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Industry Education 2018

The goal of the Industry Education program is to help industry executives broaden expertise required for a holistic, data-driven approach to transforming the grid. The program is a two-day intensive featuring lecture-style courses and project-based learning.

Module 1: Cloud Computing

In today's world where cloud computing is a key strategy for many organizations, understanding cloud services and deployment models is critical. For all the fanfare about cloud services, lost in the shuffle is the staggering complexity of implementing distributed, scalable apps built on cloud. Not to mention the endless list of cloud services and acronyms.

As of January 2018, Amazon Web Services (AWS) alone had over 100 different cloud services offerings! Although each of these services are highly modular components that can be used to deploy scalable, fault-tolerant, globally distributed apps, in practice, they present an ever-growing set of new tools that need to be mastered. All these components can have bugs, need troubleshooting, and require support.

In this module, we will walk through a variety of cloud services, provide insights that will help you navigate cloud ecosystem of products and services, and allow you to appropriately staff and prepare for your cloud endeavours. We’ll do this with examples drawn from our own development experience of Visualization and Analytics for Distributed Energy Resources (VADER), a big-data energy analytics platform entirely built on AWS cloud.

Module 2: Machine Learning and AI for Electricity

The goals of this three hour course are to explore how machine learning and artificial intelligence can address critical challenges in electric energy systems in the coming years.  The grid is undergoing a significant change with the increased penetration of renewables, adoption of storage, rise of connected consumers that produce electricity and shape their consumption and the fast adoption of novel power control and monitoring technologies among various other major trends.  The systems of the future will generate a massive amount of different types of data, and offer opportunities to automate action at multiple time and spatial scales. This offers an opportunity to change how we plan and operate the grid including engaging consumers or creating new services. Traditional approaches to managing the grid will need to be combined with new ideas to benefit from the new heterogeneous information streams and to enable the coordination of existing and new resources.

In this class we explore how various novel technologies in machine learning and AI can be repurposed for electricity system applications, what is at the core of these technologies and how to quantify the extraction of value from this information.

Module 3: AI for the Grid, Law and Regulation
Artificial intelligence has the potential to create enormous value for electricity providers and consumers. It also presents new challenges to existing electricity business and regulatory models. This unit will begin by providing a primer on US electricity law and regulation. We will discuss the development of the utility model in the U.S., the balance between state and federal authority in electricity regulation, and the differences between regulated, cost-of-service business models and competitive electricity markets. Then, we will discuss how artificial intelligence is likely to alter current practices and present new challenges for solution providers, regulated utilities, and retail customers in the future. AI presents new challenges because of its rapid innovation cycle, its use cases in regulated and competitive markets, and its ability to rapidly optimize use of resources in response to changing regulatory signals. Finally, we will conclude with a discussion of current experience integrating energy storage into U.S. electricity markets - and of how AI impacts this process. What are the key challenges for integrating storage plus AI into regulated and competitive business models? How does the ability to deploy AI allow for new connections between the regulated and competitive aspects of the US electricity system? What tensions does this create? What solutions are different regional energy regulators and markets permitting?

Module 4: Blockchain for the Grid

The goals of this module are to (1) Differentiate the characteristics of blockchain technologies and digital currencies, (2) Explore the potential for smart contract applications in the energy industry, (3) Evaluate the value proposition for utilizing blockchain for a specific company/organization, and finally (4) Understand the challenges and opportunities of different consensus mechanisms.

Please contact Jon Lo ( for registration to the Industry Education program and any questions you may have.

Stanford’s Bits & Watts program is a new initiative focused on enabling the successful development of the 21st century electricity grid – a new grid paradigm that is needed to successfully incorporate large amounts of clean power and a growing number of distributed energy resources, while simultaneously enabling grid reliability, resilience, security, and affordability. Bits & Watts serves as a unique highly-multidisciplinary honest-broker platform that brings together Stanford’s excellence in research and education across multiple schools with world-class partners from across the electricity ecosystem to identify, develop, test and help deploy new technologies, policies, market structures, financial instruments and business models that will be required to enable the 21st century electricity grid.