What does this study find?

Enormous electricity-sector savings can be achieved by scaling and better leveraging local solar and local storage (on the distribution system). While there have been many studies that attempt to demonstrate the potential value (or cost) of distributed energy resources, this is the first study to incorporate results from a modeling tool that is as comprehensive and sophisticated as the WIS:dom-P.

Who created the WIS:dom-P model?

Vibrant Clean Energy, LLC (VCE) created the WIS:dom-P model. VCE, founded by Dr. Christopher Clack, initially  focused on providing free online wind and solar power forecasts, but transitioned into a company with the “purpose of pursuing intelligent transformation of the electricity and energy system to meet the needs of the 21st century.”  You can learn more about VCE here.

Who was this model built for? 

“WIS:dom” stands for “Weather-Informed energy Systems: for design, operations, and markets”, and WIS:dom-”P” is the “Planning Model” version. WIS:dom-P is the “flagship software of VCE for finding the lowest cost market solution for entire energy systems.” It is the first commercial co-optimization model of energy grids that was built from the ground up to incorporate vast volumes of data; starting with high-resolution weather and demand data. It simultaneously co-optimizes the capacity expansion requirements (generation, transmission, and storage) and the dispatch requirements (production cost, power flow, reserves, ramping, and reliability) for the entire electric (energy) grid of interest. The model has been used by a range of energy sector stakeholders, including utilities, co-ops, RTOs, NGOs, legislators and C&I customers. Over the course of this study (2019-2020), VCE augmented the WIS:dom-P software to improve its representation and computations around the distribution-utility interface. To find more information on the model go here. 

What do regulators currently use as a modeling tool when doing capacity and resource planning? 

Regulators (and really, utilities), primarily use a combination of capacity expansion models and production cost models to develop short- and long-term energy plans. Capacity expansion models provide a high-level long-term view of the power system, while production cost models simulate power system operations on shorter time scales using detailed load, transmission, and generation data by minimizing production costs and reliability requirements.  Most grid and system planning processes aren’t equipped to consider resources based on their total costs and benefits to the entire system. That’s because they analyze the grid in a piece-meal fashion in distribution, transmission, and generation modules, lack exhaustive data inputs, and can’t fairly consider smaller resources like DERs.  

How does the WIS:dom-P model differ from the utility planning models used today?

As opposed to running multiple models that analyze the grid in a piece-meal fashion (i.e., capacity expansion and production cost models) and creating energy plans that attempt to balance the results of each, the WIS:dom-P combines capacity expansion and production costs into one model which analyzes  all resources on both the transmission and distribution side of the grid. Further, WIS:dom-P seeks the least-cost system solution while leveraging 10,000 times more data points than traditional models. It utilizes high-resolution weather data to determine resource properties over massive temporal horizons, and can be used on scales ranging from campuses to continents. This gives WIS:dom the ability to analyze the true total system cost of all resources to determine how we most cost-effectively build out the grid. 

Have any states adopted the model? Can regulators use it?

VCE has worked (as a service) with state regulators and others in performing studies, however the tool was not licensable until early in 2020 for most users and no state government currently uses it as a licensed product. WIS:dom-P is a breakthrough model that will likely grow in recognition and adoption by states, utilities, and other entities. VCE is conducting presentations with commissioners and regulators across the country to better educate them on the model and results and to get their feedback on how it can be utilized. 

Why doesn’t the current utility planning model take local solar into account?

While integrated resource planning, grid modernization, and related distributed energy resource dockets and rate cases have increasingly acknowledged and attempted to incorporate projected local solar impacts on the grid, most models treat local solar and storage as an afterthought.  Current models have been more focused on trying to anticipate local solar market growth rather than guide it’s development and take advantage of it to reduce the need for some traditional utility-scale assets.

How does cost savings come about from local solar?

By scaling and optimizing local solar and storage at the distribution level and closer to customer load, we don’t have to over-rely on the most expensive parts of the transmission system and under utilize the distribution system as many traditional planners assume. The daily peaks that the system must ramp up and down to serve can be permanently and more cost-effectively managed by local solar assets, storage injections, and off-peak charging. These DERs cost-effectively reshape the load as seen by the large-scale grid, reducing bulk power system costs and smoothing volatility and variation in load across the system. This allows for a more efficient overall allocation of investments and better utilization of grid assets.  Leveraging local solar and storage for meeting local energy demands also results in deferred or avoided distribution system investments. 

Using this model, what are the benefits of local solar to the ratepayer and the state?

From a pure grid planning perspective, this study shows that when we scale and optimize local solar and storage, we can save a lot of money. . This would naturally result in a reduction in electricity rates. Relatedly, more local solar and storage means more indirect benefits to communities such as jobs, increased economic development, increased resilience, and more equitable access to the benefits of renewables. 

What is the best way for states and utilities to implement the WIS:dom-P model?

Planning decisions are too important to base solely on the output of a single model selected and run by the plan’s proponent. States and utilities should incorporate WIS:dom-P and/or other models with similar capabilities (as they evolve), to help inform integrated resource planning, grid modernization, electrification, and other energy planning exercises. This is happening now, and the results show there are added benefits to using a better modeling tool and minimizing assumptions. It can also be used to challenge utilities on their assumptions that local solar will lead to more costs for ratepayers. 

What happens when states and utilities do not integrate this model in their energy planning analysis?

Utilities and regulators need to work together to achieve these savings, because when they are not savings, they are costs incurred by ratepayers.Therefore, not at least investigating the potential for holistic grid planning could equate to essentially accepting a higher cost grid without exploring all viable options. Notably, while the modeling tool used in this study is highly advanced and relatively novel, the available technologies utilized for deployment in the model itself are commercially available today.

What does this model tell us about how local solar can help modernize the grid?

WIS:dom-P demonstrates how the grid can be better optimized and more cost efficient by scaling and better integrating local solar and storage. As “electrification” of the grid grows across the country, local solar and storage should be built into planning processes to serve as an important resource for meeting increasingly dynamic energy needs.

Can the data from the WIS:dom-P model be broken down at the state level and is there a way to validate the findings of the WIS:dom-P model?

The model is very granular and incorporates significant detail at the state level in its assumptions regarding resource availability, grid infrastructure, and energy flow. It is specifically solving for each Balancing Authority Area (BAA) across the continental U.S. That said, it is difficult to validate findings when considering planning horizons out to 2050. VCE has performed validation of overall buildout of utility wind and solar since 2015. For distribution, because the model and the reality assumptions have to align, validation becomes difficult.

Why should the public give credibility to these results given the fact that the study was funded by companies who stand to benefit from pro-DER policies?

The companies that funded this effort did so without knowing what the results would produce. In fact, one of the most surprising findings of the study was that scaling local solar and storage unlocks the full potential of utility-scale renewables and that the lowest cost grid includes 1,600 GW of utility-scale solar, storage and wind. What’s more, VCE is an independent third-party that provides modeling services and model licenses for a range of stakeholders, from the public sector to utilities to customers. Nearly all the assumptions in the model utilize public data and any alteration is done to improve accuracy (e.g., to reflect state policy mandates or other market realities) and to reflect basic core assumptions associated with the respective modeling scenario. 

Which state is farthest along in creating policies that will realize the full potential of distributed solar and batteries?

States are making advancements in recognizing the potential benefits of local solar and storage through a variety of channels, such as integrated resource planning, grid modernization, and related distributed energy resource dockets and rate cases. States such as California, Hawaii, Massachusetts, and New York are at the forefront of technical integration, valuation and market evolution. However, distribution system planning is happening in other states around the country in response to the rapid growth of distributed energy resources.