Tesla’s Off-grid Power Storage Batteries: More Questions on Load Forecasting and Data

June 1, 2015

Tesla’s announcement last month of new energy storage batteries was positioned to mark a major milestone on the road towards a clean and sustainable future. Storage that is on the end-user’s side is being viewed, at least by some, as the last piece in the mosaic of what constitutes a distributed energy resources system. Such systems comprise multiple components, including a diverse array of power-generating technologies (such as solar, wind, combined heat and power systems, or micro hydro turbines) supplemented by backup generators, microgrids, and of course energy storage units. A properly installed and efficiently run system should be able not only to support the needs of its immediate consumers, but also act as a supplier of power to the wholesale grid.

A great vision; however, making it a reality takes a bit more than placing energy storage units in the garage. Building a “brainpower” layer operating on top of the conventional infrastructure is at the core of these new systems, and it is a major task. The intelligence, flexibility, and resilience of these new systems require the power industry to enter completely new realms of advanced technologies; hardware and software innovations will be in high demand for the next decade or so.

Researchers currently focus their efforts on developing open-source interoperability standards and cross-technology solutions that can work together. Some of the topics include solar microgrid controllers (that can recognize when new solar power is introduced to the grid), inverters, cross-discipline real-time simulation modeling programs with advanced 3D visualization, and collaboration tools. This list is long and complex; and it will keep growing and expanding in advances aimed at optimizing system-level performance, improving information security, metering, communications infrastructure, and so on. But this is only one aspect. Developers of data management solutions are facing even more complex tasks. More sophisticated tools are needed for participation in transactional energy markets where price and control signals are exchanged between grid equipment, users, and utilities. The introduction of user-based power storage batteries at this point raises many questions. Because of the timing of this introduction, these questions have to be answered much sooner than anticipated – as in “now.”

Off-grid power storage creates a completely new reality for utilities. Traditional load projections and approaches in meeting this demand by utilities are becoming obsolete. How will the utilities solve it? User-based storage can remove the costs of demand, but how will utilities know when consumers switch between user and supplier modes? It is likely that a combination of both worlds – a centralized grid and locales of distributed resources – will bring about a new model of how the power industry operates. How many types of these new customers will there be? Will there be individual distributed generation consumers tapped into the grid, and how many of them? Will there also be community-level microgrids serving several individual consumers but ultimately acting as one customer of the grid – a community customer?

How will the load be projected for these new classes? Microgrids may evolve to serve as price responsive load. They may also become suppliers of capacity and ancillary services to the wholesale market. This new paradigm may require an introduction of other new market players – aggregators. Who will it be, and how will they fit into the existing market mix?

Managing data flowing from millions of data sources on a minute basis will be a job of astronomical proportions. Highly complex, large-scale data systems will require high-performance computing taking on a more prominent role in energy sector. Can the industry afford that? The real-time monitoring and long-term load forecasting models will require access to data currently “behind-the-meter” and unavailable to grid operators. How will the issue of data security and transparency be solved? Will the utilities be able to monitor the level of charge and operating conditions of the batteries, and how will this information be built into the load forecast models? How many types of load profiles will be needed to serve one locality?

Unfortunately, regulators have not been on a fast track toward “microgridding,” thus leaving utilities, developers, balancing authorities, and consumers to their own devices. And until a new regulatory reform helps sort it out and put the pieces together, said devices may remain as distributed as the power generation itself.

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