Part I of this two-part article will discuss the conceptual architecture of a smart electric grid leveraging best practices from the Internet, HLA, and large-scale collaboration systems.
A smart grid delivers electricity from suppliers to consumers using digital technology to save energy and cost. The term "smart grid" represents a vision for a digital upgrade (and necessary levels of federation) of distribution and long-distance transmission grids to both optimize current operations, as well as open up new markets for alternative energy production. As with other industries, use of robust two-way communications, advanced sensors, and distributed computing technology will improve the efficiency, reliability and safety of power delivery and use. Smart grid features could expand energy efficiency beyond the grid into the home by coordinating low-priority home devices such as water heaters so that their use of power takes advantage of the most desirable energy sources. Smart grids can also coordinate the production of power from large numbers of small power producers such as owners of rooftop solar panels -- an arrangement that would otherwise prove problematic for power systems operators at local utilities.
A Smart Grid Strategy Model
The core recommendation of this article is to model the strategy of a smart electric grid based on proven practices in the IT industry, specifically in grid computing and large-scale collaboration systems. Both these communities evolved due to national security needs (specifically a need for real-time military simulations), and to connect diverse and distributed communities with a common thread, but at the same time giving enough power for each community to both absorb from and provide to the centralized network. Several years of sustained input into these communities by a collection of entrepreneurs and research professionals, and adequately funded by government agencies including the Department of Defense (DOD), led to successful prototyping of structures like the Global Information Grid.
The term Global Information Grid (GIG) refers to the physical realization of the information system that supports essentially all aspects of the DOD's operations. The GIG architecture is consistent with the principles of general DOD studies such as the 1998 C4ISR (Command, Control, Communications, Computer Intelligence, Surveillance, Reconnaissance) architecture document. Nine core enterprises services (CES) have been baselined to enable the GIG. The framework has been strategized to be flexible to add or update services based on specific communities of interest (COI). The core enterprise services include:
- Enterprise Services Management (ESM): including life-cycle management
- Information Assurance (IA)/Security: supporting confidentiality, integrity and availability
- Messaging: in synchronous or asynchronous fashion
- Discovery: searching data and services
- Mediation: including translation, aggregation, integration, correlation, fusion, brokering publication and other transformations for service and data
- Collaboration: provides and controls sharing with emphasis on synchronous real-time services
- User Assistance: includes automated and manual methods for optimizing the user's GIG experience (including portal interfaces)
- Storage: retention, organization and disposition of all forms of data
GIG has a hierarchically layered architecture model. It is based on four blocks of service groups that increase in specialization per layer. At the bottom level, we have what are resources and associated proxy services -- e.g., the hosting environment, which forms the virtual machine on which we are building the "distributed service operating system" contained in the next layer. Layer 2 contains the core enterprise services. This layer can be implemented with handlers like WS-RM, Security, UDDI Registry and other associated specs. Level 3 contains more granular delivery services at a feature level -- e.g., "Access a Repository", "Submit a Job". Level 4 contains the most coarse-grained targeted/aggregated/personalized profile-driven modules -- e.g., "Simulate a Missile." These modules can be tailored to be delivered via multi-channel gateways to a variety of interfaces. Usually specific COI activities tend to drive this four-layered model from a top-down manner as well. All the four layers are realized by a service-oriented architecture -- where services are built, their interactions (namely messages) are defined -- and so is the support for the two fundamental concepts of messages and services.
Similar to GIG's hierarchically layered architecture, we recommend that all components connected to the smart electric grid (generation, transmission, distribution) follow a design -- with layers of separation -- to insulate basic services (as currently offered), policy implementations (global/country/regional/urban/rural), communications services (how do networks communicate to each other and also within), resource management services (who connects first, who waits how long, what gets stored), financial services (what's the cost, time-of-day, global currency driven), security services (who gets access to what and when). These services are merely representative, and are not intended to showcase the entire set; that's a determination to be made during delivery phases of smart grid.
A different perspective to the GIG is its functional categorization:
- Computational Grids: traditional grids that are designed to provide support for high performance computing resources.
- Sensor/Data Grids: grids that provide access to data and related media. The data may be archived or real-time, collected in either case from sensors, scientific instruments.
- Collaborative Grids: these grids support communications in all forms, ranging from document and message sharing to instant messaging to audio/video collaboration. Group participation and data sharing are also important to these applications.
- Peer-to-Peer/Community Grids: these grids apply principles of peer-to-peer computing resource collections.
- Semantic Grids: these grids focus on information representation and management. They are potentially an excellent way to manage multi-staged computing tasks ("workflow") that must run in a distributed environment.
Similar to GIG's functional categorization, we recommend that the previously discussed layers of the smart electric grid (including basic, policy, communications, resource management, financial) shall be formulated at four different levels (representative set only) -- i.e., enterprise, domain, community, personalized. These different levels represent varying degrees of commonality between user groups. Enterprise-level indicates the least common denominator of services, infrastructure, and applications that apply across the board to the entire grid. Domain-level indicates a bit higher level of specialization -- e.g., targeted towards a particular geographic region or target clientele. Community and Personalized levels indicate a far higher level of individualization, targeted for customer communities or an individual corporation or customer.
Real-World IT Grid applications, in the field, must rely upon services that emerge from many of these functional categories. Military command and control and civilian emergency preparedness are two such examples. In both cases, grid-based collaboration services must link participants, many of whom will be on unreliable networks. Participants will need to rapidly assess data, so integration of data grid services with computational processing is necessary. Due to this requirement for an intrinsic integration, the GIG is also referred to as a "Super Information Grid".
Similarly, the smart grid's real-world applicability and viability shall be determined by the level of flexibility with which each service layer (with diverse functionalities, granularity differences, geographical locations, government policy changes, method of transmissions -- e.g., overhead, underwater, material used, variations in source type) can interact with each other in a value-add, cost-effective manner to the global economy. The smart grid, similar to the Super Information Grid, shall be able to connect different sources and consumers of varying influencing factors (location, policy, consumer type, time of day) using a hub-and-spoke architecture. The critical differentiator of such an architecture is that the "connector entities" can function as a hub (smart centralized storage and distribution) or as a spoke (smart localized storage and distribution) on a dynamic, ad-hoc basis. This hub-and-spoke architecture is recommended to be backed up by the "i2Neo Intelli-Insulation" methodology. This provisionally patented method enables participating grid components to maintain their "daily nature" but find and project their "inner natures" based on a combination of participating factors. These dual natures are fully insulated by design and can be visualized and reported in a unified view or a finely granular view, based on requirements. Using a combination of hub-spoke and intelli-insulation methodologies, the grid acquires fuzzy intelligence capabilities: importantly, both energy sources and consumers are indirectly transformed into smart entities, as well, with storage, efficiency of use, and factor-driven distribution schemes.
Part II of this article will address the architecture internals of the grid, and the "engine" that makes it happen.
The opinions expressed in this article are solely mine, composed based on current and prior experiences I have contributed to. They do not represent the views of any corporation or organization I may be directly or indirectly affiliated to currently.