Dynamic Control and Optimization of Distributed Energy Resources in a Microgrid


As we tend to transition toward an influence grid that is increasingly primarily based on renewable resources like solar and wind, the intelligent control of distributed energy resources (DERs) together with photovoltaic (PV) arrays, controllable masses, energy storage, and plug-in electrical vehicles (EVs) can be crucial to realizing an influence grid that may handle each the variability and unpredictability of renewable energy sources along with increasing system complexity. Realizing such a decentralized and dynamic infrastructure will require the flexibility to resolve massive scale problems in real-time with hundreds of thousands of DERs simultaneously on-line. Because of the size of the optimization downside, we have a tendency to use an iterative distributed algorithm previously developed in our group to work each DER independently and autonomously among this environment. The algorithm is deployed inside a framework that permits the microgrid to dynamically adapt to changes within the operating setting. Specifically, we tend to consider a business web site equipped with on-website PV generation, partially curtailable load, EV charge stations and a battery electrical storage unit. The web site operates as a small microgrid that may participate in the wholesale market on the ability grid. We tend to report results for simulations using real-information that demonstrate the flexibility of the optimization framework to reply dynamically in real-time to external conditions while maintaining the practical needs of all DERs.

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