New Modeling Software Helps Integrate Distributed Energy Resources Into Electric Grid and City Planning Processes

The SPIDER model is built in Analytica®, a powerful and flexible software platform developed by award-winning decision-analysis and software experts at Lumina Decision Systems.

Lumidyne Consulting LLC announced today the release of a new modeling Software as a Service (SaaS) tool that helps electric distribution utilities, cities and other organizations integrate distributed energy resources (DERs) into their planning processes. The modeling software, named SPIDER™ (Spatial Penetration and Integration of Distributed Energy Resources), is able to:

Forecast spatial adoption and grid impacts of solar PV, electric vehicles (EVs) and battery storage
Help grid planners minimize distribution system costs while ensuring system reliability
Help city planners estimate EV charging station infrastructure requirements
Rapidly update forecasts with new data through automated calibration
Analyze different policy, technology or electric rate scenarios
Account for interactions among and uncertainty across DERs
Cory Welch, founder and president of Lumidyne Consulting, notes that "failing to fully account for DERs in the planning process can result in higher distribution system costs or reduced distribution system reliability." A recent NREL study bolsters this argument and suggests that "the utility-cost impacts of mis-forecasting [distributed] PV adoption can be non-trivial … up to $7 million per terawatt-hour (TWh) of electricity sales." The state of California already requires investor-owned utilities (IOUs) to integrate DERs into their distribution planning processes. Other states (e.g., Nevada and Minnesota) are quickly following suit, and the trend is expected to continue as DERs take hold in other jurisdictions.

Lumidyne's SPIDER model employs a method called System Dynamics, a modeling technique invented at the Massachusetts Institute of Technology (MIT), where Mr. Welch studied under the gurus in the field. "The accuracy, transparency and robustness of SPIDER are unparalleled," Mr. Welch argues, "owing to well-established modeling techniques, robust calibration and the deep expertise" of its staff in modeling these technology markets. He observed that some other approaches seem to be falling into a "false precision" trap and run the risk of losing the forest for the trees. Black-box data analytics or machine learning approaches, he suggests, often fail to account for the dynamics of technology diffusion and system feedback, and typically do not address causality. He argues that the result of these failures is a less accurate forecast at greater computational and staff expense.

SPIDER is currently being applied in San Diego Gas & Electric's (SDG&E) service territory to facilitate distribution system planning and in the City of Fresno, California, to estimate EV charging station infrastructure requirements. Dan Wilson, while serving as lead forecaster in distribution planning at SDG&E, noted that "the model's transparency and visual interface helped us to gain confidence in the results" and that they were "impressed with the attention to detail and comprehensive approach" of the model.

The SPIDER model is built in Analytica®, a powerful and flexible software platform developed by award-winning decision-analysis and software experts at Lumina Decision Systems. Analytica's robust, flexible and transparent approach made it the perfect choice for SPIDER, Mr. Welch notes, and "our close collaboration with Lumina has been instrumental in developing a robust software product."

SPIDER model usage is dictated by each client's unique needs, with delivery options including:

Desktop Application -- Maximum control for end user
Software as a Service (SaaS) -- Secure web interface hosted on scalable cloud computing
Forecasting as a Service (FaaS) -- Regularly updated by Lumidyne staff
About Lumidyne: Lumidyne Consulting applies dynamic modeling to inform the transition to a clean energy future. Its staff has deep expertise in distributed energy resources, advanced modeling techniques and development of customized decision support tools.

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