Kay
Lessons from Microgrids Applied to the COVID-19 Crisis
By Trevor Gionet and Kay Aikin
There are parallels between COVID-19 responses and the management of the electrical grid of the future. Concepts like “flattening the curve”1 and” self-quarantine” are concepts not only crucial in the current pandemic, but in electricity distribution systems globally.
While we at Introspective Systems practice social distancing, working remotely, and watching record demands asked of hospitals and the infrastructure that support them, we hear something that is oddly familiar, “flattening the curve.” To those who work in the transmission and distribution environment, this concept is integral to the work we do. Our electricity systems infrastructure is determined by and broken by, peak demands of resources. When we move to a greener grid with greatly expanded renewable generation through microgrids and beneficial electrification of transportation, space heating, and industrial loads, our infrastructure will be impacted by peaks. The nation’s response to the COVID-19 crisis is driven by some of the same principals, flattening the curve (demand response) and self-quarantine (microgrids).
Peak electricity demand has been and will remain the silent killer of the electrical grid. Whether your business is a utility, a manufacturing plant, or a school district, peak electricity charges or the infrastructure required to service them are leading factors in your costs.
For this reason, Introspective Systems is focused on managing peak demands and building microgrids along with layered microgrids that “self- quarantine,” or island, during faults. Our flavor (algorithms) of Transactive Energy (TE), is designed to balance the large-scale demands on our system, orchestrating demand to match generation, while at the same time incentivizing production to be responsive to that changing demand. We do this through a balance of supply and demand, where our Economic Dispatch Value (EDV) responds to changes in the state of the system. Then, by combining the network-wide balancing capabilities of the EDV with local intelligence such as AI-enabled heating systems that forecast future grid states to take advantage of lower electricity costs, we can effectively flatten the demand curve.
These economic systems can drive microgrids or distribution grids and can then be layered as required. Much like the response to the pandemic in Hawaii, where its states are isolating or “islanding” by instituting 14-day quarantine to visitors, they protect themselves from further faults or in the case of COVID-19, new infections.
By economically incentivizing electricity customers to enable automated systems to service their needs, while meeting their demands, we can effectively have coordination throughout the entire distribution and transmission networks.
That’s how we “flatten the curve” and island ourselves.
1) https://www.cbsnews.com/news/flattening-the-curve-coronavirus-graph-social-distancing-self-quarantine-no-large-events-covid-19/?ftag=MSF0951a18
Transactive Energy for Microgrids
Our CEO Kay Aikin wrote a guest blog for Microgrid Knowledge the premier industry newsletter focused on Microgrid technologies and policy.
MRRA Microgrid
Toward Market-based Microgrid Control Systems
The largest machine on earth is often said to be our electrical grid. By the end of 2016 there were some 7600 power plants greater than 1 MW with many times more, smaller resources and an even larger number of control systems. The grid is truly a complex machine that is made up of systems collected into ever larger systems. In the controls world this is called a systems of systems. This is the ultimate in complexity and is true on all large systems like the electric grid and ecological systems.
The advantage of microgrids is they help us tame the complexity the grid by limiting the number of possible interactions within the grid. Smaller more predictable systems are less prone to unintended consequences as can happen in the electrical grid like the Northeast blackout of 2003. However, even with microgrids and the emergence of energy management systems and smart devices the control networks of a microgrid will become even more complex. But this complexity can be used to build better systems as Ecologist Eric Berlow says the more you “embrace complexity the better chance you have finding simple answers”.
A great Ted talk illustrating this concept can be seen at: https://www.ted.com/talks/eric_berlow_how_complexity_leads_to_simplicity
It has been shown that market-based systems can be amazingly stable in complex environments because of the many naturally balancing feedback loops within the system. Using this complexity, to lead to simplicity. In the electrical engineering field, the GridWise Alliance has called this idea of market-based system “Transactive Energy”. Much of the research in this area has been done by the Pacific Northwest National Laboratory and one of the successful trials was the Olympia Peninsula Project (OPP) consisting of a field demonstration of price signal-based control of distributed energy resources. The demonstration showed that market-based control was able to manage distribution constraints and reduce peak loads. This was followed with the Pacific Northwest Demonstration Project (PNDP) ending in 2015.
You can consider there to be three main methods for implementing Transactive Energy control systems applicable to microgrids including:
- Centralized (top down)
- Centralized (auction-based)
- Distributed (edge-based)
The difference between the Olympia Peninsula and Pacific Northwest Project was that OPP was a double auction very similar to the current ISO systems and PNDP was a top down model where demand response assets and distributed energy resources were optimally dispatched by individual “transactive” nodes using two-way communications. Both both were generally more centralized paradigms.
The third transactive approach is a fully distributed edge control method that relies on pricing signals reflecting the prediction of future conditions creating a different price at many different scales. Lower-level devices (or entire systems) respond to those pricing signals from higher levels. This method is currently being researched at Maine’s Brunswick Landing Microgrid Project (add link) for the Department of Energy.
While the first two transactive energy approaches have shown promise in that they have been able to balance energy demand, lowering peak demand and managing grid congestion they rely on large two-way communication networks that are particularly vulnerable to cyber assaults.
This cyber vulnerability should be a concern for the microgrid community because for a wide spread deployment of a system of microgrids this communication vulnerability is of particular concern to today’s infrastructure experts.
The edge-based system being researched at Brunswick Landing has pricing signals (potential of 10 or more different grid scales) are continuously re-calculated, only travel in a downward direction and are acted upon only by edge devices have promise, using the “power of complexity to lead to simplicity” Since the scope of influence of a single node is typically only one or two degrees of separation as described by Eric Berlow, this limits the computing power required to calculate the system state and provides for enhanced capabilities using advanced artificial intelligence techniques and limits security risks with limited communications routes.
An effective transactive edge-based energy system can provide increased resilience, versatility, reliability and flexibility when used not only in microgrids but the greater electrical grid.
Kay Aikin is CEO of Introspective Systems, a complex systems architecture and engineering company in Portland Maine. Introspective Systems is the project lead at the Brunswick Landing Microgrid Project researching edge-based transactive energy networks.