The following article, part 1 of 3 in a series about transition to clean energy, comes to you from our affiliate: Beacon Climate Innovations

Racing with Climate Change – Speeding the Energy Transition
Part I: Framing the Renewables Dilemma and the Emerging Tools to Address It

“There is no silver bullet that will decarbonize our economy, but there is silver buckshot”
— A Department of Energy (DOE) Saying

“We can still improve the effectiveness of that buckshot with better aim, sequencing and accountability”
— point of this blog

A Sequence of Instrumental Measures and Vital Roles in Taking Them

The costs for wind & solar and barriers to their entry in the energy markets have been coming down and will continue declining for some time. As these renewable resources proliferate, there is a threshold where their value to the grid and their contribution to decarbonization efforts start to diminish. This is because they are variable energy resources that cannot reliably cover our 24/7/365 energy demands. Other resources must come into play. Depending on locale and which grid (e.g., PJM, CAISO, NEISO), solar & wind are matching anywhere from 5% to 35% of its load. With an ever-growing number of solar – photovoltaic (PV) installations and significant offshore wind farms slated to come online those percentages will increase dramatically over just a handful of years. The Rocky Mountain Institute recently issued a “Power by the Hour” report that explains the dilemma and identifies the threshold where it takes hold. Simply put, the net value of solar & wind alone evaporates at about the 50-yard line on the way to a 100% carbon-free grid.

Adding battery storage is an obvious answer. However, more and more energy storage will be required to match an increasing amount of the 24 hour -365 days/year load. As a result, even with the cost of battery storage declining rapidly – the cost to match more of the load only adds to a “snowball” of increasing costs. This is best depicted in the following graph from the RMI Report.

The above example identifies ~ 55% load match as the inflection point where system costs starts to skyrocket as more battery capacity is added.

The next series of graphs is intended to illustrate this phenomenon in another way. These graphs are representative of trends that can occur with increasing installation of wind & solar (PV), but don’t reflect specific data from one grid or load profile to the other.

Graph A: Represents the cost of adding solar (photovoltaic-PV) & wind without any battery energy storage (BESS) to the energy mix (blue) and its value to serving the grid (orange). In short it identifies a point where the “supply” at the time it is available exceeds the “demand” at the time it is needed. This is the point where the “net value” (NVG) goes negative (cost exceeds value) and only gets worse as more supply is added.

Experts representing specific carbon-free or carbon neutralizing, non-renewable technologies such as nuclear, direct air carbon capture and geo-engineering see that inflection point as the opportunity for their solutions as the point to fill the gap.

Graph B: Illustrates the impact of adding battery capacity (BESS) to retain the value of the Wind + Solar (PV) to the grid. This graph identifies the point where the cost to match the load exceeds its value and again the “net value” (NVG) goes negative. This illustration depicts a very modest inflection point shift. Clearly that shift can improve with more dramatic cost reduction in battery technologies, perhaps coming from long-duration flow batteries and other chemistries better suited for stationary applications (e.g., zinc).

There is another suite of powerful tools available today for communities, large and small, to extend the value of PV & wind and push the inflection point to the right. For purposes of this blog, let’s categorize these tools under “Smart Grid Interactive” SGI. These include “Virtual Power Plant”, multi-use platforms (e.g., microgrid, EV infrastructure), flexible demand resources (e.g., heat pumps with thermal storage), DER/DSM optimization platforms, combined heat & power (CH&P) and non-battery storage (e.g., flywheels). These “smart” tools, applied in concert with building and operation efficiency measures, cost-effectively creates platforms to match variable energy supply (PV & Wind) with the demand. They do so by leveraging new/existing sources of excess/wasted energy and employing edge control capabilities with real-time, data-driven, machine learning/AI techniques that optimally redeploy the capacity to match demand with supply.

An example includes retrofitting low-income housing facilities with heat pumps that integrate thermal storage and aggregating the energy storage capacity via virtual power plant portal. The residents will enjoy improved living conditions and energy savings without interruption while the local utility has unrestricted access to the storage capacity that they can beneficially apply to their demand curve. Another example includes PV/Battery micro-grids for critical facilities (e.g., hospitals) that replace/avoid fossil fuel backup generators for emergency conditions while cost-effectively reducing energy consumption and peak demand during day-to-day operation. NOTE Other examples abound. Please reach out to Beacon Climate for further details.

Graph C considers what the inclusion of SGI can do for the Value-to-Grid equation. Note how in this representation that the “net value” NVG crossover pushes towards 80%. Faster and more widespread application of SGI tools can push it even further, while slower and limited application will stifle its contribution.

Graph D better depicts the comparison between the different scenarios discussed above. Percent % match along the x-axis is analogous to % saturation is analogous to time. It becomes clear to see that SGI suite of tools can expedite the clean energy transition before having to deploy technologies that come with inherently higher risks.

It’s important to highlight the “grid-interactivity” of the SGI suite of tools. They are not relying on the dedicated, “one-way” assets of the conventional carbon-centric grid, but rather shared, multi-directional assets of a decarbonized, “next generation” grid. What is particularly compelling about these SGI platforms is that they can be deployed in modular, phased ways. They can be easily refined in the “field” with negligible consequences to the end-users. This is quite unlike nuclear or geo-engineering technologies requiring large-scale and/or high-volume commitments to justify initial deployments. These grand technologies come with costly and possibly irreversible consequences in the event of failure. Hence, the extensive scrutiny that they receive prior to any commercial deployment.

Conversely, SGI platforms learn and improve as they operate and expand their network. They readily adapt as resources and behaviors evolve with the energy transition. This is not to say that they are replacements for other technologies, but they do bring diversity, innovation, and resilience safely to the mix early in this process. They are ready now, buying more time for other emerging technologies to “get it right”. It also must be said that SGI puts more resources and control in the hands of local communities and their decision-makers rather than larger regional, national and global entities/institutions – that simply can’t match the understanding and awareness of local needs of local leadership.


It can’t be re-iterated enough. Smart Grid Interactive (SGI) tools are available NOW. They facilitate agility – the primary attribute for a successful energy transition. Because they are self-learning, software-centric, these tools will improve with real world deployment, built-in user feedback and direct tie-ins to fast-evolving data sources and metrics that are needed to navigate climate change and the energy transition. The key is to step up the pace of deployment. The sooner that they are deployed, the greater their beneficial impact. This circles back to the original premise of this blog, SGI tools should be at the front of (sequencing) of that “silver buckshot”. The questions of which entities are best suited to lead the deployment (aiming) of these tools and necessary criteria to establish their effectiveness (accountability) in the context of the other actions are the subject of the Part II and III of this blog series. STAY TUNED!

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