Major programs IntelliGrid – Created by the Electric Power Research Institute (EPRI), IntelliGrid architecture provides methodology, tools, and recommendations for standards and technologies for utility use in planning, specifying, and procuring IT-based systems, such as advanced metering, distribution automation, and demand response. The architecture also provides a living laboratory for assessing devices, systems, and technology. Several utilities have applied IntelliGrid architecture including Southern California Edison, Long Island Power Authority, Salt River Project, and TXU Electric Delivery. The IntelliGrid Consortium is a
public/private partnership that integrates and optimizes global research efforts, funds technology R&D, works to integrate technologies, and disseminates technical information.
Grid 2030 – Grid 2030 is a joint vision statement for the U.S. electrical system developed by the electric utility industry, equipment manufacturers, information technology providers, federal and state government agencies, interest groups, universities, and national laboratories. It covers generation, transmission, distribution, storage, and end-use. The National Electric Delivery Technologies Roadmap is the implementation document for the Grid 2030 vision. The Roadmap outlines the key issues and challenges for modernizing the grid and suggests paths that government and industry can take to build America's future electric delivery system.
Modern Grid Initiative (MGI) is a collaborative effort between the U.S. Department of Energy (DOE), the National Energy Technology Laboratory (NETL), utilities, consumers, researchers, and other grid stakeholders to modernize and integrate the U.S. electrical grid. DOE's Office of Electricity Delivery and Energy Reliability (OE) sponsors the initiative, which builds upon Grid 2030 and the National Electricity Delivery Technologies Roadmap and is aligned with other programs such as GridWise and GridWorks.
GridWise – A DOE OE program focused on developing information technology to modernize the U.S. electrical grid. Working with the GridWise Alliance, the program invests in communications architecture and standards; simulation and analysis tools; smart technologies; test beds and demonstration projects; and new regulatory, institutional, and market frameworks. The GridWise Alliance is a consortium of public and private electricity sector stakeholders, providing a forum for idea exchanges, cooperative efforts, and meetings with policy makers at federal and state levels.
GridWise Architecture Council (GWAC) was formed by the
U.S. Department of Energy to promote and enable interoperability among the many entities that interact with the nation's electric power system. The GWAC members are a balanced and respected team representing the many constituencies of the electricity supply chain and users. The GWAC provides industry guidance and tools to articulate the goal of interoperability across the electric system, identify the concepts and architectures needed to make interoperability possible, and develop actionable steps to facilitate the inter operation of the systems, devices, and institutions that encompass the nation's electric system. The GridWise Architecture Council Interoperability Context Setting Framework, V 1.1 defines necessary guidelines and principles.
GridWorks – A DOE OE program focused on improving the reliability of the electric system through modernizing key grid components such as cables and conductors, substations and protective systems, and power electronics. The program's focus includes coordinating efforts on high temperature superconducting systems, transmission reliability technologies, electric distribution technologies, energy storage devices, and GridWise systems.
Pacific Northwest Smart Grid Demonstration Project. - This project is a demonstration across five Pacific Northwest states-Idaho, Montana, Oregon, Washington, and Wyoming. It involves about 60,000 metered customers, and contains many key functions of the future smart grid.
Solar Cities - In Australia, the Solar Cities programme included close collaboration with energy companies to trial smart meters, peak and off-peak pricing, remote switching and related efforts. It also provided some limited funding for grid upgrades.
Smart Grid Energy Research Center (SMERC) - Located at
University of California, Los Angeles dedicated its efforts to large-scale testing of its smart EV charging network technology. It created another platform for bidirectional flow of information between a utility and consumer end-devices. SMERC also developed a demand response (DR) test bed that comprises a Control Center, Demand Response Automation Server (DRAS), Home-Area-Network (HAN), Battery Energy Storage System (BESS), and photovoltaic (PV) panels. These technologies are installed within the Los Angeles Department of Water and Power and Southern California Edison territory as a network of EV chargers, battery energy storage systems, solar panels, DC fast charger, and Vehicle-to-Grid (V2G) units. These platforms, communications and control networks enables UCLA-led projects within the area to be tested in partnership with two local utilities, SCE and LADWP.
Smart Quart - In Germany, the Smart Quart project develops three smart districts to develop, test and showcase technology to operate smart grids. The project is a collaboration of
E.ON,
Viessmann, gridX and hydrogenious together with the
RWTH Aachen University. It is planned that by the end of 2024 all three districts are supplied with locally generated energy and are largely independent of
fossil energy sources.
Smart5Grid – In Portugal, aims to ensure that operators in the energy sector take advantage of the benefits associated with the use of
5G networks. With
reliability and security, a solution is proposed to precisely address the specific requirements imposed by Smart Grids, such as high data transfer rates and real-time monitoring.
Smart grid modelling Many different concepts have been used to model intelligent power grids. They are generally studied within the framework of
complex systems. In a recent brainstorming session, the power grid was considered within the context of
optimal control,
ecology, human cognition, glassy dynamics,
information theory, microphysics of
clouds, and many others. Here is a selection of the types of analyses that have appeared in recent years. ;Protection systems that verify and supervise themselves Pelqim Spahiu and Ian R. Evans in their study introduced the concept of a substation based smart protection and hybrid Inspection Unit. ;Kuramoto oscillators The power grid has been mapped onto variations of the
Kuramoto model, a well-studied framework for synchronization of nonlinear oscillators. The model describes how the electrical system keeps the power balance, to maintain
phase synchronization (also known as phase locking). Strictly speaking, the model is most used for an ordinary electrical grid, to determine, for instance, the role of branch insertions or of paramters dispersion. Non-uniform oscillators also help to model different technologies, different types of power generators, patterns of consumption, and so on. The model has also been used to describe the synchronization patterns in the blinking of fireflies. ;Neural networks
Neural networks have been considered for power grid management as well. Electric power systems can be classified in multiple different ways: non-linear, dynamic, discrete, or random. Artificial Neural Networks (ANNs) attempt to solve the most difficult of these problems, the non-linear problems. ;Demand Forecasting One application of ANNs is in demand forecasting. In order for grids to operate economically and reliably, demand forecasting is essential, because it is used to predict the amount of power that will be consumed by the load. This is dependent on weather conditions, type of day, random events, incidents, etc. For non-linear loads though, the load profile isn't smooth and as predictable, resulting in higher uncertainty and less accuracy using the traditional Artificial Intelligence models. Some factors that ANNs consider when developing these sorts of models: classification of load profiles of different customer classes based on the consumption of electricity, increased responsiveness of demand to predict real time electricity prices as compared to conventional grids, the need to input past demand as different components, such as peak load, base load, valley load, average load, etc. instead of joining them into a single input, and lastly, the dependence of the type on specific input variables. An example of the last case would be given the type of day, whether its weekday or weekend, that wouldn't have much of an effect on Hospital grids, but it'd be a big factor in resident housing grids' load profile. ;Markov processes As
wind power continues to gain popularity, it becomes a necessary ingredient in realistic power grid studies. Off-line storage, wind variability, supply, demand, pricing, and other factors can be modelled as a mathematical game. Here the goal is to develop a winning strategy.
Markov processes have been used to model and study this type of system. ==Economics==