No matter what the extreme weather situation is, strain on the grid is increasing. In general, it matters less these days to a utility how much energy is needed; more important is when and where energy needs to be distributed.

How to Beat the Heat (waves)

Larsh Johnson | Stem

Please tell us a bit about Stem and your role in the alternative energy industry?

Stem is the leader of artificial intelligence-driven energy storage services, and we are dedicated to transforming the way energy is consumed and distributed. With energy storage, the question is no longer “if,” but “when” it will be needed. Real-time energy optimization is an absolute necessity as consumers demand more control over their energy decisions, and utilities need to modernize an increasingly decentralized grid fed by variable renewable energy. The world needs energy storage with software-enabled energy superintelligence that can perform multiple services—to benefit customers by reducing their energy bills while dispatching a storage network that helps utilities and grid operators relieve the overall stress on the grid. So our cutting-edge AI platform, Athena, optimizes energy use in real time and enables higher penetrations of renewable energy on the grid. Our mission is to create a more efficient and modern grid for all while empowering users to better manage their energy use.
 

We know extreme weather can impact consumers’ power bills, but how are extreme weather patterns, like the current heat waves impacting California and Texas, affecting energy grids? Does the same apply to extreme cold?

No matter what the extreme weather situation is, strain on the grid is increasing. In general, it matters less these days to a utility how much energy is needed; more important is when and where energy needs to be distributed. For example, Utility X may need it on these distribution circuits here right now, but maybe over there in the next hour. Traditional generation assets can’t provide that localized, fast-dispatch response that you can get by leveraging customer demand for intelligent energy storage and aggregating those customer sites into responsive networks of flexible energy. But then when you add in either cold or heat spikes, the grid needs more relief. We’ve had cold-weather induced spikes where natural gas demand for heating caused shortages for electric generation. And in California, this week, the heat waves are causing a rare phenomenon—Day Ahead market prices have skyrocketed to above $1000/MWh and in some zones for 11 hours straight on July 24. That’s half the day! So we’re getting called a lot to help relieve grid stress this month.  
 

Does energy storage help mitigate some of the previously mentioned affects? If so, can you explain how?

There’s something important to note here: Over fifty percent of a typical utility bill can be caused by unexpectedly high demand, triggering a “demand charge.” So during these periods of extreme weather, the energy consumption is through the roof and the strain on the grid is high. By incorporating storage, particularly with an AI like ours, that strain is mitigated. We have a number of grid-facing contracts and electric rate programs, such as our 85 MW contract with Southern California Edison for local capacity in the highly congested West LA Basin.  So far in July, we have executed on 97 calls across our programs and contracts as heat waves spiked demand for energy across the state.

 

When considering energy storage’s relationship to extreme weather events, what’s the number one thing my readers should know?

Plain and simple: AI-driven energy storage offers reliable, flexible, and fast-dispatch resources to the customer, utility, and grid operator. That customer demand, to control their energy decisions and participate in the energy markets in new ways, means that customer-sited storage will scale in the coming years, and in so doing, offer intelligent resources—again, at scale—to state energy planning.
 

How can advanced technology integrating with energy storage—in Stem’s case, your AI, Athena—change the efficacy or impactfulness of energy storage and behind the meter technologies in general?

With energy storage, it’s all about the software. Our AI platform, Athena,  has the most experience in the field. We’ve had projects operating since 2012, we have over 400 systems installed across five US states, Japan, and Ontario Canada (with approximately 500 more underway), and those existing sites creates millions of runtime hours and terabytes of data stored to our cloud from one-second data captures. That data feeds our predictive analytics, enabling machine learning for our algorithms to self-improve. Additionally, our AI has to analyze a range of other high-speed data, like weather, market data, the building’s energy behavior, utility tariff options, and available market opportunities, to determine for the customer which will deliver the most value. Athena leverages this information in real-time, in fast-changing energy markets, to optimize energy storage for the individual site and in consideration of the hundreds of sites in the Stem network.  
 

Can you describe how your technology is implemented in a real world scenario? Who are the players and how do they work together to make a system happen?

A great example is our 85 MW contract with Southern California Edison that I mentioned earlier. We’ve signed dozens of customers, including Fortune 500 leaders and public sector institutions, to provide them with long-term energy savings “as a service” on a monthly subscription basis. Whole Foods is a good example who has partnered with Stem in the Hawaii and California markets. Stem expects to save them over $500k in ten-year net energy savings across seven stores by using stored energy during periods of high electricity use. When the energy storage system is not needed on-site, we can call upon it and other systems in our network to provide that needed capacity for the utility. And our customers are winning awards for using energy storage in their energy management planning: LBA Realty and California State University at Dominguez Hills both won the 2018 Smart Energy Decisions Innovation award for relying on Stem’s AI-driven energy storage services.
 

When this tech is applied, does its impact on consumers and grid operators differ? If so, how?

The game-changing opportunity of software-driven energy storage compared to other grid resources is that it can provide multiple services for different stakeholders within the space of a day. So we’re helping non-residential customers reduce their demand charges and save money on their energy bills. But we’re also providing local capacity, aggregated demand response, or other grid-firming services to the utility or grid operator, depending on the territory and its particular needs. Both benefit.
 

What’s the future for energy storage, and AI in energy space more broadly?

Energy storage is a growth market in all senses of the word. Demand for energy storage’s unique capabilities will continue to grow, among not only commercial and industries customers, but utilities as well. AI-driven energy storage will continue to improve the security and reliability of onsite and offsite renewable energy. We’re seeing increased investment across the board in energy storage, even among traditionally conservative investors, because of the strength of the business model. Energy storage is increasingly a necessary component to the energy ecosystem, and likewise, AI will remain an essential component. Even with the ability to store energy, there are still thousands of calculations, forecasting simulations, and split-second decisions required to produce meaningful results and only machine intelligence can perform this work. AI can simply compute on a level that isn’t possible or practical for most organizations or utilities to do manually, with benefit to the customer and the grid. So I believe customer-sited energy storage will scale as large and perhaps faster as we saw with distributed solar, and it seems many industry analysts agree, such as Greentech Media’s quarterly U.S. Energy Storage Monitor.

 

 

About Larsh Johnson
As Chief Technology Officer, Larsh Johnson leads hardware and software engineering to meet the unique needs of Stem’s C&I, utility and energy market customers. Prior to joining Stem, Larsh was Chief Technology Officer at Siemens Digital Grid, where he led technology development teams on products spanning from consumer metering, demand response and analytics to control center software and grid automation.

 

The content & opinions in this article are the author’s and do not necessarily represent the views of AltEnergyMag

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