Last, Austin SHINES aimed to demonstrate the solution’s methodology would enable the DER grid ecosystem to serve load at a technical cost (System Levelized Cost of Electricity, or System LCOE) of less than the U.S.
The project also produced a methodology to create a replicable DERMS template, adaptable to other regions and market structures. This project developed and deployed the platform as a Distributed Energy Resource Management System (DERMS), engaging multiple advanced controls, to evaluate operation and optimization of a fleet of diverse DER assets, installed at several locations among Austin Energy’s customers and distribution system.
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The Austin SHINES project and solution is a software management platform, for an electric grid with a high penetration of dispersed photovoltaic (PV) solar generation sites, which maintains the traditional power quality and reliability associated with grid service. Finally, the model presented can also be a starting point for designing system operation infrastructure that communicates with the devices that schedule loads in response to price = , We assess the sensitivity of this result to the flexibility of load, along with its relationship to the deployment of renewables. For our illustrative numerical case, derived from the Current Trends scenario of the ERCOT Long Term System Assessment, the average energy arbitrage value per ERCOT customer of optimal load shifting technologies is estimated to be $3 for the 2031 scenario year. Through analytic and numeric assessment of the model, we assess the equilibrium value of optimal electricity load shifting, including how the value changes as more electricity consumers adopt associated technologies. The associated computationally tractable formulation can be used to inform market design or policy analysis in the context of increasing availability of the smart grid technologies that enable optimal load shifting. We analyze a competitive electricity market, where consumers exhibit optimal load shifting behavior to maximize utility and producers/suppliers maximize their profit under supply capacity constraints.