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A candid discussion with author, entrepreneur, and clean energy advocate Bill Nussey, the founder of the Freeing Energy Project and the CEO of Solar Inventions. He is a three-time tech CEO, an ex-IBM VP Corporate Strategy, a recovering venture capitalist, a board member, a TED addict, a geek, and a closet scientist.

Watch the 3rd episode of WIP FM 113.0, organized by IEEE Power & Energy Society Young Professionals and hear Damir Novosel, President of Quanta Technology as he shares his wide experience and knowledge.

Welcome to the 2nd episode of WIP FM 113.0, initiated by IEEE Power & Energy Society Young Professionals; to introduce the Leaders & experts from Power & Energy Society.

Meet Nirupama Prakash Kumar, Senior Product Manager - Microgrids at Bloom Energy as she shares her vast experiences and opportunities in Microgrids.

Watch the inaugural episode of WIP FM 113.0, a talk show focusing on introducing the technical leaders in Power and Energy and the different opportunities in this sector. Join us for the 1st Episode to hear from Shay Bahramirad, Vice President of Climate & Resilience with Quanta Technology.

This short paper investigates distribution-level synchrophasor measurement errors with online and offline tests, and mathematically and systematically identifies the actual distribution of the measurement errors through graphical and numerical analysis. It is observed that the measurement errors in both online and offline case studies follow a non-Gaussian distribution, instead of the traditionally assumed Gaussian distribution.

This work presents definitions and metrics developed for quantifying the resilience of the electric power system (EPS) while considering its interdependent operation with the water distribution system (WDS). These metrics are used within a novel formulation in order to determine EPS resilience during the coordinated real-time operation of the two systems where both the operational state and infrastructural configuration of the EPS is taken into account.

Planned islanding is one of the fundamental functions of microgrid (MG) controllers. However, existing planned islanding functions cannot be directly utilized in MGs that have the capability to have both dynamic boundary and multiple sub-MGs. To optimize the smart switch operation and distributed energy resource (DER) output power, a planned islanding algorithm is designed to minimize the battery energy storage systems' power difference before and after a planned islanding.

This paper investigates real-time self-dispatch of a remote wind-storage integrated power plant connecting to the main grid via a transmission line with a limited capacity. Because prediction is a complicated task and inevitably incurs errors, it is a better choice to make real-time decisions based on the information observed in the current time slot without predictions on the uncertain electricity price and wind generation in the future.

In regions with high penetration of Distributed Energy Resources (DER), grid congestion is mostly caused by power feed-in of generators. In this context, conventional approaches for solving the grid congestion problems are Active Power Curtailment (APC) of DER and grid reinforcement. In the wake of increased DER generation, it is not only of interest how to obtain the grid reinforcement, but also how to consider APC during grid planning.

A two-stage machine learning-based approach for creating synthetic phasor measurement unit (PMU) data is proposed in this article. This approach leverages generative adversarial networks (GAN) in data generation and incorporates neural ordinary differential equation (Neural ODE) to guarantee underlying physical meaning.