The historic winter that hit Texas in February of last year broke all illusions that our grids are designed to handle the effects of climate change. As such, how we design energy projects needs to evolve with this climate reality. In the past, planning used to be much simpler because there weren’t as many moving parts. Now, there are a multitude of factors that impact how an energy project is designed and ultimately implemented to maximize profitability and efficiency.
This modern process played out in Plano, Texas, at a large shopping mall. Our team recently partnered with Empower Energies for a client that didn’t know they had a problem until it was too late. Due to the extremely cold temperatures, access to natural gas fuel was restricted, leading to massive power outages while prices skyrocketed. As a result, in a single month, their utility bill was 36 times higher than normal.
Despite having a solar system installed over their parking lots, there was no way to capture excess power during low peaks in demand and less extreme weather. Requiring power to about a dozen buildings, they needed to connect a battery storage system with their solar hardware so that they could capture excess energy and tap into it when needed.
After discussions with the client, we identified three project goals:
● Minimize surprise bills and make them more consistent and predictable
● Ensure the shopping mall sources at least 50% clean energy throughout the year
● Offset project costs through additional revenue opportunities
Having already picked a battery vendor, an analysis was done on how to configure it. These were the options: charge batteries exclusively from solar power, retain full solar investment tax credit (ITC), or take a hybrid approach that leverages both grid power and solar. Factoring in their goals, having that flexibility to charge both from the grid and solar maximized their revenue opportunity.
One might assume – without using AI to analyze price spikes – that higher prices would occur during the same times in the future. However, the analysis uncovered that the common periods of high prices had a 13% share overall. That means 87% of the high prices occurred during other times. Because energy prices are so volatile, missing a single spike can ruin a day’s revenue-generating potential, which is why accurate forecasting is so critical in planning these types of projects.
In the end, four key value streams surfaced, which required AI to plan and operationalize to strike the right balance in real-time. These include:
AI helped determine the optimal size for the battery energy storage system (BESS), allowing the client to hit on these four value streams. In addition, it led to the decision to build a larger battery storage system. Not only was it still financially viable, but it also enabled the facility owner to meet their carbon reduction target in the first year. This was achieved by using on-site solar production and offtake via a virtual power purchase agreement (PPA).
To improve total return on investment even further, AI-driven analytics identified three other opportunities to optimize the final design of the operations. By charging the batteries through onsite solar and striking the right balance between charging and discharging to the grid, they remained eligible under the federal ITC. And lastly, operating the storage and solar operations independently of each other increased the BESS economics as a tradeoff that enhanced the payback period of the total renewable energy system.
Now, in the event of another severe storm or other disruptive weather patterns, the facility has the means to stay in compliance with the company’s environmental goals and harden itself to prevent high utility bills and energy loss. And since they now have the optimal system in place to charge and discharge from their batteries, they can unlock revenue opportunities that they can take advantage of throughout the year.
By Ben Sigrin, Director of Product and Data Science, Veritone
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