More Local Solar Means More New Energy Benefits

Why Local Solar For All Costs Less: A New Roadmap for the Lowest Cost Grid

Christopher Clack, Aditya Choukulkar, Brianna Cote, Sarah A, McKee, December 2020 (Vibrant Clean Energy)

Executive Summary

The electricity system in the United States (US) is considered to be one the largest machines ever created. 1 With the advent of clean and renewable technologies, a widespread evolution is occurring. The renewable technologies are lower cost than fossil thermal generation on a levelized cost basis, 2 but their variability creates new and unique constraints and opportunities for the electricity system of the next several decades. Superimposed on the changing structure of the electricity system is a damaged climate that will continue to worsen as mankind continues to emit greenhouse gas (GHG) pollution into the atmosphere. 3

The US electricity system is the second largest in the world (China has the largest). In 2018 it served approximately 150 million customers with over 3,859 terawatt-hours (TWh) of electricity from over 1,190 gigawatts (GW) of generating capacity, routed through 476,000 miles of transmission lines (over 69 kV), 55,000 substations and 6.3 million miles of distribution lines (under 69 kV). 4,5,6 By the end of 2019, there was 86,000 MW of renewable capacity awaiting construction across the US and each year that number continues to grow. 7 The carbon dioxide (CO2) emissions from electricity generation across the US reached an estimated 1,659 million metric tons (mmT) in 2019, accounting for approximately 32% of the total United States (US) energy-related CO2 emissions (5,130 mmT). 8

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The present study demonstrates, quantifies and evaluates the potential value that distributed energy resources (DERs) could provide to the electricity system, while considering as many facets of their inclusion into a sophisticated grid modeling tool. The Weather-Informed energy Systems: for design, operations and markets planning (WIS:dom®- P) optimization software tool is utilized for the present study. A detailed technical document of the WIS:dom®-P software can be found online.9 The modeling software is a combined capacity expansion and production cost model that allows for simultaneous 3- kilometer, 5-minute dispatch and power flow along with multi-decade resource selection. It includes detailed representations of fossil generation, variable resources, storage, transmission and DERs. It also contains policies, mandates, and localized data, as well as engineering parameters and constraints of the electricity system and its components. Some novel features include highly granular weather inputs over the whole US, climate changeinduced changes to energy infrastructure, land use and siting constraints, dynamic transmission line ratings, electrification and novel fuel production endogenously, and detailed storage dispatch algorithms.

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The distribution grid is where the majority of customers connect with the electricity system at large. However, traditional modeling tools ignore its existence almost entirely. Many assume pre-decided buildout rates of distributed solar PV (DPV), energy efficiency (EE), demand-side management (DSM), demand response (DR), and distributed storage (DS). As the electricity system continues to evolve, customers are demanding more local resources. This creates a problem because the providers of electricity (across utility service territories and RTOs) do not possess integrated modeling tools that reveal the opportunities and costs of changing distributed generation and demand as a decision variable. The opportunities could include reduced utility-scale capacity and generation, high-voltage transmission, distribution infrastructure deferments, utility-observed peak load reduction, and increased utility-observed load factors. The costs could be more distribution infrastructure, more high-voltage transmission, increased DER buildout, and utility-scale back-up capacity and generation to cover the DER buildout.

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Vibrant Clean Energy, LLC (VCE®) augmented the WIS:dom-P software to improve its representation and computations of the distribution-utility interface. The augmentations enabled a modeling framework that included the distribution grid and DERs that is tractable and akin to traditional utility planning models.

During the entire study, fifteen nationwide simulations were performed. Numerous intermediate simulations were used to determine the sensitivity of the modeling tool to changes in the augmentation created during the study. The model was initialized and aligned with historical data from 2018 and then the simulations evolved the electricity system across the contiguous United States (CONUS) from 2020 through 2050 in 5-year investment periods. In the present report, we focus on four main scenarios that answer two main questions: 10

1. Can DERs lower costs across the entire electricity system compared with alternatives, while maintaining resource adequacy, reliability and resilience?

2. Can DERs provide support and benefits for clean electricity goals across the entire electricity system?

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The four scenarios simulated for the present report were:

Business-As-Usual, Traditional (“BAU”): Allow economics to drive the changes in the electricity system, while including existing policies, mandates, and incentives through 2050. Deploy WIS:dom-P in a manner that mimics traditional models.

Business-As-Usual, Augmented (“BAU-DER”): Allow economics to drive the changes in the electricity system, while including existing policies, mandates, and incentives through 2050. Deploy the augmented version of WIS:dom-P that includes detailed modeling of the distribution-utility (DU) interface.

Clean Electricity, Traditional (“CE”): Enforce a nationwide clean energy standard (CES) that reduces emissions by 95% from 1990 levels by 2050. Deploy WIS:dom-P in a manner that mimics traditional models.

Clean Electricity, Augmented (“CE-DER”): Enforce a nationwide clean energy standard (CES) that reduces emissions by 95% from 1990 levels by 2050. Deploy the augmented version of WIS:dom-P that includes detailed modeling of the distribution-utility (DU) interface.

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The augmentation of the WIS:dom-P software to include distribution planning cooptimization results in cumulative system-wide savings of $301 billion by 2050 (“BAU” vs “BAU-DER”), which rises to $473 billion when considering a clean energy standard (“CE” vs “CE-DER”). Interestingly, the “CE-DER” scenario pathway is lower cost than the “BAU” scenario to the tune of $88 billion by 2050. Figure ES-1 shows the cumulative system cost savings through 2050.

For the clean electricity system cost savings to materialize, a small amount of additional spending occurs in the first decade, however, for “BAU-DER”, the savings accrue immediately. By 2035, the “BAU-DER” scenario has saved nearly $115 billion over the “BAU” scenario, while the “CE-DER” scenario has accumulated savings of $114 billion compared with the “CE” scenario. Over the same time period, the “CE-DER” scenario is $19 billion more expensive than the “BAU” scenario, but has reduced cumulative emissions by 5,112 mmT (equivalent to a cost of carbon of ~$3.70 per metric ton). By 2050, the scenario has avoided more than 10,000 mmT compared with “BAU” (as depicted in Fig. ES-2), while saving $88 billion in costs.

If a clean electricity mandate were imposed by 2035, rather than the modeled 2050 (and the US could deploy enough generation), the DERs would bring forward the cost savings observed by 2050 to 2035, since they enable more clean utility-scale variable generation to be deployed efficiently.

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The inclusion of distribution modeling within the WIS:dom-P software drives emergent behavior.11 The distribution grid seeks to minimize exposure to the utility grid while maximizing its benefits of being connected by minimizing system costs that includes infrastructure connecting the utility and distribution grids. This manifests as increased load factors as experienced by the utility-scale grid, while reduced peak demand. Further, the more local resources can defer some distribution infrastructure costs. The sum of these is net system cost savings, increased jobs, more manageable installation rates, a more reliable and robust system, and more opportunities for private capital investments.

The striking result is that the cost savings come with relatively little change in the macro-scale view of installed capacities and generation stack. This is because a small change in the tails of production and demand can have amplified cost implications throughout the system. Additionally, the distribution cost augmentation facilitates economic tradeoff between more resources, which improves competition and reduces costs further…

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