This guide on distributed energy resource management system (DERMS) is Part 2 of our ongoing series on Smart Grid Technology. Read on to learn more about the role a DERMS play in helping asset managers and grid operators control energy costs, reduce carbon emissions, and ensure more reliable electricity delivery.
- What Is Distributed Energy Management?
- The Role of a DERMS in a Smart Grid
- What Are the Benefits of a DERMS?
- Use Cases of DERMS Technology
- The Role of Artificial Intelligence in a DERMS
- Conclusion
What Is Distributed Energy Resource Management?
Distributed energy resources (DER’s) are the full spectrum of solar, wind, storage, and even electric vehicle (EV) assets that feed electricity into and take electricity out of the larger utility network. Because edge devices like rooftop solar photovoltaic (PV) installations are often privately owned, they exist outside the direct control of grid operators. However, there is a growing push to provide utilities and asset managers with better tools to balance electricity production, storage, and delivery across the network.
A distributed energy resource management system (DERMS) is the combination of hardware and software that allows real-time communication and control across the batteries, solar panels, and other edge devices that normally lie behind-the-meter and outside grid operators’ direct control. This integrated management system relies on both sensors and receivers to facilitate network-wide coordination:
- Sensors on edge devices send real-time data to the grid, alerting operators to changes in energy storage and production. For example, a utility provider might receive a notification the moment a customer’s PV installation generates 25% less power due to passing cloud cover.
- Receivers on distributed energy assets intercept instructions sent by the grid to accommodate fluctuations in power production and storage. For example, a utility might remotely redirect some of the energy stored in another customer’s solar batteries to account for a sudden dip in wind power generation somewhere else in the network.
Distributed energy management systems work in concert with other smart grid concepts – including microgrids and resilience – to optimize resource allocation and ensure smoother electricity delivery for everyone within the network:
- Microgrids are aggregated and localized DER’s that function as independent but grid-connected power plants. You increasingly see them on campuses and industrial parks that are equipped with their own blend of on-site solar, storage, and EV-charging assets.
- Resilience describes the redundancy built into grids so that a malfunction in one section of the network doesn’t negatively impact grid operations as a whole. The concept is similar to data centers or blockchain technology – both of which use distributed, redundant backups to mitigate the frequency and severity of disruptions to the larger system.
What Are the Benefits of A DERMS?
With a traditional grid, power generation is centralized at the utility level and distributed to area communities via transmission lines in a spoke-like fashion. However, the growing popularity of consumer solar power, commercial wind farms, and other privately-owned distributed energy resources has changed the landscape – making it harder for grid operators and asset managers to balance supply and demand. That these edge devices are behind-the-meter and outside any centralized control produces a litany of problems for grid operations, including:
- Overproduction and dumping
- Underproduction and shortages
- Surges and equipment malfunctions
- Disruptions and blackouts
- Islanding and personal injury
- Phase load imbalances
- Unnecessary pollution
DERMS’s allow grid operators to smooth out peaks and valleys across the network, so that:
- Energy production becomes more manageable
- Electricity prices become more predictable
- Power distribution becomes more reliable
Use Cases of DERMS Technology
Below is a hypothetical snapshot of how grid operators might use DERMS technology to optimize the energy network:
- Cloud cover makes rooftop solar production suddenly drop in the city’s largest residential neighborhood.
- Grid operators immediately scale up production at its coal-burning plant to help balance out decreased energy supply. Being a Saturday, they also temporarily switch the city’s fleet of electric school buses to “slow-charging” to build more slack into the network.
- The clouds eventually pass just as wind production also picks up. The neighborhood’s collection of rooftop solar assets are now working at full capacity – bolstered by windfarms on the outskirts of town.
- With a sudden boost in citywide energy generation, the utility scales back its coal-burning plant. It also enables “fast-charging” for all grid-connected batteries and EV’s to store any excess power.
Variations of this exact scenario happen continuously, with DERMS’s using sensor data and receiver communications to better coordinate energy generation and storage across distributed, grid-connected assets – all in real-time.
The Role of AI in A DERMS
Even a well-designed distributed energy resource management system faces limitations if human actors are guiding all decisions. Grid operators and asset managers already struggle to meet demand with the resources they directly control. Managing thousands of edge devices – and many terabytes of real-time data – is nearly impossible.
However, managing Big Data isn’t a problem for artificial intelligence (AI).
AI can continuously monitor edge devices and make real-time decisions about resource allocation – based on current demand, supply, weather conditions, and a host of other constantly evolving variables. At Veritone, our AI solutions for energy can also use historic data analysis and predictive modeling to make incredibly accurate forecasts about how these variables will impact the energy landscape seconds, days, and weeks into the future. With this data, our AI software can then optimize and control edge devices to ensure smooth electricity delivery at the right time, place, and price.
A useful analogy of AI’s potential comes from traffic management, with many municipalities now equipping their own traffic lights with sensors to relay data and receivers to intercept instructions. Cities around the globe are increasingly using AI to coordinate street lights, minimize congestion, and ensure everyone reaches their destinations faster.
When applied to energy management, the principle is the same.
Veritone Energy’s machine learning technology is designed to help grid operators and asset managers coordinate distributed edge devices, minimize grid congestion, and ensure electrons reach their destinations.
Conclusion
Distributed energy management systems are central to a smart grid design. They allow for better coordination so that all end-users receive the most reliable power at the best possible price. DERMS’s are also critical to the larger decarbonization movement given their ability to integrate intermittent and unpredictable renewable energy resources like solar power into the grid.
Simply put, the planet will never eliminate fossil fuels completely without DERMS’s, or any equivalent technology, helping to bridge the gap.
As important as distributed energy resource management systems are, however, they represent just one component of intelligent smart grid design.
To learn more about the other key technologies at play, visit the resources below.
- The Ultimate Guide to Smart Grid Technology and Benefits
- Autonomous Microgrid Technology
- Grid Resilience and Continuity
- AI-Powered Electricity Grids and Autonomous Newwork Management
You may also enjoy this 30-minute podcast that introduces the challenges of smart grids and highlights some of the benefits of AI to improve energy and utility operations.