical radio channel across the network to route signals so as to avoid existing congestion and avoid creating new congested regions. By understanding the properties of the radio channels, the quality of service for control operations can be managed more effectively and the channels used more efficiently (e.g., low-rate data without tight latency requirements can be sent through poor channels with highly redundant codes). Finally, it has already been proven that sharing information among different layers of a protocol stack can improve system performance; such an approach has only been considered in homogeneous networks, however. The challenge will be to study and devise novel cross-layer optimization approaches where a heterogeneous mixture of links and protocol stacks exists.
Smart Grid Design Trends and Key Features
Satisfying this demanding set of requirements for a next-generation power grid system requires a better understanding of the future design trends of the smart grid and identification of its key features. While such a study will include a broad set of interdisciplinary technical areas, we focus here on the computing and communication aspects, as they will lay the foundation for any power system with sufficient flexibility and resilience to meet future needs.
Architectural Design and Data Aggregation
Given the scale and scope of the systems being considered, with thousands or even millions of potential end users on the network, the architecture for a smart grid computing and communication system must be carefully designed. In particular, the development of a distributed management and data aggregation model will be critical to making the system scalable and responsive to localized changes. In particular, a key choice is that between a semicentralized or a wholly distributed model: whether the system is managed by a small set of entities or by many entities. This involves calculating the trade-off between simple, unified control on one hand and more localized and responsive but complex control on the other.
Provision of Computing Power
Another key component of a new smart grid system will be some significant “back-end” processing services to support dynamic analysis of the incoming monitoring statistics and provide updated information to the management entities and administrators. This will require the provision of on-demand computing facilities capable of dealing with this volume of data. A natural way to fulfill this need is through cloud computing, whereby resources can be allocated on demand for data analysis without a significant initial outlay for equipment. There are still a number of issues related to cloud computing in this context that need to be resolved, however. Perhaps the most significant of these is data protection and security, as strict guarantees will need to be given in this respect.
A Simple, Scalable, and Efficient System
Finally, for any system to be deployable over the entire network it must be sufficiently simple and scalable to be seen as a worthwhile investment. This is a highly complex issue and includes the cost of equipment in the core and edge, administrative and training overheads, development and maintenance costs, and many other factors. This is because the system must be viewed in its entirety, not in isolation. One potential solution is to adopt a modular approach in which smart grid “islands” are deployed in streets, communities, villages, or other discrete units and interconnected and scaled up from there.
Secure, Robust, and Reliable Communication
With the provision of a dedicated communication network that becomes critical to the operation of the system, it is clear that this network must be secure, robust, and reliable. It has long been accepted that such critical infrastructures must be protected and made resilient against failures and attacks, and mature network “hardening” techniques can be employed for this purpose. In the event that the public Internet is used to connect customer equipment with the provider infrastructure, it is obvious that strong encryption and authentication measures must be taken to ensure the security of data in transit. Energy providers may also want to consider adopting a trusted platform model to ensure the integrity of the entities in the system and help protect against attack.
Making the smart grid a reality will entail communication capabilities that do not exist in current power grids and their legacy control systems. New grid elements such as distributed energy generation and PHEVs will necessitate changes in these existing communication networks. These changes will be dictated by the need for new control operations that will allow efficient management of these new elements and that cannot be supported by the existing communication infrastructure. Moreover, the smart grid will let households manage energy usage more efficiently through AMI and HEMSs. The realization of these systems will require pushing communication networks far out from the network core and deep into homes and buildings. We have presented the communication requirements of the smart grid, and we have identified the main technical challenges that need to be tackled. The only viable way to fulfill these requirements is to design a new communication architecture that can support smart grid services and control operations. This future communication architecture will need to take advantage of the recent progress made in communication technologies and protocols. It will require the introduction of communications technologies that were not considered in the past. In addition, this communication architecture will need to be reliable, scalable, and extendable to future smart grid services and applications.
For Further Reading
C. Hauser, D. E. Bakken, and A. Bose, “A failure to communicate: Next generation communication requirements, technologies, and architecture for the electric power grid,” IEEE Power Energy Mag., vol. 3, no. 2, pp. 47–55, 2005.
R. Currie et al., “Active power flow management to facilitate increased connection of renewable and distributed generation to rural distribution networks,” Int. J. Distrib. Energy Resour., vol. 3, no. 3, pp. 177–189, 2007.
E. M. Davidson and S. McArthur, “Exploiting multi-agent system technology within an autonomous regional active network management system,” in Proc. Int. Conf. Intelligent Systems Applications to Power Systems, 2007.
D. G. Hart, “Using AMI to realize the Smart Grid,” in Proc. Power and Energy Society General Meeting—Conversion and Delivery of Electrical Energy in the 21st -Century, Pittsburgh, PA, 2008.
R. J. Meyersa, E. D. Williams, and H. S. Matthew, “Scoping the potential of monitoring and control technologies to reduce energy use in home,” in Proc. IEEE Int. Symp. Electronics and the Environment, Orlando, FL, 2007.
T. Bevis et al., “A review of PHEV grid impacts,” in Proc. North American Power Symp. (NAPS), Starkville, MS, 2009.
Faycal Bouhafs is with Liverpool John Moores University.
Michael Mackay is with Liverpool John Moores University.
Madjid Merabti is with Liverpool John Moores University.