For the first time in decades, electricity demand is rising, driven by industrial growth, data center energy demand, and record-breaking adoption of distributed energy resources (DER) like electric vehicles, backup batteries, and rooftop solar.
As utilities support this transition, reliably operating the grid is becoming dramatically more complex. Many utilities are already seeing significant grid impacts from distributed energy resources, including overloading of transformers and backfeeding on distribution circuits.
With the grid impacts of distribution-connected devices expected to grow over the next decade, utilities are recognizing that they need to better manage DERs and demand response in coordination with core grid operations.
Historical investments in Distributed Energy Resource Management Systems (DERMS) and Demand Response Management Systems (DRMS) have often treated flexibility at the grid edge as the purview of customer-facing teams, rather than a core component of day-to-day operations and planning.
Utilities now find themselves with solutions that can reliably turn DERs on and off, but lack the comprehensive visibility and awareness needed to incorporate local resources into traditional grid management.
As such, utilities repeatedly find that DERMS and DRMS implementations stop short of the utility’s end goals – enabling system-wide peak management but not the precise, location-specific management that utilities need to support sustained load growth.
To fill this gap, a new class of utility software systems—called grid orchestration platforms—is designed specifically to manage the grid with the help of local resources.
Grid orchestration refers to proactively dispatching local resources, from electric vehicle chargers and smart thermostats to substation-sited batteries and industrial loads, to manage distribution network capacity and optimize the use of existing grid infrastructure. To achieve this, a grid orchestration platform combines four key capabilities in a single interface:
Grid orchestration platforms, including Camus’ own platform, work in concert with existing utility software systems to deliver data-driven, real-time management of the grid through local resource flexibility.
The four key capabilities enabled by an orchestration platform are all supportive of the long-term transition of utilities into acting as Distribution System Operators (DSOs).
DERMS solutions have been deployed by utilities around the world to manage the behavior of distributed energy resources. Those familiar with the concept of a DERMS – as defined in industry guides like SEPA’s Encyclopedia of DERMS Functionalities – may well think: doesn’t DERMS provide orchestration already?
Unfortunately, the reality of real-world DERMS implementations is that they routinely differ from what’s described in industry white papers and marketing briefs. Today, most DERMS solutions fall into one of two subcategories:
While both subcategories can provide benefits to utilities, neither provides a fully scalable solution to incorporating DERs into core operations and planning.
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“Edge” DERMS software platforms enable utilities to enroll, connect, and control large numbers of smart thermostats, water heaters, batteries, EVs, and other distributed devices. They offer expansive portfolios of direct device integrations and often leverage device and customer data to forecast future load and available flexibility.
Put succinctly, edge DERMS are great solutions for dispatching large numbers of DERs for grid-wide services – such as reducing peak demand.
However, these platforms do not know the location of DERs in relation to upline grid equipment, nor do they incorporate awareness of local grid conditions. As a result, when utility operators use edge DERMS to turn resources on or off, they are blind to how their actions impact the grid above the meter.
This approach limits the ways in which local resources can be harnessed for grid support. They can shave peaks, address a shortfall of generation, and reduce wholesale power supply costs. But an edge DERMS is not suitable for ensuring that large loads like EVs and batteries remain within available grid capacity. For example, an operator cannot see if pre-charging a fleet of EVs ahead of a system peak is overloading transformers or conductors.
As utilities increase their usage of these energy resources to shift power demand, grid-blind control can create new problems, such as coincident and localized peaks in high EV adoption areas.
The lack of comprehensive locational and real-time data on the impact of these devices can also cause problems with other key utility workflows, such as distribution automation and outage restoration.
Centralized DERMS seek to expand upon the capabilities of an Edge DERMS by providing enhanced grid awareness through direct integration with the utility’s key operational systems – especially the Advanced Distribution Management System (ADMS).
An ADMS is a core utility operational software system providing a range of distribution optimization capabilities including voltage management and outage restoration. An ADMS is among the most important systems utilities use to keep the lights on.
In theory, centralized DERMS combine control of local resources with grid awareness and short-term forecasting. But in practice, they fall short. This happens for two reasons:
The grid awareness capabilities of centralized DERMS rely on the accuracy and availability of a utility’s physics-based power flow model. This occurs because centralized DERMS do not have access to comprehensive real-time data about the state of the system.
Instead, to dispatch DERs, a centralized DERMS runs a full physics model of current and future grid conditions – a slow and compute-intensive process. The physics model provides a view of what’s likely to happen based on the DER dispatch instructions, but it has no ability to monitor their real-world grid impacts.
The model-based dispatch approach relies on distributed devices perfectly responding to dispatch signals from the utility. As more DERs are aggregated into Virtual Power Plants (VPPs), especially those operated by third-parties as mandated by FERC Order 2222, the inability to see how devices actually respond to dispatch instructions will become a severe impediment to managing the local grid impacts of DERs.
In addition, keeping the utility’s power flow models highly accurate requires updating records for millions of pieces of utility equipment, which can be extremely costly and time-intensive. The data cleanup involved to launch grid-aware management of DERs using model-based approaches can cost a utility ten times as much as the DERMS software.
And as more local energy resources are deployed on the grid, more equipment will need to be fed into these models, increasing the cost and challenge of maintaining near-perfect models.
In addition, the analytics and forecasting capabilities of a centralized DERMS become severely limited when these systems are deployed “on-premises” or via “hybrid cloud” solutions. Nearly all centralized DERMS take one of these two approaches today. As DER adoption increases, the amount of data ingested by the utility grows exponentially and the cost of on-premises and hybrid compute capacity quickly becomes unsustainable.
As a result, utilities throw out large volumes of useful data and settle for lower quality analysis and forecasting – hindering their ability to solve real-time operational problems.
We’ve spoken with several utilities who have attempted to deploy a centralized DERMS from the same vendor that provided their ADMS. In such deployments, they were able to successfully control a moderate number of DER resources, but were not able to expand that control across numerous programs or provide integrated grid-wide visibility.
This approach proved to be slow and costly to operate—and not practical for making real-time decisions or for integrating rapidly proliferating DERs into grid operations and planning. As a result, these utilities are now seeking orchestration partners with “cloud-native” architectures, which scale more reliably and affordably.
Instead of relying on near-perfect grid models and limited on-premises or hybrid cloud computing capabilities, a grid orchestration platform takes a data-first approach to managing DER impacts.
The platform leverages any and all data—from customers, devices, utility systems, and third-party sources—to identify devices connected to the grid, what they are doing, and how they affect the grid in real-time and in the near future. Connectivity models and physics-based simulation inform and enhance the orchestration system, filling data gaps and simulating specific future conditions.
“Taking a data-first approach enables our customer utilities to gain resilience to model drift: where their network model results differ significantly from observed real-world conditions.”
Astrid Atkinson, Camus CEO & Co-Founder
With the low cost and scalability of a cloud-native architecture, utilities can harness all available data and rapidly flex computing capacity up and down – providing a more accurate view of grid conditions at a more affordable cost, and allowing for huge numbers of servers to be utilized temporarily for model building and online state calculation.
Using this approach, an orchestration platform can manage millions of DERs, including devices controlled by third-party aggregators.
A grid orchestration platform is intended to complement, not avoid or replace, investments in DER and demand response management. For utilities who have already invested in a DERMS or DRMS, a grid orchestration platform unlocks more value from those investments by enabling precise, grid-aware dispatch across all resource types.
For utilities with limited DER or DR management capabilities today, orchestration provides a foundation for improving visibility ahead of a DERMS or DRMS deployment.
Orchestration complements utilities’ varying approaches to managing local resources in six key ways:
Integrating with existing DERMS or DRMS solutions provides the orchestration platform with information on the available flexibility across utility programs and systems.
For example, a DERMS may know that a thousand smart thermostats can provide 800 kilowatts of demand reduction during a specific hour while the DRMS knows that 5 MW of flexibility is available from commercial and industrial facilities during that same hour. The orchestration platform surfaces the availability of both resources to operators in a unified interface to help them decide when and where to shift loads.
A grid orchestration platform provides the robust grid awareness that Edge DERMS and DRMS lack. The platform gathers and integrates data from utility systems like supervisory control and data acquisition (SCADA), advanced metering infrastructure (AMI), and geographic information systems (GIS).
This enables the utility operator to monitor grid conditions, see how they are affected by DER behavior, and dispatch local energy resources to provide the optimal benefit to the grid.
Aggregating large numbers of behind-the-meter, flexible resources into utility-operated virtual power plants can be a powerful tool to provide capacity and power supply flexibility. While a DERMS can aggregate diverse types of DERs, a grid orchestration platform uses grid awareness to send intelligent, grid-friendly dispatch instructions to these aggregations – providing a smarter way to operate utility VPPs.
Unlike most Edge DERMS, a grid orchestration platform can provide direct control of utility-owned, front-of-the-meter (FTM) assets, such as solar and battery storage, in coordination with behind-the-meter DERs at homes and businesses. This can help utilities optimize the operation of local resources for cost savings and local reliability needs.
In addition to a DERMS’ focus on resources directly enrolled in utility programs, a grid orchestration platform can interface with third-party aggregators (also known as non-utility VPPs) to procure valuable grid services. The platform can communicate location-based operating constraints to aggregators to ensure safe dispatch while expanding the pool of available flexibility.
Utilities often struggle to leverage data on existing DERs to inform future system planning. An orchestration platform spans the Operations and Planning silos, enabling planners to use real-world data from DERs to simulate the impacts of future device adoption. Doing so can help identify major savings opportunities, including distribution equipment deferral, non-wires alternatives and bridge-to-wires solutions.
For utilities with an ADMS, a grid orchestration platform makes it easier to scale monitoring, analysis, and control of DERs while supporting the ADMS’s mission-critical functions. An ADMS typically has a robust view of the grid down to the transformer level, and a grid orchestration platform can extend this view down to the grid edge.
For instance, Camus’s orchestrator has a meter-level forecasting capability that provides accurate day-ahead, hourly load predictions for every point on the grid, including specific transformers and conductors. It can also “nowcast” load for these assets, addressing the delay in receiving data from smart meters.
These forecasts inform how the ADMS executes outage restoration, fault location, automated switching, and other distribution optimization activities—and ultimately helps utilities get more out of their ADMS investment.
A grid orchestration platform can also implement flexible interconnection approaches that enable utilities to approve solar, EV charging, and other DER projects by curtailing their output or load only when grid constraints arise.
Consider this scenario: the ADMS informs the orchestration platform that it wants to switch the configuration of feeders, and the orchestrator in turn curtails output or load of local DERs to ensure safe, reliable switching. Flexible interconnection, which is likely to grow more common as DER penetration grows, can increase a feeder’s capacity to accommodate more EV charging or solar without grid upgrades.
The ADMS can also share connectivity and switch state with the grid orchestration platform, enabling the latter to generate feeder- and transformer-level grid constraints. The orchestration platform then allocates these constraints across downline DERs, calculating bounds on how much power each device can import or export at any given moment. The orchestrator accounts for voltage violations, circuit overloading, and other impacts and dispatches DERs in a way that supports overall grid needs.
By performing these functions, the orchestration platform is removing the burden of analyzing grid-edge resources from the ADMS so it can devote computing power to outage restoration and other critical real-time applications.
Utility leaders may wonder why grid-aware DER management is needed today, when the penetration of resources remains limited in most regions.
The reason is quite simple: the timeline for deploying grid infrastructure is much longer than for consumers adopting EVs, batteries, or distributed solar. If utilities wait for high penetration of DERs to get started, they’ll find themselves years behind – and struggling with rising costs, reliability challenges, and unhappy community members.
Consider the implications of continued rapid EV adoption. Utilities are facing a growing need to upgrade transformers and reconductor power lines to accommodate load growth from EV charging. A reactive approach—upgrading grid assets as local EV charging loads exceeds available grid capacity—will result in extremely high grid infrastructure costs.
A medium-sized utility may need to invest tens or hundreds of millions of dollars in line reconductoring, significantly raising its customers’ costs. Equally important, these expenditures are likely to be first distributed to wealthy communities with early adopters, leaving fewer resources available for low- and medium-income communities.
Deploying a grid orchestration platform now is a crucial, proactive step that utilities should take today to manage costs over the next decade. Rather than raising rates to pay for upgrades in wealthy areas, utilities can harness local energy resources to improve the efficiency and flexibility of their grids.
That’s the path that Camus’ utility partners, including PPL Electric Utilities and Kit Carson Electric Cooperative, are taking to deliver on their ambitious reliability, affordability, and carbon reduction goals.
And it’s the path that we encourage more utilities to pursue in support of an affordable, reliable, and equitable energy transition.
Camus works with electric utilities of all sizes to manage the pace of electrification and load growth. If your utility is exploring how to engage local resources, we'd love to help.
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