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Thu, Oct

Smart grid deployment

Technology
Typography

The many smart grid technology areas – each consisting of sets of individual technologies – span the entire grid, from generation through transmission and distribution to various types of electricity consumers. Some of the technologies are actively being deployed and are considered mature in both their development and application, while others require further development and demonstration. A fully optimised electricity system will deploy all the technology areas in Figure 8. However, not all technology areas need to be installed to increase the “smartness” of the grid.

Wide-area monitoring and control

Real-time monitoring and display of power system components and performance, across interconnections and over large geographic areas, help system operators to understand and optimise power system components, behaviour and performance. Advanced system operation tools avoid blackouts and facilitate the integration of variable renewable energy resources. Monitoring and control technologies along with advanced system analytics – including wide-area situational awareness (WASA), wide-area monitoring systems (WAMS), and wide-area adaptive protection, control and automation (WAAPCA) – generate data to inform decision making, mitigate wide-area disturbances, and improve transmission capacity and reliability.

Information and communications technology integration

Underlying communications infrastructure, whether using private utility communication networks (radio networks, meter mesh networks) or public carriers and networks (Internet, cellular, cable or telephone), support data transmission for deferred and real-time operation, and during outages. Along with communication devices, significant computing, system control software and enterprise resource planning software support the two-way exchange of information between stakeholders, and enable more efficient use and management of the grid.

Renewable and distributed generation integration

Integration of renewable and distributed energy resources – encompassing large scale at the transmission level, medium scale at the distribution level and small scale on commercial or residential building – can present chalenges for the dispatchability and controllability of these resources and for operation of the electricity system. Energy storage systems, both electrically and for themally based, can alleviate such problems by decoupling the production and delivery of energy. Smart grids can help through automation of control of generation and demand (in addition to other forms of demand response) to ensure balancing of supply and demand.

Transmission enhancement applications

There are a number of technologies and applications for the transmission system. Flexible AC transmission systems (FACTS) are used to enhance the controllability of transmission networks and maximise power transfer capability. The deployment of this technology on existing lines can improve efficiency and defer the need of additional investment. High voltage DC (HVDC) technologies are used to connect offshore wind and solar farms to large power areas, with decreased system losses and enhanced system controllability, allowing efficient use of energy sources remote from load centres. Dynamic line rating (DLR), which uses sensors to identify the current carrying capability of a section of network in real time, can optimise utilisation of existing transmission assets, without the risk of causing overloads. High-temperature superconductors (HTS) can significantly reduce transmission losses and enable economical fault-current limiting with higher performance, though there is a debate over the market readiness of the technology.

Distribution grid management

Distribution and sub-station sensing and automation can reduce outage and repair time, maintain voltage level and improve asset management. Advanced distribution automation processes real-time information from sensors and meters for fault location, automatic reconfiguration of feeders, voltage and reactive power optimisation, or to control distributed generation. Sensor technologies can enable condition- and performance-based maintenance of network components, optimising equipment performance and hence effective utilisation of assets.

Advanced metering infrastructure

Advanced metering infrastructure (AMI) involves the deployment of a number of technologies – in addition to advanced or smart meters that enable two-way flow of information, providing customers and utilities with data on electricity price and consumption, including the time and amount of electricity consumed. AMI will provide a wide range of functionalities:

• Remote consumer price signals, which can provide time-of-use pricing information.

• Ability to collect, store and report customer energy consumption data for any required time intervals or near real time.

• Improved energy diagnostics from more detailed load profiles.

• Ability to identify location and extent of outages remotely via a metering function that sends a signal when the meter goes out and when power is restored.

• Remote connection and disconnection.

• Losses and theft detection.

• Ability for a retail energy service provider to manage its revenues through more effective cash collection and debt management.

Electric vehicle charging infrastructure

Electric vehicle charging infrastructure handles billing, scheduling and other intelligent features for smart charging (grid-to-vehicle) during low energy demand. In the long run, it is envisioned that large charging installation will provide power system ancillary services such as capacity reserve, peak load shaving and vehicle-to-grid regulation. This will include interaction with both AMI and customer-side systems.

Customer-side systems

Customer-side systems, which are used to help manage electricity consumption at the industrial, service and residential levels, include energy management systems, energy storage devices, smart appliances and distributed generation. Energy efficiency gains and peak demand reduction can be accelerated with in-home displays/energy dashboards, smart appliances and local storage. Demand response includes both manual customer response and automated, price-responsive appliances and thermostats that are connected to an energy management system or controlled with a signal from the utility or system operator.

Table 3 highlights a number of hardware and systems and software associated with each technology area.

Within the smart grid technology landscape, a broad range of hardware, software, application and communication technologies are at various levels of maturity. Some technologies have proven themselves over time, but many – even if mature – have yet to be demonstrated or deployed on a large scale. Existing projects give an indication of the maturity levels and development trends of smart grid technologies (Table 4).

Smart grid demonstration and deployment efforts

There has been a marked acceleration in the deployment of smart grid pilot and demonstration projects globally, due in part to the recent government stimulus investment initiatives in 2009 and 2010 (Table 5). Investments around the world have enabled hundreds of projects entirely or partly focused on smart grid technologies; the above table provides only a small sample.

Most current smart grid pilot projects focus on network enhancement efforts such as local balancing, demand-side management (through smart meters) and distributed generation. Demonstration projects have so far been undertaken on a restricted scale and have been hindered by limited customer participation and a lack of a credible aggregator business model. Data (and security) challenges are likely to increase as existing pilots expand to larger-scale projects. Non-network solutions such as ICTs are being used in a growing number of smart grid projects, bringing a greater dependence on IT and data management systems to enable network operation (Boots et al., 2010).

The Telegestore project, launched in 2001 by ENEL Distribuzione S.p.A. (i.e. prior to the current smart grids stimulus funding) addresses many of these issues. The project installed 33 million smart meters (including system hardware and software architecture) and automated 100 000 distribution substations, while also improving management of the operating workforce and optimising asset management policies and network investments. The project has resulted in fewer service interruptions, and its EUR 2.1 billion investment has led to actual cost savings of more than EUR 500 million per year. Today an active small and medium scale industry is developing technologies for smart grids and ENEL is continually enhancing the system by introducing new features, technologies and flexibility. The project clearly demonstrates the value of a large-scale, integrated deployment of smart grid technologies to solve existing problems and plan for future needs.

Although significant effort and financial resources are already being invested in smart grids, the scale of demonstration and deployment co-ordination needs to be increased. Several organisations have created, are creating or are calling for the creation of an inventory or database of detailed case studies to gather the lessons learned from such projects, particularly in the areas of policy, standards and regulation, finance and business models, technology development, consumer engagement and workforce training.

Tailoring smart grids to developing countries and emerging economies

While advanced countries have well-developed modern grids, many others have grids that do not operate consistently over a 24-hour period, and still others have no electricity infrastructure at all. Developing countries and emerging economies are often categorised by high growth in electricity demand, high commercial and technical losses in a context of rapid economic growth and development, dense urban populations and dispersed rural populations. These aspects present both significant challenges and opportunities. Smart grids can play an important role in the deployment of new electricity infrastructure in developing countries and emerging economies by enabling more efficient operation and lower costs. Small “remote” systems – not connected to a centralised electricity infrastructure and initially employed as a cost-effective approach to rural electrification – could later be connected easily to a national or regional infrastructure.

As a means to access to electricity in sparsely populated areas, smart grids could enable a transition from simple, one-off approaches to electrification (e.g. battery- or solar PV-based household electrification) to community grids that can then connect to national and regional grids (Figure 9).

The deployment stages in Figure 9 require standardisation and interoperability to be scaled up to the next level with higher amounts of supply and demand. Each successive step can increase reliability and the amount of power available if managed in a way that allows a seamless transition for the community. Roadmaps and targeted analysis focusing on developing countries and emerging economies should assess what lessons can be learned from smart grid demonstrations and deployments in developed countries. Ultimately, the end point of smart grid deployment is expected to be similar across the world, but the routes and time it takes to get there could be quite different (Bazilian, 2011).

Status of electricity system markets and regulation

Current regulatory and market systems, both at the retail and wholesale levels, can present obstacles to demonstration and deployment of smart grids. It is vital that regulatory and market models – such as those addressing system investment, prices and customer participation – evolve as technologies offer new options.

Some markets allow vertically integrated utilities, which own and operate infrastructure assets across the generation, distribution and transmission sectors. This ensures that costs and benefits from the deployment of technology are shared and managed efficiently across the various sectors. Vertically integrated structures also allow the most appropriate and fully integrated investment and development for the power system as a whole, rather than just evaluating costs and benefits in one part of the electricity system. It can be difficult for competitors to enter such markets and compete with incumbent players, which could hinder innovation and increase prices for consumers. However, the climate for competitiveness depends largely on whether the market is governed by appropriate regulatory structures.

“Unbundling” of the electricity system, which is intended to allow increased competition, has required entities that operated across the entire system to divide into market-based and regulated units, either functionally by creating separated operating teams within companies or legally by selling companies or creating new ones to separate activities. Market-based activities typically include the generation sector and the retail sector (Figure 10). In the generation sector, markets have developed in which generators sell electricity within a structure defining prices, time frames and other rules. In the retail sector, sometimes the distribution system operator still retails the electricity to consumers and sometimes new participants enter the market that sell only electricity services.

The introduction of market-based activities through unbundling has brought many benefits to the electricity sector, primarily a continued downward pressure on prices, but such objectives can also be met in vertically integrated markets. Varying degrees of unbundling exist around the world. Unbundling also makes it difficult to capture both costs and benefits of various technology deployments on a system-wide basis – especially with respect to smart grids. Smart grid investments are likely to be deployed more rapidly in vertically integrated utilities where the business case can more easily be made. In the many areas where this is not possible, more strategic co-operation between distribution system operators and transmission system operators is needed.

Source: Technology Roadmap- Smart Grids

© OECD/IEA, 2011