We live in the 21st century, in a world where cutting edge technology is at our fingertips. We carry a portal to the world’s entire body of information in our pockets everyday. Have a problem? There’s an app for that!
So it’s logical to assume that there’s a straightforward, software-based solution to tell you exactly what kind of energy assets you should purchase and install and how to operate those assets.
This is not a great assumption.
In his book, The Design of Business, Roger Martin describes the path of maturity for any technology or industry as having three stages: Mystery, Heuristic, and Algorithm. When, as a design community, we set out to innovate and solve new problems (like, say, replace centralized fossil-fuel energy resources with clean, sustainable, renewable, resilient distributed energy resources, or DERs), we necessarily start in the realm of Mystery. What are the actual problems we need to solve? What are the biggest challenges to overcome? How can we figure this out? In the Mystery phase of innovation, every project is unique. Every client has their own needs, preferences, and challenges. Solution providers must listen critically to these diverse parameters and provide individualized solutions.
After a set of these highly individualized solutions are developed, patterns start to emerge. We as a design community start to develop Heuristics, or rules of thumb, and a certain amount of intuition about what’s going to work and what doesn’t. There are still humans in the loop here, but we are able to develop software tools to start to codify these rules of thumb to make the feasibility and design processes easier, faster, and more reliable.
Only after a period of time in the Heuristic phase can an industry move into the Algorithm phase of maturity, in which we are able to standardize and fully automate the decision making processes that previously required so much intervention. In order for this to happen, inputs to the process need to be standardized, the outputs agreed upon, and the uniqueness of the solutions minimized.
The thing is, the new energy industry is not yet in the algorithm stage of maturity. This feels silly, because the traditional energy industry is old and seen as an area lacking in innovation. But here we are on the cusp of seeing our entire energy infrastructure undergo a total butterfly-like transformation, and innovation is at the core of that transformation. Everything old is new again, and we as an industry find ourselves back at the Mystery and Heuristic stages of technology development.
The new energy industry is just not ready for full automation of the feasibility, design, and operational processes. It is coming. We will get there. Some energy applications (solar) are more advanced along the path of maturity than others (energy storage, energy trading). But for now, you should absolutely want to have a human in the loop while designing and deploying energy systems.
Here are five reasons you should always want human eyes on whatever analysis you commission to design, build, and operate systems of DERs:
Utility tariffs are non-standard and highly complex
Utility bills, tariffs, and rate structures are critical inputs to energy feasibility and design analysis. These bills reveal the most important revenue streams for behind-the-meter DERs — primarily demand charge reduction and avoided energy costs, not to mention frequency regulation and other ancillary services. And understanding of these tariffs is absolutely necessary to evaluate the economic performance of an energy system.
To say that utility tariffs are not standardized is a laughable understatement. Sometimes they are so highly complex and varied that it is difficult for even a human to parse them. Utility tariffs have never reached the standardized level of Algorithm because they never had to before. Each utility operates in its own little world, in its own market, and has never had any reason to standardize either the rate structures to which it subjects its customers or the format in which the charges are communicated.
Since the utility input cannot be standardized at this time, it’s nigh unto impossible to standardize the process for including these bills in analysis without human intervention to validate and format the rate data.
Load profiles are available in varying levels of fidelity and applicability
The second critical input to energy system design analysis is the load profile. The load profile is derived from the operational strategy for the site, which drives the energy needs to which we are designing. The trouble is, sometimes even getting a load profile at all is a challenge, as smart meters are not currently universally deployed. Data is available in a wide variety of formats and granularity. Standards like Green Button and Orange Button Data are trying valiantly to fix this problem, but are not in wide use yet.
There can also be complexity in load profiles. If a site is a mixed-use site, the load profile can be complex and strategic attention must be paid to which meters handle what and what energy must be used when. There can be outliers based on extreme weather or unusual usage situations. A property owner will want to think strategically about whether it is advisable to design to these outliers (and spend extra money to have capacity for those extreme cases) or to throw out the outliers and design to a nominal case, whether that’s an 80% or a 95% solution. These are qualitative value judgments – while supported by data and analysis – that require human decision making.
Energy trading markets are unique and complex
Simple net metering is going the way of the dodo. Complex markets for putting energy back on the grid are expanding and evolving quickly. Strategic energy trading markets like PJM and NYSERDA’s VDER are paving the way for other regions across the US and around the world to follow suit, and exploiting these new energy trading markets as revenue streams necessarily puts us back in the mystery and early heuristic stage as we all figure it out.
This doesn’t even cover more complex and unique energy trading situations such as community microgrids and third-party offtakers.
Not everything can be quantified (yet)
Again, we’d like to believe that in the 21st century, every aspect of energy systems can be quantified and then calculated. But while some energy system qualities such as resiliency, particularly in the face of natural disasters, clearly have value, the industry has yet to quantify and codify precisely how resiliency is valued. Indeed the value of resiliency may vary by property owner or investor or property use case, and that makes – you guessed it – more unique situations that require human intervention in the design process.
Operational strategies for sites and their DERs are also still very human-in-the-loop. While we can automate design for nominal usage, especially when the usage is consistent and predictable, humans can still win the day when making smart decisions about how to operate their systems especially in changing or unpredictable conditions.
And the top takeaway here is that all of these things that we’ve talked about – tariffs, load profiles, energy trading markets, and (as yet) unquantifiable strategies – matter. A slight tweak to the valuations, revenue streams, or usage of your DERs can make a big difference in your project’s bottom line. Simple decisions or assumptions can make or break projects. Because of these sensitivities, you are going to want humans to have their eyes, hands, and innovative brains on your energy project throughout the feasibility, design, and operational phases.
Here at muGrid Analytics, we use powerful software tools and big data analysis to help you make great decisions. But our secret sauce isn’t really in the software. It’s in our years of experience, our deep domain expertise, and our razor sharp intuition that’s going to help you meet your site’s unique needs in rapidly evolving markets.
As Peter Asmus of Navigant Energy famously said, “If you’ve seen one microgrid… you’ve seen one microgrid.” Indeed, every microgrid, every system of DERs is still unique. As we as an industry mature energy analysis capability from mystery to heuristic and then finally to algorithm, it’s your human partners that are going to help you get the biggest bang for your energy buck throughout the project life cycle.