EnergyIoT Article 4 – Operational Technology (OT) Domain - Evolving The Future GridPosted to GridIntellect, LLC – A Veteran-owned Company
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- May 2, 2019 3:45 pm GMTMay 2, 2019 3:39 pm GMT
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EnergyIoT Article 4 – Operational Technology (OT) Domain – Evolving the Future Grid
By Stuart McCafferty, Eamonn McCormick, David Forfia
Disclaimer: The viewpoints in this article and others in the series are the personal views of the authors and in no way are meant to imply or represent those of the companies they work for.
Figure 1- EnergyIoT Conceptual Model
(developed for this series with the Gridwise Architecture Council)
This is the fourth in a series of articles introducing an EnergyIoT Conceptual Model. This article focuses on the physical Operational Technology (OT) Domain within the Model, which is highlighted in the red box on the bottom right corner of Figure 1. The OT Domain envisioned:
- Has intelligence – a “Neural Grid”
- Is nimble and adaptive
- Facilitates rapid interconnect and provisioning of Distributed Energy Resources (DER) and traditional assets
- Empowers transportation electrification
- Is safe, reliable, and resilient
- Is interoperable, including legacy assets
- Leverages all available assets to address grid needs
- Is a bottom-up hierarchical paradigm that builds from highly localized distribution network “atoms” all the way up to transmission level systems
- Is physically and cyber secure
- Is economical
- Is inclusive
- Accommodates opportunities for innovation and new services
The Neural Grid
The centerpiece of the OT Domain is the Neural Grid. It is a bottom-up hierarchy where smaller “atoms” within the grid (e.g. a feeder or neighborhood or street) can aggregate into larger hierarchical structures. Each atom can manage itself with the help of its parent and the rest of the hierarchy.
The simple fact is that the “grid edge” is accelerating faster than the other physical OT layers and the Neural Grid will naturally evolve into a smarter grid than today’s. There are technological advances in control technology, optimization, and power electronics that will be needed to fully realize the Neural Grid. As this type of system matures, the “atoms” could island themselves, completely managing all the resources within its span of control independently of the rest of the grid for extended periods of time. This is years away, but conceptually, this is the type of grid intelligence envisioned, and this architecture is designed to support. In addition, the architecture was designed to allow different parties to participate when and however they can, eventually moving to energy cloud DevOps environments that dramatically simplify and accelerate integrating system components with grid assets. The concept of a Digital Twin Agent will be discussed in “EnergyIoT Article 6 – Energy Services (DevOps) Domain”, as the mechanism that would enable this hierarchical functionality.
Sensors and Measurement
In order to realize a Neural Grid, additional sensors will be needed to provide low-latency feedback for self-awareness, the ability to react to conditions or get help from other parts of the grid, and isolation or self-healing when things go wrong. Grid metrology will need to be much more granular. Real power, reactive power, and phase angles will need to be measured and maintained within acceptable operating ranges on each Neural Grid atom. Digital Phasor Measurement Units (PMUs) will become common-place on transmission and distribution networks. Weather conditions such as temperature, solar radiation, precipitation, and wind measurements will factor in to more granular week-ahead, day-ahead, and hour-ahead planning, and affect electricity market prices.
In the near term, bulk generation will remain an integral part of the generation portfolio, but it will continue to evolve to less and less reliance on fossil fuels. Bulk generation is cost effective and, as the name implies, it supports large populations with high quality power. The problem of bulk generation is the overall cost of operations, the environmental impact of the fossil fuel power plants and the amount of energy lost when transmitted across distances. The preferred fuel mix of bulk generation is changing quickly as economics and policy changes drive fossil fuel plant retirements and incent new grid-scale renewable energy plants getting commissioned.
Figure 2- Bulk Power Plant Retirements and Additions (Source EIA)
The US Energy Information Administration (EIA) reported that “Nearly all of the utility-scale power plants in the United States that were retired from 2008 through 2017 were fueled by fossil fuels.” The majority of those retirements were older, smaller coal plants, with more planned retirements for 2019. EIA reported that 24 GW of planned additions for bulk generation will be made this year, with 64% (15.2 GW) of that through intermittent renewable energy resources.
Reliable, low-latency communication capabilities is equally as important as reliable electron flow. Feedback and control cannot be accomplished without dependable communications. Current communications infrastructure is a combination of radio, fiber, copper, and microwave.
Figure 3- Wireless Technology Speed and Latency
5G networks will have a significant impact on the electric power industry. With fiber-like speeds up to 20x faster than 4G LTE (20GB/s vs 1 GB/s), 5G networks can support low-latency messaging (under a millisecond in ideal conditions) for peer-to-peer and grid-to-cloud communications. 5G is also capable of being highly directional and can establish a direct wireless connection between the tower and grid assets, allowing the asset to communicate with other assets or the cloud with minimal chance of interference. 5G is truly “the killer app” for the energy industry. The EnergyIoT architecture will fully leverage these new capabilities and enable the Neural Grid described earlier.
Aggregators and Community Choice Aggregation
Customers and assets owned or controlled by third parties are already becoming part of the smart grid landscape. In the consumer space, an aggregator serves the power consumer by joining customers together and negotiates on their behalf for the purchase of electricity. For prosumers, an aggregator can combine multiple buildings and negotiates on their behalf to sell services or electricity. In some states, Community Choice Aggregation allows municipalities to opt out of their current regulated utility and negotiate in the bulk markets in order to meet their community’s local needs. Whether driven by costs savings, local economic incentives, or local policies requiring greener generation portfolios, this phenomenon is likely to continue. The architecture recognizes and supports the need for non-utility entities to participate within the OT Domain either as consumers or producers of electricity.
Smart Homes, Buildings, and Cities
The race for home automation capabilities for the masses is finally here. With IP-addressable consumer devices and highspeed connectivity widely deployed and affordably priced, artificial intelligence like Google Assistant (Home Hub), Amazon Alexa (Echo), and Apple Siri (HomePod) are creating the ripe potential for automated management of energy devices. The opportunity to use artificial intelligence to execute human policies as a “Home Energy Management (HEM)” system opens the possibility of participating in real time electricity markets – which operate too quickly for a human at the distribution level. Imagine the not-too-distant future when an energy device (thermostat and HVAC, rooftop solar, electric vehicle, battery or something not yet imagined) can all be managed by an intelligent “robot” (see Build the Grid for Robots - Your New Customer) working in partnership with a much larger ecosystem that balances energy consumption with energy generation from the bottom up. This could also be accomplished by a smart meter or some other intelligent device that appears to grid assets and systems upstream in the hierarchy as a single point of aggregation. In fact, some companies like Span.io are currently investigating the idea of developing “smart panels” inside the home that can act as the point of aggregation and provide continuous improvement in energy management services for the homeowner. This single point of aggregated intelligence is responsible for performing ALL the duties of a HEM, including managing energy usage, storage, and generation, participating in available markets, and possibly allowing the home to operate as an islanded microgrid for some period of time, if necessary.
Over time, technology companies and building energy device manufacturers will be driven by customers to provide interoperable solutions through standards as happened with the personal computers and routers in the 90’s plug-and-play movement. There is an enormous opportunity in this area with explosive growth potential and a vast, unserved consumer base. Standards like IEEE 2030.5 (Home Area Network (HAN)) and OpenADR (demand response) are foundational when looking for true interoperability from central systems all the way to the HAN and Building Energy Management Systems located behind the meter. Simple and bullet-proof plug-and-play interoperability for consumers took time to implement for computers and will take a similar amount of time for electrical devices.
Distributed Energy Resources (DERs)
DERs are arguably the biggest technology catalyst for looking at a different architecture. For the purposes of this document, the authors consider National Association of Regulatory Utility Commissioners’ (NARUC) definition of DER as most appropriate:
“A resource sited close to customers that can provide all or some of their immediate electric and power needs and can also be used by the system to either reduce demand (such as energy efficiency) or provide supply to satisfy the energy, capacity, or ancillary service needs of the distribution grid. The resources, if providing electricity or thermal energy, are small in scale, connected to the distribution system, and close to load. Examples of different types of DER include solar PV, wind, CHP, energy storage, demand response (DR), electric vehicles (EVs), microgrids, and energy efficiency (EE).”
The key point is that DER is normally described as a grid-connected asset that provides distributed generation, a controllable load, or energy storage and are generally small in size and located on the distribution network.
The sheer number and rapid adoption of DER that is creating highly complex challenges for the top-down grid architecture that includes:
- Over-generation due to solar photovoltaic (PV) systems during daylight hours and high ramp rates when people return home and the sun sets (Duck Curve)
- Limited or missing situational awareness of assets behind the meter
- Complex integrated interconnect agreements and systems
- Increased need for additional distributed grid sensor equipment (e.g. Phasor Measurement Units, weather)
- High costs of establishing and integrating DER Management Systems (DERMS) with other central operations systems to manage DER. There are no Enterprise DERMS systems that can manage all DER that include assets that are non-utility-owned and behind-the-meter.
- High costs for communication and supporting systems to integrate DERs
- High costs to maintain DERMS and supporting systems
- Non-standard semantic and protocol communications (or too many standards) with thousands or hundreds of thousands of a variety of assets that create brittle relationships that are easily broken when upgrades or other changes occur
- Errors in long term and short term planning due to inadequate or missing information
- Uncoordinated system restoration, potentially involving large voltage or frequency swings, in the event of a major weather-related event or an emergency load shed event
- Difficulty maintaining and operating power flow models due to inaccurate inputs to the State Estimator and Load Adaptation
- Ability to coordinate and manage DERs to support dynamic response to faults, reactive power needs, voltage control needs, and other grid events
- Distribution-level congestion management
But DERs also create very compelling opportunities to:
- Reduce or eliminate dependence on fossil fuel generation and the associated greenhouse gases (GHG)
- Reduce overall electric power costs
- Create democratized distribution markets and other Distribution System Operator (DSO) functional capabilities (see DSO Models for Utility Stakeholders)
- Increase resilience and reduce restoration times when failures occur
These issues and opportunities are not being met by the current hub and spoke top-down architecture. The old architecture cannot scale at the projected levels to support the policy decisions that are incentivizing or requiring much larger adoption of DER including rooftop solar, batteries, and electric vehicles. The green Energy Services Cloud (DevOps) in the EnergyIoT Conceptual Architecture introduces an abstraction layer designed to simplify and accelerate new DER interconnection and make integration with other grid assets and systems (including those in central operations centers) standardized. This will be discussed in more detail in EnergyIoT Article 6 - The Energy Services Cloud (DevOps) Domain.
Energy Storage DER
Energy storage is a special type of DER that deserves additional discussion. Batteries are the “killer app” for energy systems with the ability to consume, supply, and store power. This is especially true in today’s world of intermittent renewable supply sources and unpredictable (and sometimes mobile) load profiles. The ability to store energy in a DER-rich environment is profoundly important, especially when balancing the potential overgeneration of photovoltaic (PV) systems during daylight hours and the rapid ramp loads when the sun goes down and people return to their homes.
The California Independent System Operator (CAISO) “duck curve” phenomena is discussed in Article 1 – Get Your Head in the Cloud - A Call to Action. The California Public Utilities Commission (CPUC) under the AB 2868 mandate has incentivized its Investor Owned Utilities (IOUs) to install 10 MW and greater energy storage systems at some feeder locations to support the duck curve phenomenon, provide voltage support, and provide electrical islanding opportunities.
Batteries are an obvious potential solution to the duck curve phenomenon. Conceptually, energy storage systems can be charged during low demand or overgeneration conditions, then at dusk combine energy storage discharge and Demand Response programs. This would not stress the grid or exceed thermal limits.
As mentioned in Article 2 – Architectural Challenges to the Energy Transformation, when implementing a bottoms-up “microgrid” building block type of architecture, energy storage is a critical piece of maintaining supply and demand balance and power quality within each building block. Luckily, energy storage is a rapidly growing industry within the ecosystem as prices continue to drop and utilities, microgrid vendors, large industrial customers, and even homeowners become more comfortable leveraging them within their own energy management systems. In fact, according to Wood Mackenzie, the US energy storage market will grow each year by 14 GWh within the next 5 years.
Figure 4- U.S. Energy Storage Deployment Forecast (Source: Wood Mackenzie)
Protecting the physical grid from sabotage, energy theft, and tampering will always be an important foundation for providing inexpensive, reliable, and safe power. Event-driven monitoring of grid assets and analytics that search for abnormal behavior from “bad actors” will provide physical and cyber secure assurances that uses today’s most sophisticated artificial intelligence and machine learning technologies. These capabilities will continuously evolve and “learn” to provide greater and greater security benefits to the grid and its stakeholders.
Security will be discussed in more detail in EnergyIoT Article 6 - Energy Services (DevOps) Cloud Domain.
Electric Vehicles (EVs)
Figure 5 - 2018 Worldwide Electric Vehicle Sales (Source: Forbes)
According to Greentech Media, EV sales increased by 81% in 2018 vs 2017 in the US. In China and Europe, adoption is even greater due to policy requirements and incentives to reduce GHG and pollution. China is the largest EV market in the world with 580,000 EVs sold in 2017. In Norway, 39% of all vehicles sold were electric, which makes them the country with the largest market share in the world.
Every major car manufacturer in the world is announcing EV lines that are already here or will be available by 2020 including Audi, BMW, Chevrolet, Ford, Honda, Kia, Mazda, Nissan, Tesla, Toyota, and Volkswagen.
Figure 6 - U.S. Electric Vehicle Sales & Market Share
EV adoption is currently accelerating at rates that no one anticipated 5 years ago. The growth in EVs is challenging to utilities and the grid infrastructure. It spawns enormous electricity demand that can push transformers, wires, and other grid assets to their thermal limits if not coordinated. In fact, the US Department of Energy’s Energy Information Association (EIA) predicts that electricity demand from EVs will grow anywhere from 10x to 30x in the next 20 years.
Figure 7 - Projected Electric Vehicle Energy Demand (Source: Energy Information Agency)
Electric Vehicles are truly one of the most transformative catalysts in the electric power industry that require increased grid-to-vehicle awareness with completely different requirements for protection systems and the ability to cohesively coordinate charge and discharge large numbers of EVs at each grid constraint location serving them. This is a gap and is incredibly complex to manage using existing centralized command & control architectural model. Localized grid intelligence, standardized message communications, and scheduling of these “mobile DERs” that can charge, discharge, and store electricity will be more achievable with a middleware abstraction layer that provides common services. This will allow the local grid intelligence to identify when an EV plugs in, what the current constraints are at that location, and schedule chargepoint services that meet the needs of the EV owner without endangering other grid assets.
Today’s grid is a patchwork of legacy assets that in most territories struggle to meet the needs of the communities they serve. As the energy demands of the 21st century continue to accelerate worldwide and the expectations from stakeholders increase for reliability, power quality, transportation electrification and the scalability to support large numbers of renewables and other DER assets, more investment will be required to transform today’s grid to one that is much more adaptable and nimble. This can and must be done over time and will require new innovation and careful planning aligned with significant infrastructure investment.
Unfortunately, the reality is that the current top-down architecture and centralized command and control is unlikely to support the needs of electric power stakeholders going forward. It is time to think differently and leverage today’s advanced technologies and prepare for the next technologies like 5G communications, autonomous EVs and high penetration solar PV. There is a need to couple these with intelligent decisions and a bottoms-up, data-centric, event-driven architecture that can rapidly adapt both the physical grid and business systems as new assets enter and exit local grids.
This is the fourth in a series of EnergyIoT articles addressing the current challenges being experienced and proposing a fundamentally different architecture to solve the problems of today and tomorrow. The fifth article, “EnergyIoT Article 5 – Energy Systems Domain”, will be published next week on Energy Central and LinkedIn.
 NARUC DER Manual, pg 45.
 The authors believe that Energy Efficiency (EE) is difficult to include in DER conversations since it is not a “controllable” asset. However, we recognize that EE is a worthwhile investment to consider when managing load profiles whether it is defined as a DER or not.
The rest of the article series can be found here:
About the Authors
Stuart McCafferty, IoT Architect, Black & Veatch
Stuart McCafferty is an accomplished Smart Grid technical executive with an innovative history, strong relationships in the utility and vendor communities, business and partner development, platform and solution design, go to market planning and execution, and practical application of existing and emerging/disruptive technologies. Prior to B&V, he was VP of EnergyIoT for Hitachi America, where he led the architectural design of a distribution system platform supporting microgrid and Distributed Energy Resource (DER) related businesses. At B&V, Stuart supports the utility, technology, and vendor communities in strategy and pragmatic application of DER that combines IoT best practices and technologies with energy standards and protocols.
Thought leader in the Internet of Things (IoT), Big Data, Cloud Computing, Artificial Intelligence (AI), Machine Learning, and connected home with practical application within the Smart Grid ecosystem. Expert in utility IT/OT and the application of DER and microgrids for resilience, economics, and reliability.
Stuart is a US military veteran, Air Force Academy graduate, an Energy Fellow for community resilience at the National Institute of Standards and Technology (NIST), an Energy “Expert” for Energy Central, and Vice Chair of the Open Field Message Bus (OpenFMB) user group.
David Forfia, Gridwise Architecture Council Chair
David is the Chair of the GridWise Architecture Council since 2015 and has been a council member since 2013.
The GridWise Architecture Council (GWAC) is a team of industry leaders who are shaping the guiding principles of a highly intelligent and interactive electric system. The Council is neither a design team, nor a standards making body. Its role is to help identify areas for standardization that allow significant levels of interoperation between system components. More about the Council can be found at www.gridwiseac.org
David is the current chair of the Technical Advisory Committee and a former member of the Board of Directors of the Smart Electric Power Alliance. He was also Chair of the SGIP Board of Directors from 2015 until 2017, and as a board member beginning in 2011.
In his current role, he is the Director of Technology Architecture and IT Transformation at the Electric Reliability Council of Texas (ERCOT). He began his career at Austin Energy Director of Information Technology Services for Austin Energy and was Deputy Director and Chief Information Officer for an $18B pension fund. He holds a BBA from the University of Texas at Austin and an MBA from St. Edward’s University.
Eamonn McCormick, Chief Technology Officer, Utilicast
Eamonn McCormick is the CTO at Utilicast, a leading energy industry consultancy. Eamonn is a passionate believer in the bright future of the energy industry and the importance of collaboration as the foundation for solving for our current industry challenges. He is a results driven technology leader with a track record of success. He has implemented strategic technology change at several large energy companies over the last twenty years in the areas of wholesale markets, transmission and energy distribution primarily. In addition Eamonn is currently chief architect of the Energy Block Chain consortium.